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Diffusion MRI in early cancer therapeutic response assessment

dc.contributor.authorGalbán, C. J.
dc.contributor.authorHoff, B. A.
dc.contributor.authorChenevert, T. L.
dc.contributor.authorRoss, B. D.
dc.date.accessioned2017-04-13T20:34:25Z
dc.date.available2018-05-15T21:02:50Zen
dc.date.issued2017-03
dc.identifier.citationGalbán, C. J. ; Hoff, B. A.; Chenevert, T. L.; Ross, B. D. (2017). "Diffusion MRI in early cancer therapeutic response assessment." NMR in Biomedicine 30(3): n/a-n/a.
dc.identifier.issn0952-3480
dc.identifier.issn1099-1492
dc.identifier.urihttps://hdl.handle.net/2027.42/136261
dc.publisherWHO
dc.publisherWiley Periodicals, Inc.
dc.subject.otherdiffusion‐weighted MRI
dc.subject.otherimaging biomarker
dc.subject.othercancer treatment response
dc.subject.otherreview article
dc.subject.otherfunctional diffusion map
dc.titleDiffusion MRI in early cancer therapeutic response assessment
dc.typeArticleen_US
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelElectrical Engineering
dc.subject.hlbsecondlevelPhysics
dc.subject.hlbtoplevelScience
dc.subject.hlbtoplevelEngineering
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/136261/1/nbm3458_am.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/136261/2/nbm3458.pdf
dc.identifier.doi10.1002/nbm.3458
dc.identifier.sourceNMR in Biomedicine
dc.identifier.citedreferenceChoi SA, Lee SS, Jung IH, Kim HA, Byun JH, Lee MG. The effect of gadoxetic acid enhancement on lesion detection and characterisation using T(2) weighted imaging and diffusion weighted imaging of the liver. Br. J. Radiol. 2012; 85 ( 1009 ): 29 – 36.
dc.identifier.citedreferenceNemoto K, Tateishi T, Ishidate T. Changes in diffusion‐weighted images for visualizing prostate cancer during antiandrogen therapy: preliminary results. Urol. Int. 2010; 85 ( 4 ): 421 – 426.
dc.identifier.citedreferenceSong I, Kim CK, Park BK, Park W. Assessment of response to radiotherapy for prostate cancer: value of diffusion‐weighted MRI at 3 T. Am. J. Roentgenol. 2010; 194 ( 6 ): W477 – W482.
dc.identifier.citedreferenceCurvo‐Semedo L, Lambregts DM, Maas M, Thywissen T, Mehsen RT, Lammering G, Beets GL, Caseiro‐Alves F, Beets‐Tan RG. Rectal cancer: assessment of complete response to preoperative combined radiation therapy with chemotherapy—conventional MR volumetry versus diffusion‐weighted MR imaging. Radiology 2011; 260 ( 3 ): 734 – 743.
dc.identifier.citedreferenceJang KM, Kim SH, Choi D, Lee SJ, Park MJ, Min K. Pathological correlation with diffusion restriction on diffusion‐weighted imaging in patients with pathological complete response after neoadjuvant chemoradiation therapy for locally advanced rectal cancer: preliminary results. Br. J. Radiol. 2012; 85 ( 1017 ): e566 – e572.
dc.identifier.citedreferenceKim SH, Lee JY, Lee JM, Han JK, Choi BI. Apparent diffusion coefficient for evaluating tumour response to neoadjuvant chemoradiation therapy for locally advanced rectal cancer. Eur. Radiol. 2011; 21 ( 5 ): 987 – 995.
dc.identifier.citedreferenceLambrecht M, Vandecaveye V, De Keyzer F, Roels S, Penninckx F, Van Cutsem E, Filip C, Haustermans K. Value of diffusion‐weighted magnetic resonance imaging for prediction and early assessment of response to neoadjuvant radiochemotherapy in rectal cancer: preliminary results. Int. J. Radiat. Oncol. Biol. Phys. 2012; 82 ( 2 ): 863 – 870.
dc.identifier.citedreferenceLambregts DM, Beets GL, Maas M, Curvo‐Semedo L, Kessels AG, Thywissen T, Beets‐Tan RG. Tumour ADC measurements in rectal cancer: effect of ROI methods on ADC values and interobserver variability. Eur. Radiol. 2011; 21 ( 12 ): 2567 – 2574.
dc.identifier.citedreferenceLambregts DM, Vandecaveye V, Barbaro B, Bakers FC, Lambrecht M, Maas M, Haustermans K, Valentini V, Beets GL, Beets‐Tan RG. Diffusion‐weighted MRI for selection of complete responders after chemoradiation for locally advanced rectal cancer: a multicenter study. Ann. Surg. Oncol. 2011; 18 ( 8 ): 2224 – 2231.
dc.identifier.citedreferenceSeehaus A, Vacaro C, Ocantos J, Varela A, Savluk L, Ojea Quintana G, Rossi G, Weimbaur V, Pablo Santino J, Garcia‐Monaco R. [Diffusion‐weighted MR imaging in patients with rectal cancer: our initial experience]. Acta Gastroenterol. Latinoam. 2011; 41 ( 3 ): 199 – 207.
dc.identifier.citedreferenceDeVries AF, Kremser C, Hein PA, Griebel J, Krezcy A, Ofner D, Pfeiffer KP, Lukas P, Judmaier W. Tumor microcirculation and diffusion predict therapy outcome for primary rectal carcinoma. Int. J. Radiat. Oncol. Biol. Phys. 2003; 56 ( 4 ): 958 – 965.
dc.identifier.citedreferenceLambrecht M, Deroose C, Roels S, Vandecaveye V, Penninckx F, Sagaert X, van Cutsem E, de Keyzer F, Haustermans K. The use of FDG‐PET/CT and diffusion‐weighted magnetic resonance imaging for response prediction before, during and after preoperative chemoradiotherapy for rectal cancer. Acta Oncol. 2010; 49 ( 7 ): 956 – 963.
dc.identifier.citedreferenceBajpai J, Gamnagatti S, Kumar R, Sreenivas V, Sharma MC, Khan SA, Rastogi S, Malhotra A, Safaya R, Bakhshi S. Role of MRI in osteosarcoma for evaluation and prediction of chemotherapy response: correlation with histological necrosis. Pediatr. Radiol. 2011; 41 ( 4 ): 441 – 450.
dc.identifier.citedreferenceBaunin C, Schmidt G, Baumstarck K, Bouvier C, Gentet JC, Aschero A, Ruocco A, Bourliere B, Gorincour G, Desvignes C, Colavolpe N, Bollini G, Auqier P, Petit P. Value of diffusion‐weighted images in differentiating mid‐course responders to chemotherapy for osteosarcoma compared to the histological response: preliminary results. Skel. Radiol. 2012; 41 ( 9 ): 1141 – 1149.
dc.identifier.citedreferenceDudeck O, Zeile M, Pink D, Pech M, Tunn PU, Reichardt P, Ludwig WD, Hamm B. Diffusion‐weighted magnetic resonance imaging allows monitoring of anticancer treatment effects in patients with soft‐tissue sarcomas. J. Magn. Reson. Imaging 2008; 27 ( 5 ): 1109 – 1113.
dc.identifier.citedreferenceOka K, Yakushiji T, Sato H, Hirai T, Yamashita Y, Mizuta H. The value of diffusion‐weighted imaging for monitoring the chemotherapeutic response of osteosarcoma: a comparison between average apparent diffusion coefficient and minimum apparent diffusion coefficient. Skel. Radiol. 2010; 39 ( 2 ): 141 – 146.
dc.identifier.citedreferenceUhl M, Saueressig U, Koehler G, Kontny U, Niemeyer C, Reichardt W, Ilyasof K, Bley T, Langer M. Evaluation of tumour necrosis during chemotherapy with diffusion‐weighted MR imaging: preliminary results in osteosarcomas. Pediatr. Radiol. 2006; 36 ( 12 ): 1306 – 1311.
dc.identifier.citedreferenceEinarsdottir H, Karlsson M, Wejde J, Bauer HC. Diffusion‐weighted MRI of soft tissue tumours. Eur. Radiol. 2004; 14 ( 6 ): 959 – 963.
dc.identifier.citedreferenceKoh DM, Blackledge M, Collins DJ, Padhani AR, Wallace T, Wilton B, Taylor NJ, Stirling JJ, Sinha R, Walicke P, Leach MO, Judson I, Nathan P. Reproducibility and changes in the apparent diffusion coefficients of solid tumours treated with combretastatin A4 phosphate and bevacizumab in a two‐centre phase I clinical trial. Eur. Radiol. 2009; 19 ( 11 ): 2728 – 2738.
dc.identifier.citedreferenceDirix P, Vandecaveye V, De Keyzer F, Stroobants S, Hermans R, Nuyts S. Dose painting in radiotherapy for head and neck squamous cell carcinoma: value of repeated functional imaging with (18)F‐FDG PET, (18)F‐fluoromisonidazole PET, diffusion‐weighted MRI, and dynamic contrast‐enhanced MRI. J. Nucl. Med. 2009; 50 ( 7 ): 1020 – 1027.
dc.identifier.citedreferenceKing AD, Mo FK, Yu KH, Yeung DK, Zhou H, Bhatia KS, Tse GM, Vlantis AC, Wong JK, Ahuja AT. Squamous cell carcinoma of the head and neck: diffusion‐weighted MR imaging for prediction and monitoring of treatment response. Eur. Radiol. 2010; 20 ( 9 ): 2213 – 2220.
dc.identifier.citedreferenceVandecaveye V, Dirix P, De Keyzer F, de Beeck KO, Vander Poorten V, Roebben I, Nuyts S, Hermans R. Predictive value of diffusion‐weighted magnetic resonance imaging during chemoradiotherapy for head and neck squamous cell carcinoma. Eur. Radiol. 2010; 20 ( 7 ): 1703 – 1714.
dc.identifier.citedreferenceVandecaveye V, Dirix P, De Keyzer F, Op de Beeck K, Vander Poorten V, Hauben E, Lambrecht M, Nuyts S, Hermans R, Levy A. Diffusion‐weighted magnetic resonance imaging early after chemoradiotherapy to monitor treatment response in head‐and‐neck squamous cell carcinoma. Int. J. Radiat. Oncol. Biol. Phys. 2012; 82 ( 3 ): 1098 – 1107.
dc.identifier.citedreferenceKato H, Kanematsu M, Tanaka O, Mizuta K, Aoki M, Shibata T, Yamashita T, Hirose Y, Hoshi H. Head and neck squamous cell carcinoma: usefulness of diffusion‐weighted MR imaging in the prediction of a neoadjuvant therapeutic effect. Eur. Radiol. 2009; 19 ( 1 ): 103 – 109.
dc.identifier.citedreferenceKim S, Loevner L, Quon H, Sherman E, Weinstein G, Kilger A, Poptani H. Diffusion‐weighted magnetic resonance imaging for predicting and detecting early response to chemoradiation therapy of squamous cell carcinomas of the head and neck. Clin. Cancer Res. 2009; 15 ( 3 ): 986 – 994.
dc.identifier.citedreferenceGehan EA, Schneiderman MA. Historical and methodological developments in clinical trials at the National Cancer Institute. Stat. Med. 1990; 9 ( 8 ): 871 – 80 discussion 903–906.
dc.identifier.citedreferenceEisenhauer EA, Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R, Dancey J, Arbuck S, Gwyther S, Mooney M, Rubinstein L, Shankar L, Dodd L, Kaplan R, Lacombe D, Verweij J. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur. J. Cancer 2009; 45 ( 2 ): 228 – 247.
dc.identifier.citedreferenceWen PY, Macdonald DR, Reardon DA, Cloughesy TF, Sorensen AG, Galanis E, Degroot J, Wick W, Gilbert MR, Lassman AB, Tsien C, Mikkelsen T, Wong ET, Chamberlain MC, Stupp R, Lamborn KR, Vogelbaum MA, van den Bent MJ, Chang SM. Updated response assessment criteria for high‐grade gliomas: response assessment in neuro‐oncology working group. J. Clin. Oncol. 2010; 28 ( 11 ): 1963 – 1972.
dc.identifier.citedreferenceWorld Health Organization (WHO). WHO Handbook for Reporting Results of Cancer Treatment. Geneva: WHO; 1979.
dc.identifier.citedreferenceJaffe CC. Measures of response: RECIST, WHO, and new alternatives. J. Clin. Oncol. 2006; 24 ( 20 ): 3245 – 3251.
dc.identifier.citedreferenceChoi H, Charnsangavej C, de Castro Faria S, Tamm EP, Benjamin RS, Johnson MM, Macapinlac HA, Podoloff DA. CT evaluation of the response of gastrointestinal stromal tumors after imatinib mesylate treatment: a quantitative analysis correlated with FDG PET findings. Am. J. Roentgenol. 2004; 183 ( 6 ): 1619 – 1628.
dc.identifier.citedreferenceStrumberg D, Richly H, Hilger RA, Schleucher N, Korfee S, Tewes M, Faghih M, Brendel E, Voliotis D, Haase CG, Schwartz B, Awada A, Voigtmann R, Scheulen ME, Seeber S. Phase I clinical and pharmacokinetic study of the novel Raf kinase and vascular endothelial growth factor receptor inhibitor BAY 43‐9006 in patients with advanced refractory solid tumors. J. Clin. Oncol. 2005; 23 ( 5 ): 965 – 972.
dc.identifier.citedreferenceBarrington SF, Mikhaeel NG, Kostakoglu L, Meignan M, Hutchings M, Mueller SP, Schwartz LH, Zucca E, Fisher RI, Trotman J, Hoekstra OS, Hicks RJ, O’Doherty MJ, Hustinx R, Biggi A, Cheson BD. Role of imaging in the staging and response assessment of lymphoma: consensus of the International Conference on Malignant Lymphomas Imaging Working Group. J. Clin. Oncol. 2014; 32 ( 27 ): 3048 – 3058.
dc.identifier.citedreferenceChinnaiyan AM, Prasad U, Shankar S, Hamstra DA, Shanaiah M, Chenevert TL, Ross BD, Rehemtulla A. Combined effect of tumor necrosis factor‐related apoptosis‐inducing ligand and ionizing radiation in breast cancer therapy. Proc. Natl. Acad. Sci. USA 2000; 97 ( 4 ): 1754 – 1759.
dc.identifier.citedreferenceCheson BD, Fisher RI, Barrington SF, Cavalli F, Schwartz LH, Zucca E, Lister TA, Alliance AL, Lymphoma G, Eastern Cooperative Oncology G, European Mantle Cell Lymphoma C, Italian Lymphoma F, European Organisation for R, Treatment of Cancer/Dutch Hemato‐Oncology G, Grupo Espanol de Medula O, German High‐Grade Lymphoma Study G, German Hodgkin’s Study G, Japanese Lymphorra Study G, Lymphoma Study A, Group NCT, Nordic Lymphoma Study G, Southwest Oncology G, United Kingdom National Cancer Research I. Recommendations for initial evaluation, staging, and response assessment of Hodgkin and non‐Hodgkin lymphoma: the Lugano classification. J. Clin. Oncol. 2014; 32 ( 27 ): 3059 – 3068.
dc.identifier.citedreferenceStejskal E, Tanner J. Spin diffusion measurements: spin echoes in the presence of a time‐dependent field gradient. J. Chem. Phys. 1965; 42 ( 1 ): 288 – 292.
dc.identifier.citedreferenceThomsen C, Henriksen O, Ring P. In vivo measurement of water self diffusion in the human brain by magnetic resonance imaging. Acta Radiol. 1987; 28 ( 3 ): 353 – 361.
dc.identifier.citedreferenceMerboldt KD, Bruhn H, Frahm J, Gyngell ML, Hanicke W, Deimling M. MRI of “diffusion” in the human brain: new results using a modified CE‐FAST sequence. Magn. Reson. Med. 1989; 9 ( 3 ): 423 – 429.
dc.identifier.citedreferenceLe Bihan D, Breton E, Lallemand D, Aubin ML, Vignaud J, Laval‐Jeantet M. Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology 1988; 168 ( 2 ): 497 – 505.
dc.identifier.citedreferenceLe Bihan D. Molecular diffusion nuclear magnetic resonance imaging. Magn. Reson. Q. 1991; 7 ( 1 ): 1 – 30.
dc.identifier.citedreferenceBammer R. Basic principles of diffusion‐weighted imaging. Eur. J. Radiol. 2003; 45 ( 3 ): 169 – 184.
dc.identifier.citedreferencePadhani AR, Liu G, Koh DM, Chenevert TL, Thoeny HC, Takahara T, Dzik‐Jurasz A, Ross BD, Van Cauteren M, Collins D, Hammoud DA, Rustin GJ, Taouli B, Choyke PL. Diffusion‐weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 2009; 11 ( 2 ): 102 – 125.
dc.identifier.citedreferenceEdelman RR, Wielopolski P, Schmitt F. Echo‐planar MR imaging. Radiology 1994; 192 ( 3 ): 600 – 612.
dc.identifier.citedreferenceHamstra DA, Rehemtulla A, Ross BD. Diffusion magnetic resonance imaging: a biomarker for treatment response in oncology. J. Clin. Oncol. 2007; 25 ( 26 ): 4104 – 4109.
dc.identifier.citedreferenceLyng H, Haraldseth O, Rofstad EK. Measurement of cell density and necrotic fraction in human melanoma xenografts by diffusion weighted magnetic resonance imaging. Magn. Reson. Med. 2000; 43 ( 6 ): 828 – 836.
dc.identifier.citedreferenceGuo AC, Cummings TJ, Dash RC, Provenzale JM. Lymphomas and high‐grade astrocytomas: comparison of water diffusibility and histologic characteristics. Radiology 2002; 224 ( 1 ): 177 – 183.
dc.identifier.citedreferenceChenevert TL, Stegman LD, Taylor JM, Robertson PL, Greenberg HS, Rehemtulla A, Ross BD. Diffusion magnetic resonance imaging: an early surrogate marker of therapeutic efficacy in brain tumors. J. Natl. Cancer Inst. 2000; 92 ( 24 ): 2029 – 2036.
dc.identifier.citedreferenceChenevert TL, McKeever PE, Ross BD. Monitoring early response of experimental brain tumors to therapy using diffusion magnetic resonance imaging. Clin. Cancer Res. 1997; 3 ( 9 ): 1457 – 1466.
dc.identifier.citedreferenceLe Bihan D. The ’wet mind’: water and functional neuroimaging. Phys. Med. Biol. 2007; 52 ( 7 ): R57 – 90.
dc.identifier.citedreferenceChenevert TL, Sundgren PC, Ross BD. Diffusion imaging: insight to cell status and cytoarchitecture. Neuroimaging Clin. N. Am. 2006; 16 ( 4 ): 619 – 632 viii–ix.
dc.identifier.citedreferenceRoss BD, Moffat BA, Lawrence TS, Mukherji SK, Gebarski SS, Quint DJ, Johnson TD, Junck L, Robertson PL, Muraszko KM, Dong Q, Meyer CR, Bland PH, McConville P, Geng H, Rehemtulla A, Chenevert TL. Evaluation of cancer therapy using diffusion magnetic resonance imaging. Mol. Cancer Ther. 2003; 2 ( 6 ): 581 – 587.
dc.identifier.citedreferenceHuang CF, Chou HH, Tu HT, Yang MS, Lee JK, Lin LY. Diffusion magnetic resonance imaging as an evaluation of the response of brain metastases treated by stereotactic radiosurgery. Surg. Neurol. 2008; 69 ( 1 ): 62 – 68 discussion 68.
dc.identifier.citedreferenceLee KC, Hamstra DA, Bhojani MS, Khan AP, Ross BD, Rehemtulla A. Noninvasive molecular imaging sheds light on the synergy between 5‐fluorouracil and TRAIL/Apo2L for cancer therapy. Clin. Cancer Res. 2007; 13 ( 6 ): 1839 – 1846.
dc.identifier.citedreferenceLee KC, Hall DE, Hoff BA, Moffat BA, Sharma S, Chenevert TL, Meyer CR, Leopold WR, Johnson TD, Mazurchuk RV, Rehemtulla A, Ross BD. Dynamic imaging of emerging resistance during cancer therapy. Cancer Res. 2006; 66 ( 9 ): 4687 – 4892.
dc.identifier.citedreferenceLee KC, Bradley DA, Hussain M, Meyer CR, Chenevert TL, Jacobson JA, Johnson TD, Galban CJ, Rehemtulla A, Pienta KJ, Ross BD. A feasibility study evaluating the functional diffusion map as a predictive imaging biomarker for detection of treatment response in a patient with metastatic prostate cancer to the bone. Neoplasia 2007; 9 ( 12 ): 1003 – 1011.
dc.identifier.citedreferenceHamstra DA, Lee KC, Tychewicz JM, Schepkin VD, Moffat BA, Chen M, Dornfeld KJ, Lawrence TS, Chenevert TL, Ross BD, Gelovani JT, Rehemtulla A. The use of 19 F spectroscopy and diffusion‐weighted MRI to evaluate differences in gene‐dependent enzyme prodrug therapies. Mol. Ther. 2004; 10 ( 5 ): 916 – 928.
dc.identifier.citedreferenceBufi E, Belli P, Di Matteo M, Terribile D, Franceschini G, Nardone L, Petrone G, Bonomo L. Effect of breast cancer phenotype on diagnostic performance of MRI in the prediction to response to neoadjuvant treatment. Eur. J. Radiol. 2014; 83 ( 9 ): 1631 – 1638.
dc.identifier.citedreferenceGaeta M, Benedetto C, Minutoli F, D’Angelo T, Amato E, Mazziotti S, Racchiusa S, Mormina E, Blandino A, Pergolizzi S. Use of diffusion‐weighted, intravoxel incoherent motion, and dynamic contrast‐enhanced MR imaging in the assessment of response to radiotherapy of lytic bone metastases from breast cancer. Acad. Radiol. 2014; 21 ( 10 ): 1286 – 1293.
dc.identifier.citedreferenceLiu L, Wu N, Ouyang H, Dai JR, Wang WH. Diffusion‐weighted MRI in early assessment of tumour response to radiotherapy in high‐risk prostate cancer. Br. J. Radiol. 2014; 87 ( 1043 ): 20140359.
dc.identifier.citedreferencePickles MD, Gibbs P, Lowry M, Turnbull LW. Diffusion changes precede size reduction in neoadjuvant treatment of breast cancer. Magn. Reson. Imaging 2006; 24 ( 7 ): 843 – 847.
dc.identifier.citedreferenceSharma U, Danishad KK, Seenu V, Jagannathan NR. Longitudinal study of the assessment by MRI and diffusion‐weighted imaging of tumor response in patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy. NMR Biomed. 2009; 22 ( 1 ): 104 – 113.
dc.identifier.citedreferenceTheilmann RJ, Borders R, Trouard TP, Xia G, Outwater E, Ranger‐Moore J, Gillies RJ, Stopeck A. Changes in water mobility measured by diffusion MRI predict response of metastatic breast cancer to chemotherapy. Neoplasia 2004; 6 ( 6 ): 831 – 837.
dc.identifier.citedreferenceYankeelov TE, Lepage M, Chakravarthy A, Broome EE, Niermann KJ, Kelley MC, Meszoely I, Mayer IA, Herman CR, McManus K, Price RR, Gore JC. Integration of quantitative DCE‐MRI and ADC mapping to monitor treatment response in human breast cancer: initial results. Magn. Reson. Imaging 2007; 25 ( 1 ): 1 – 13.
dc.identifier.citedreferenceBonekamp S, Jolepalem P, Lazo M, Gulsun MA, Kiraly AP, Kamel IR. Hepatocellular carcinoma: response to TACE assessed with semiautomated volumetric and functional analysis of diffusion‐weighted and contrast‐enhanced MR imaging data. Radiology 2011; 260 ( 3 ): 752 – 761.
dc.identifier.citedreferenceCorona‐Villalobos CP, Halappa VG, Geschwind JF, Bonekamp S, Reyes D, Cosgrove D, Pawlik TM, Kamel IR. Volumetric assessment of tumour response using functional MR imaging in patients with hepatocellular carcinoma treated with a combination of doxorubicin‐eluting beads and sorafenib. Eur. Radiol. 2014; 25: 380 – 390.
dc.identifier.citedreferenceDeng J, Miller FH, Rhee TK, Sato KT, Mulcahy MF, Kulik LM, Salem R, Omary RA, Larson AC. Diffusion‐weighted MR imaging for determination of hepatocellular carcinoma response to yttrium‐90 radioembolization. J. Vasc. Interv. Radiol. 2006; 17 ( 7 ): 1195 – 2200.
dc.identifier.citedreferenceKamel IR, Bluemke DA, Eng J, Liapi E, Messersmith W, Reyes DK, Geschwind JF. The role of functional MR imaging in the assessment of tumor response after chemoembolization in patients with hepatocellular carcinoma. J. Vasc. Intervent. Radiol. 2006; 17 ( 3 ): 505 – 512.
dc.identifier.citedreferenceKamel IR, Liapi E, Reyes DK, Zahurak M, Bluemke DA, Geschwind JF. Unresectable hepatocellular carcinoma: serial early vascular and cellular changes after transarterial chemoembolization as detected with MR imaging. Radiology 2009; 250 ( 2 ): 466 – 473.
dc.identifier.citedreferenceKamel IR, Reyes DK, Liapi E, Bluemke DA, Geschwind JF. Functional MR imaging assessment of tumor response after 90 Y microsphere treatment in patients with unresectable hepatocellular carcinoma. J. Vasc. Intervent. Radiol. 2007; 18 ( 1 Pt 1 ): 49 – 56.
dc.identifier.citedreferenceMannelli L, Kim S, Hajdu CH, Babb JS, Taouli B. Serial diffusion‐weighted MRI in patients with hepatocellular carcinoma: prediction and assessment of response to transarterial chemoembolization. Preliminary experience. Eur. J. Radiol. 2013; 82 ( 4 ): 577 – 582.
dc.identifier.citedreferenceRhee TK, Naik NK, Deng J, Atassi B, Mulcahy MF, Kulik LM, Ryu RK, Miller FH, Larson AC, Salem R, Omary RA. Tumor response after yttrium‐90 radioembolization for hepatocellular carcinoma: comparison of diffusion‐weighted functional MR imaging with anatomic MR imaging. J. Vasc. Intervent. Radiol. 2008; 19 ( 8 ): 1180 – 1186.
dc.identifier.citedreferenceYu JS, Kim JH, Chung JJ, Kim KW. Added value of diffusion‐weighted imaging in the MRI assessment of perilesional tumor recurrence after chemoembolization of hepatocellular carcinomas. J. Magn. Reson. Imaging 2009; 30 ( 1 ): 153 – 160.
dc.identifier.citedreferenceZelhof B, Pickles M, Liney G, Gibbs P, Rodrigues G, Kraus S, Turnbull L. Correlation of diffusion‐weighted magnetic resonance data with cellularity in prostate cancer. BJU Int. 2009; 103: 883 – 888.
dc.identifier.citedreferenceBarbaro B, Vitale R, Valentini V, Illuminati S, Vecchio FM, Rizzo G, Gambacorta MA, Coco C, Crucitti A, Persiani R, Sofo L, Bonomo L. Diffusion‐weighted magnetic resonance imaging in monitoring rectal cancer response to neoadjuvant chemoradiotherapy. Int. J. Radiat. Oncol. Biol. Phys. 2012; 83 ( 2 ): 594 – 599.
dc.identifier.citedreferenceBirlik B, Obuz F, Elibol FD, Celik AO, Sokmen S, Terzi C, Sagol O, Sarioglu S, Gorken I, Oztop L. Diffusion‐weighted MRI and MR‐volumetry in the evaluation of tumor response after preoperative chemoradiotherapy in patients with locally advanced rectal cancer. Magn. Reson. Imaging 2015; 33: 201 – 212.
dc.identifier.citedreferenceCarbone SF, Pirtoli L, Ricci V, Carfagno T, Tini P, Lazzi S, Volterrani L. Diffusion‐weighted MR volumetry for assessing the response of rectal cancer to combined radiation therapy with chemotherapy. Radiology 2012; 263 ( 1 ): 311.
dc.identifier.citedreferenceCarbone SF, Pirtoli L, Ricci V, Venezia D, Carfagno T, Lazzi S, Mourmouras V, Lorenzi B, Volterrani L. Assessment of response to chemoradiation therapy in rectal cancer using MR volumetry based on diffusion‐weighted data sets: a preliminary report. Radiol. Med. 2012; 117 ( 7 ): 1112 – 1124.
dc.identifier.citedreferenceSchmidt S, Dunet V, Koehli M, Montemurro M, Meuli R, Prior JO. Diffusion‐weighted magnetic resonance imaging in metastatic gastrointestinal stromal tumor (GIST): a pilot study on the assessment of treatment response in comparison with 18 F‐FDG PET/CT. Acta Radiol. 2013; 54 ( 8 ): 837 – 842.
dc.identifier.citedreferenceGenovesi D, Filippone A, Ausili Cefaro G, Trignani M, Vinciguerra A, Augurio A, Di Tommaso M, Borzillo V, Sabatino F, Innocenti P, Liberatore E, Colecchia G, Tartaro A, Cotroneo AR. Diffusion‐weighted magnetic resonance for prediction of response after neoadjuvant chemoradiation therapy for locally advanced rectal cancer: preliminary results of a monoinstitutional prospective study. Eur. J. Surg. Oncol. 2013; 39 ( 10 ): 1071 – 1078.
dc.identifier.citedreferenceHein PA, Kremser C, Judmaier W, Griebel J, Pfeiffer KP, Kreczy A, Hug EB, Lukas P, DeVries AF. Diffusion‐weighted magnetic resonance imaging for monitoring diffusion changes in rectal carcinoma during combined, preoperative chemoradiation: preliminary results of a prospective study. Eur. J. Radiol. 2003; 45 ( 3 ): 214 – 222.
dc.identifier.citedreferenceIppolito D, Monguzzi L, Guerra L, Deponti E, Gardani G, Messa C, Sironi S. Response to neoadjuvant therapy in locally advanced rectal cancer: assessment with diffusion‐weighted MR imaging and 18 FDG PET/CT. Abdom. Imaging 2012; 37 ( 6 ): 1032 – 1040.
dc.identifier.citedreferenceKim SH, Lee JM, Hong SH, Kim GH, Lee JY, Han JK, Choi BI. Locally advanced rectal cancer: added value of diffusion‐weighted MR imaging in the evaluation of tumor response to neoadjuvant chemo‐ and radiation therapy. Radiology 2009; 253 ( 1 ): 116 – 125.
dc.identifier.citedreferenceKim SH, Ryu KH, Yoon JH, Lee Y, Paik JH, Kim SJ, Jung HK, Lee KH. Apparent diffusion coefficient for lymph node characterization after chemoradiation therapy for locally advanced rectal cancer. Acta Radiol. 2015; 56: 1446 – 1453.
dc.identifier.citedreferenceDe Paepe K, Bevernage C, De Keyzer F, Wolter P, Gheysens O, Janssens A, Oyen R, Verhoef G, Vandecaveye V. Whole‐body diffusion‐weighted magnetic resonance imaging at 3 Tesla for early assessment of treatment response in non‐Hodgkin lymphoma: a pilot study. Cancer Imaging 2013; 13: 53 – 62.
dc.identifier.citedreferenceHorger M, Claussen C, Kramer U, Fenchel M, Lichy M, Kaufmann S. Very early indicators of response to systemic therapy in lymphoma patients based on alterations in water diffusivity—a preliminary experience in 20 patients undergoing whole‐body diffusion‐weighted imaging. Eur. J. Radiol. 2014; 83 ( 9 ): 1655 – 1664.
dc.identifier.citedreferenceMontoro J, Laszlo D, Zing NP, Petralia G, Conte G, Colandrea M, Martinelli G, Preda L. Comparison of whole‐body diffusion‐weighted magnetic resonance and FDG‐PET/CT in the assessment of Hodgkin’s lymphoma for staging and treatment response. Ecancermedicalscience 2014; 8: 429.
dc.identifier.citedreferencePrat MC, Surapaneni K, Chalian H, DeLaPaz RL, Kazim M. Ocular adnexal lymphoma: monitoring response to therapy with diffusion‐weighted imaging. Ophth. Plast. Reconstruct. Surg. 2013; 29 ( 6 ): 424 – 427.
dc.identifier.citedreferenceSiegel MJ, Jokerst CE, Rajderkar D, Hildebolt CF, Goyal S, Dehdashti F, Wagner Johnston N, Siegel BA. Diffusion‐weighted MRI for staging and evaluation of response in diffuse large B‐cell lymphoma: a pilot study. NMR Biomed. 2014; 27 ( 6 ): 681 – 691.
dc.identifier.citedreferenceTsuji K, Kishi S, Tsuchida T, Yamauchi T, Ikegaya S, Urasaki Y, Fujiwara Y, Ueda T, Okazawa H, Kimura H. Evaluation of staging and early response to chemotherapy with whole‐body diffusion‐weighted MRI in malignant lymphoma patients: a comparison with FDG‐PET/CT. J. Magn. Reson. Imaging 2015; 41: 1601 – 1607.
dc.identifier.citedreferenceDing Y, Fuller C, Mohamed A, Wang J, Hazle J. TU‐F‐CAMPUS‐I‐01: head and neck squamous cell carcinoma: short‐term repeatability of apparent diffusion coefficient and intravoxel incoherent motion parameters at 3.0T. Med. Phys. 2015; 42 ( 6 ): 3646.
dc.identifier.citedreferenceGalban CJ, Mukherji SK, Chenevert TL, Meyer CR, Hamstra DA, Bland PH, Johnson TD, Moffat BA, Rehemtulla A, Eisbruch A, Ross BD. A feasibility study of parametric response map analysis of diffusion‐weighted magnetic resonance imaging scans of head and neck cancer patients for providing early detection of therapeutic efficacy. Transl. Oncol. 2009; 2 ( 3 ): 184 – 190.
dc.identifier.citedreferenceBlackledge MD, Collins DJ, Tunariu N, Orton MR, Padhani AR, Leach MO, Koh DM. Assessment of treatment response by total tumor volume and global apparent diffusion coefficient using diffusion‐weighted MRI in patients with metastatic bone disease: a feasibility study. PloS One 2014; 9 ( 4 ): e91779.
dc.identifier.citedreferenceByun WM, Shin SO, Chang Y, Lee SJ, Finsterbusch J, Frahm J. Diffusion‐weighted MR imaging of metastatic disease of the spine: assessment of response to therapy. Am. J. Neuroradiol. 2002; 23 ( 6 ): 906 – 912.
dc.identifier.citedreferenceCui Y, Zhang XP, Sun YS, Tang L, Shen L. Apparent diffusion coefficient: potential imaging biomarker for prediction and early detection of response to chemotherapy in hepatic metastases. Radiology 2008; 248 ( 3 ): 894 – 900.
dc.identifier.citedreferenceKukuk GM, Murtz P, Traber F, Meyer C, Ullrich J, Gieseke J, Ahmadzadehfar H, Ezziddin S, Schild HH, Willinek WA. Diffusion‐weighted imaging with acquisition of three b‐values for response evaluation of neuroendocrine liver metastases undergoing selective internal radiotherapy. Eur. Radiol. 2014; 24 ( 2 ): 267 – 276.
dc.identifier.citedreferenceMarugami N, Tanaka T, Kitano S, Hirohashi S, Nishiofuku H, Takahashi A, Sakaguchi H, Matsuoka M, Otsuji T, Takahama J, Higashiura W, Kichikawa K. Early detection of therapeutic response to hepatic arterial infusion chemotherapy of liver metastases from colorectal cancer using diffusion‐weighted MR imaging. Cardiovasc. Intervent. Radiol. 2009; 32 ( 4 ): 638 – 646.
dc.identifier.citedreferenceMungai F, Pasquinelli F, Mazzoni LN, Virgili G, Ragozzino A, Quaia E, Morana G, Giovagnoni A, Grazioli L, Colagrande S. Diffusion‐weighted magnetic resonance imaging in the prediction and assessment of chemotherapy outcome in liver metastases. Radiol. Med. 2014; 119 ( 8 ): 625 – 633.
dc.identifier.citedreferenceBastin ME, Delgado M, Whittle IR, Cannon J, Wardlaw JM. The use of diffusion tensor imaging in quantifying the effect of dexamethasone on brain tumours. Neuroreport 1999; 10 ( 7 ): 1385 – 1391.
dc.identifier.citedreferenceLi X, Abramson RG, Arlinghaus LR, Kang H, Chakravarthy AB, Abramson VG, Farley J, Mayer IA, Kelley MC, Meszoely IM, Means‐Powell J, Grau AM, Sanders M, Yankeelov TE. Multiparametric magnetic resonance imaging for predicting pathological response after the first cycle of neoadjuvant chemotherapy in breast cancer. Invest. Radiol. 2015; 50: 195 – 204.
dc.identifier.citedreferenceUhl M, Saueressig U, van Buiren M, Kontny U, Niemeyer C, Kohler G, Ilyasov K, Langer M. Osteosarcoma: preliminary results of in vivo assessment of tumor necrosis after chemotherapy with diffusion‐ and perfusion‐weighted magnetic resonance imaging. Invest. Radiol. 2006; 41 ( 8 ): 618 – 623.
dc.identifier.citedreferenceHein PA, Eskey CJ, Dunn JF, Hug EB. Diffusion‐weighted imaging in the follow‐up of treated high‐grade gliomas: tumor recurrence versus radiation injury. Am. J. Neuroradiol. 2004; 25 ( 2 ): 201 – 209.
dc.identifier.citedreferenceReischauer C, Froehlich JM, Koh DM, Graf N, Padevit C, John H, Binkert CA, Boesiger P, Gutzeit A. Bone metastases from prostate cancer: assessing treatment response by using diffusion‐weighted imaging and functional diffusion maps—initial observations. Radiology 2010; 257 ( 2 ): 523 – 531.
dc.identifier.citedreferenceTakahara T, Imai Y, Yamashita T, Yasuda S, Nasu S, Van Cauteren M. Diffusion weighted whole body imaging with background body signal suppression (DWIBS): technical improvement using free breathing, STIR and high resolution 3D display. Radiat. Med. 2004; 22 ( 4 ): 275 – 282.
dc.identifier.citedreferenceKwee TC, Takahara T, Ochiai R, Nievelstein RA, Luijten PR. Diffusion‐weighted whole‐body imaging with background body signal suppression (DWIBS): features and potential applications in oncology. Eur. Radiol. 2008; 18 ( 9 ): 1937 – 1952.
dc.identifier.citedreferenceDzik‐Jurasz A, Domenig C, George M, Wolber J, Padhani A, Brown G, Doran S. Diffusion MRI for prediction of response of rectal cancer to chemoradiation. Lancet 2002; 360 ( 9329 ): 307 – 308.
dc.identifier.citedreferenceKremser C, Judmaier W, Hein P, Griebel J, Lukas P, de Vries A. Preliminary results on the influence of chemoradiation on apparent diffusion coefficients of primary rectal carcinoma measured by magnetic resonance imaging. Strahlenther. Onkol. 2003; 179 ( 9 ): 641 – 649.
dc.identifier.citedreferenceJacobs MA, Herskovits EH, Kim HS. Uterine fibroids: diffusion‐weighted MR imaging for monitoring therapy with focused ultrasound surgery—preliminary study. Radiology 2005; 236 ( 1 ): 196 – 203.
dc.identifier.citedreferenceAliu SO, Wilmes LJ, Moasser MM, Hann BC, Li KL, Wang D, Hylton NM. MRI methods for evaluating the effects of tyrosine kinase inhibitor administration used to enhance chemotherapy efficiency in a breast tumor xenograft model. J. Magn. Reson. Imaging 2009; 29 ( 5 ): 1071 – 1079.
dc.identifier.citedreferenceJust N. Improving tumour heterogeneity MRI assessment with histograms. Br. J. Cancer 2014; 111 ( 12 ): 2205 – 2213.
dc.identifier.citedreferenceWoo S, Cho JY, Kim SY, Kim SH. Histogram analysis of apparent diffusion coefficient map of diffusion‐weighted MRI in endometrial cancer: a preliminary correlation study with histological grade. Acta Radiol. 2014; 55 ( 10 ): 1270 – 1277.
dc.identifier.citedreferenceBoes JL, Hoff BA, Hylton N, Pickles MD, Turnbull LW, Schott AF, Rehemtulla A, Chamberlain R, Lemasson B, Chenevert TL, Galb NC, Meyer CR, Ross BD. Image registration for quantitative parametric response mapping of cancer treatment response. Transl. Oncol. 2014; 7 ( 1 ): 101 – 110.
dc.identifier.citedreferenceLemasson B, Chenevert TL, Lawrence TS, Tsien C, Sundgren PC, Meyer CR, Junck L, Boes J, Galban S, Johnson TD, Rehemtulla A, Ross BD, Galban CJ. Impact of perfusion map analysis on early survival prediction accuracy in glioma patients. Transl. Oncol. 2013; 6 ( 6 ): 766 – 774.
dc.identifier.citedreferenceMoffat BA, Chenevert TL, Lawrence TS, Meyer CR, Johnson TD, Dong Q, Tsien C, Mukherji S, Quint DJ, Gebarski SS, Robertson PL, Junck LR, Rehemtulla A, Ross BD. Functional diffusion map: a noninvasive MRI biomarker for early stratification of clinical brain tumor response. Proc. Natl. Acad. Sci. USA 2005; 102 ( 15 ): 5524 – 5529.
dc.identifier.citedreferenceLi X, Dawant BM, Welch EB, Chakravarthy AB, Freehardt D, Mayer I, Kelley M, Meszoely I, Gore JC, Yankeelov TE. A nonrigid registration algorithm for longitudinal breast MR images and the analysis of breast tumor response. Magn. Reson. Imaging 2009; 27 ( 9 ): 1258 – 1270.
dc.identifier.citedreferenceLi X, Dawant BM, Welch EB, Chakravarthy AB, Xu L, Mayer I, Kelley M, Meszoely I, Means‐Powell J, Gore JC, Yankeelov TE. Validation of an algorithm for the nonrigid registration of longitudinal breast MR images using realistic phantoms. Med. Phys. 2010; 37 ( 6 ): 2541 – 1552.
dc.identifier.citedreferenceEllingson BM, Cloughesy TF, Lai A, Nghiemphu PL, Liau LM, Pope WB. Quantitative probabilistic functional diffusion mapping in newly diagnosed glioblastoma treated with radiochemotherapy. Neuro‐oncology 2013; 15 ( 3 ): 382 – 390.
dc.identifier.citedreferenceEllingson BM, Cloughesy TF, Zaw T, Lai A, Nghiemphu PL, Harris R, Lalezari S, Wagle N, Naeini KM, Carrillo J, Liau LM, Pope WB. Functional diffusion maps (fDMs) evaluated before and after radiochemotherapy predict progression‐free and overall survival in newly diagnosed glioblastoma. Neuro‐oncology 2012; 14 ( 3 ): 333 – 343.
dc.identifier.citedreferenceHamstra DA, Chenevert TL, Moffat BA, Johnson TD, Meyer CR, Mukherji SK, Quint DJ, Gebarski SS, Fan X, Tsien CI, Lawrence TS, Junck L, Rehemtulla A, Ross BD. Evaluation of the functional diffusion map as an early biomarker of time‐to‐progression and overall survival in high‐grade glioma. Proc. Natl. Acad. Sci. USA 2005; 102 ( 46 ): 16 759 – 764.
dc.identifier.citedreferenceHamstra DA, Galban CJ, Meyer CR, Johnson TD, Sundgren PC, Tsien C, Lawrence TS, Junck L, Ross DJ, Rehemtulla A, Ross BD, Chenevert TL. Functional diffusion map as an early imaging biomarker for high‐grade glioma: correlation with conventional radiologic response and overall survival. J. Clin. Oncol. 2008; 26 ( 20 ): 3387 – 3394.
dc.identifier.citedreferencePadhani AR, Liu G, Mu‐Koh D, Chenevert TL, Thoeny HC, Takahara T, Dzik‐Jurasz A, Ross BD, Van Cauteren M, Collins D, Hammoud DA, Rustin GJ, Taouli B, Choyke PL. Diffusion‐weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 2009; 11 ( 2 ): 102 – 125.
dc.identifier.citedreferenceDelakis I, Moore EM, Leach MO, De Wilde JP. Developing a quality control protocol for diffusion imaging on a clinical MRI system. Phys. Med. Biol. 2004; 49 ( 8 ): 1409 – 1422.
dc.identifier.citedreferenceLaubach HJ, Jakob PM, Loevblad KO, Baird AE, Bovo MP, Edelman RR, Warach S. A phantom for diffusion‐weighted imaging of acute stroke. J. Magn. Reson. Imaging 1998; 8 ( 6 ): 1349 – 1354.
dc.identifier.citedreferenceTofts PS, Lloyd D, Clark CA, Barker GJ, Parker GJ, McConville P, Baldock C, Pope JM. Test liquids for quantitative MRI measurements of self‐diffusion coefficient in vivo. Magn. Reson. Med. 2000; 43 ( 3 ): 368 – 374.
dc.identifier.citedreferenceChenevert TL, Galban CJ, Ivancevic MK, Rohrer SE, Londy FJ, Kwee TC, Meyer CR, Johnson TD, Rehemtulla A, Ross BD. Diffusion coefficient measurement using a temperature‐controlled fluid for quality control in multicenter studies. J. Magn. Reson. Imaging 2011; 34 ( 4 ): 983 – 987.
dc.identifier.citedreferenceSimpson JH, Carr HY. Diffusion and nuclear spin relaxation in water. Phys. Rev. 1958; 111: 1201 – 1202.
dc.identifier.citedreferenceBelli G, Busoni S, Ciccarone A, Coniglio A, Esposito M, Giannelli M, Mazzoni LN, Nocetti L, Sghedoni R, Tarducci R, Zatelli G, Anoja RA, Belmonte G, Bertolino N, Betti M, Biagini C, Ciarmatori A, Cretti F, Fabbri E, Fedeli L, Filice S, Fulcheri CP, Gasperi C, Mangili PA, Mazzocchi S, Meliado G, Morzenti S, Noferini L, Oberhofer N, Orsingher L, Paruccini N, Princigalli G, Quattrocchi M, Rinaldi A, Scelfo D, Freixas GV, Tenori L, Zucca I, Luchinat C, Gori C, Gobbi G, Italian Association of Physics in Medicine Working Group on MRI. Quality assurance multicenter comparison of different MR scanners for quantitative diffusion‐weighted imaging. J. Magn. Reson. Imaging 2015. doi: 10.1002/jmri.24956. [Epub ahead of print]
dc.identifier.citedreferenceMalyarenko D, Galban CJ, Londy FJ, Meyer CR, Johnson TD, Rehemtulla A, Ross BD, Chenevert TL. Multi‐system repeatability and reproducibility of apparent diffusion coefficient measurement using an ice–water phantom. J. Magn. Reson. Imaging 2013; 37 ( 5 ): 1238 – 1246.
dc.identifier.citedreferenceKakite S, Dyvorne H, Besa C, Cooper N, Facciuto M, Donnerhack C, Taouli B. Hepatocellular carcinoma: short‐term reproducibility of apparent diffusion coefficient and intravoxel incoherent motion parameters at 3.0T. J. Magn. Reson. Imaging, 2015; 41 ( 1 ): 149 – 156.
dc.identifier.citedreferenceBernardin L, Douglas NH, Collins DJ, Giles SL, O’Flynn EA, Orton M, deSouza NM. Diffusion‐weighted magnetic resonance imaging for assessment of lung lesions: repeatability of the apparent diffusion coefficient measurement. Eur. Radiol. 2014; 24 ( 2 ): 502 – 511.
dc.identifier.citedreferenceIntven M, Reerink O, Philippens ME. Repeatability of diffusion‐weighted imaging in rectal cancer. J. Magn. Reson. Imaging 2014; 40 ( 1 ): 146 – 150.
dc.identifier.citedreferenceGalban CJ, Ma B, Malyarenko D, Pickles MD, Heist K, Henry NL, Schott AF, Neal CH, Hylton NM, Rehemtulla A, Johnson TD, Meyer CR, Chenevert TL, Turnbull LW, Ross BD. Multi‐site clinical evaluation of DW‐MRI as a treatment response metric for breast cancer patients undergoing neoadjuvant chemotherapy. PloS One 2015; 10 ( 3 ): e0122151.
dc.identifier.citedreferenceHeo S, Cho HJ, Jeon IS. A case of posterior reversible encephalopathy syndrome in a child with myelodysplastic syndrome following allogenic bone marrow transplantation. Pediatr. Hematol. Oncol. 2010; 27 ( 1 ): 59 – 64.
dc.identifier.citedreferenceHuang RY, Neagu MR, Reardon DA, Wen PY. Pitfalls in the neuroimaging of glioblastoma in the era of antiangiogenic and immuno/targeted therapy – detecting illusive disease, defining response. Frontiers Neurol. 2015; 6: 33.
dc.identifier.citedreferenceRygh CB, Wang J, Thuen M, Gras Navarro A, Huuse EM, Thorsen F, Poli A, Zimmer J, Haraldseth O, Lie SA, Enger PO, Chekenya M. Dynamic contrast enhanced MRI detects early response to adoptive NK cellular immunotherapy targeting the NG2 proteoglycan in a rat model of glioblastoma. PloS One 2014; 9 ( 9 ): e108414.
dc.identifier.citedreferenceMcDonald K, Sebire NJ, Anderson J, Olsen OE. Patterns of shift in ADC distributions in abdominal tumours during chemotherapy‐feasibility study. Pediatr. Radiol. 2011; 41 ( 1 ): 99 – 106.
dc.identifier.citedreferenceWai Y, Chu J, Wang C, Lin Y, Lin G, Wan Y, Wang J. An integrated diffusion map for the analysis of diffusion properties: a feasibility study in patients with acoustic neuroma. Acad. Radiol. 2009; 16 ( 4 ): 428 – 434.
dc.identifier.citedreferenceNakayama T, Yoshida S, Fujii Y, Koga F, Saito K, Masuda H, Kobayashi T, Kawakami S, Kihara K. Use of diffusion‐weighted MRI in monitoring response of lymph node metastatic bladder cancer treated with chemotherary. Nihon Hinyokika Gakkai zasshi [Jpn. J. Urol.] 2008; 99 ( 7 ): 737 – 741.
dc.identifier.citedreferenceYoshida S, Koga F, Kawakami S, Ishii C, Tanaka H, Numao N, Sakai Y, Saito K, Masuda H, Fujii Y, Kihara K. Initial experience of diffusion‐weighted magnetic resonance imaging to assess therapeutic response to induction chemoradiotherapy against muscle‐invasive bladder cancer. Urology 2010; 75 ( 2 ): 387 – 391.
dc.identifier.citedreferenceBallon D, Watts R, Dyke JP, Lis E, Morris MJ, Scher HI, Ulug AM, Jakubowski AA. Imaging therapeutic response in human bone marrow using rapid whole‐body MRI. Magn. Reson. Med. 2004; 52 ( 6 ): 1234 – 1238.
dc.identifier.citedreferenceArmitage PA, Schwindack C, Bastin ME, Whittle IR. Quantitative assessment of intracranial tumor response to dexamethasone using diffusion, perfusion and permeability magnetic resonance imaging. Magn. Reson. Imaging 2007; 25 ( 3 ): 303 – 310.
dc.identifier.citedreferenceMardor Y, Roth Y, Lidar Z, Jonas T, Pfeffer R, Maier SE, Faibel M, Nass D, Hadani M, Orenstein A, Cohen JS, Ram Z. Monitoring response to convection‐enhanced taxol delivery in brain tumor patients using diffusion‐weighted magnetic resonance imaging. Cancer Res. 2001; 61 ( 13 ): 4971 – 4973.
dc.identifier.citedreferenceMardor Y, Roth Y, Ochershvilli A, Spiegelmann R, Tichler T, Daniels D, Maier SE, Nissim O, Ram Z, Baram J, Orenstein A, Pfeffer R. Pretreatment prediction of brain tumors’ response to radiation therapy using high b‐value diffusion‐weighted MRI. Neoplasia 2004; 6 ( 2 ): 136 – 142.
dc.identifier.citedreferenceMardor Y, Pfeffer R, Spiegelmann R, Roth Y, Maier SE, Nissim O, Berger R, Glicksman A, Baram J, Orenstein A, Cohen JS, Tichler T. Early detection of response to radiation therapy in patients with brain malignancies using conventional and high b‐value diffusion‐weighted magnetic resonance imaging. J. Clin. Oncol. 2003; 21 ( 6 ): 1094 – 1100.
dc.identifier.citedreferenceTomura N, Narita K, Izumi J, Suzuki A, Anbai A, Otani T, Sakuma I, Takahashi S, Mizoi K, Watarai J. Diffusion changes in a tumor and peritumoral tissue after stereotactic irradiation for brain tumors: possible prediction of treatment response. J. Comput. Assist. Tomogr. 2006; 30 ( 3 ): 496 – 500.
dc.identifier.citedreferenceGoldman M, Boxerman JL, Rogg JM, Noren G. Utility of apparent diffusion coefficient in predicting the outcome of gamma knife‐treated brain metastases prior to changes in tumor volume: a preliminary study. J. Neurosurg 2006; 105 ( Suppl ): 175 – 182.
dc.identifier.citedreferenceGupta A, Young RJ, Karimi S, Sood S, Zhang Z, Mo Q, Gutin PH, Holodny AI, Lassman AB. Isolated diffusion restriction precedes the development of enhancing tumor in a subset of patients with glioblastoma. Am. J. Neuroradiol. 2011; 32 ( 7 ): 1301 – 1306.
dc.identifier.citedreferenceHattingen E, Jurcoane A, Bahr O, Rieger J, Magerkurth J, Anti S, Steinbach JP, Pilatus U. Bevacizumab impairs oxidative energy metabolism and shows antitumoral effects in recurrent glioblastomas: a 31 P/ 1 H MRSI and quantitative magnetic resonance imaging study. Neuro‐oncology 2011; 13 ( 12 ): 1349 – 1363.
dc.identifier.citedreferencePope WB, Lai A, Mehta R, Kim HJ, Qiao J, Young JR, Xue X, Goldin J, Brown MS, Nghiemphu PL, Tran A, Cloughesy TF. Apparent diffusion coefficient histogram analysis stratifies progression‐free survival in newly diagnosed bevacizumab‐treated glioblastoma. Am. J. Neuroradiol. 2011; 32 ( 5 ): 882 – 889.
dc.identifier.citedreferenceVrabec M, Van Cauter S, Himmelreich U, Van Gool SW, Sunaert S, De Vleeschouwer S, Suput D, Demaerel P. MR perfusion and diffusion imaging in the follow‐up of recurrent glioblastoma treated with dendritic cell immunotherapy: a pilot study. Neuroradiology 2011; 53 ( 10 ): 721 – 731.
dc.identifier.citedreferenceYamasaki F, Kurisu K, Aoki T, Yamanaka M, Kajiwara Y, Watanabe Y, Takayasu T, Akiyama Y, Sugiyama K. Advantages of high b‐value diffusion‐weighted imaging to diagnose pseudo‐responses in patients with recurrent glioma after bevacizumab treatment. Eur. J. Radiol. 2012; 81 ( 10 ): 2805 – 2810.
dc.identifier.citedreferenceGalban CJ, Chenevert TL, Meyer CR, Tsien C, Lawrence TS, Hamstra DA, Junck L, Sundgren PC, Johnson TD, Galban S, Sebolt‐Leopold JS, Rehemtulla A, Ross BD. Prospective analysis of parametric response map‐derived MRI biomarkers: identification of early and distinct glioma response patterns not predicted by standard radiographic assessment. Clin. Cancer Res. 2011; 17 ( 14 ): 4751 – 4760.
dc.identifier.citedreferenceNowosielski M, Recheis W, Goebel G, Guler O, Tinkhauser G, Kostron H, Schocke M, Gotwald T, Stockhammer G, Hutterer M. ADC histograms predict response to anti‐angiogenic therapy in patients with recurrent high‐grade glioma. Neuroradiology 2011; 53 ( 4 ): 291 – 302.
dc.identifier.citedreferencePrabhu SP, Ng S, Vajapeyam S, Kieran MW, Pollack IF, Geyer R, Haas‐Kogan D, Boyett JM, Kun L, Poussaint TY. DTI assessment of the brainstem white matter tracts in pediatric BSG before and after therapy: a report from the Pediatric Brain Tumor Consortium. Child Nerv. Syst. 2011; 27 ( 1 ): 11 – 18.
dc.identifier.citedreferenceRingelstein A, Turowski B, Gizewski ER, Schroeteler J, Rapp M, Saleh A, Lanzman RS, Mathys C, Sabel M, Modder U. [Evaluation of ADC mapping as an early predictor for tumor response to chemotherapy in recurrent glioma treated with bevacizumab/irinotecan: proof of principle]. RoFo: Fortschr. Gebiete Rontgenstrahlen Nuklearmedizin 2010; 182 ( 10 ): 868 – 872.
dc.identifier.citedreferenceChen HJ, Panigrahy A, Dhall G, Finlay JL, Nelson MD Jr., Bluml S. Apparent diffusion and fractional anisotropy of diffuse intrinsic brain stem gliomas. Am. J. Neuroradiol. 2010; 31 ( 10 ): 1879 – 1885.
dc.identifier.citedreferenceJain R, Scarpace LM, Ellika S, Torcuator R, Schultz LR, Hearshen D, Mikkelsen T. Imaging response criteria for recurrent gliomas treated with bevacizumab: role of diffusion weighted imaging as an imaging biomarker. J. Neuro‐oncol. 2010; 96 ( 3 ): 423 – 431.
dc.identifier.citedreferenceSeshadri M, Ciesielski MJ. MRI‐based characterization of vascular disruption by 5,6‐dimethylxanthenone‐acetic acid in gliomas. J. Cerebr. Blood Flow Metab. 2009; 29 ( 8 ): 1373 – 1382.
dc.identifier.citedreferenceJager HR, Waldman AD, Benton C, Fox N, Rees J. Differential chemosensitivity of tumor components in a malignant oligodendroglioma: assessment with diffusion‐weighted, perfusion‐weighted, and serial volumetric MR imaging. Am. J. Neuroradiol. 2005; 26 ( 2 ): 274 – 278.
dc.identifier.citedreferenceLidar Z, Mardor Y, Jonas T, Pfeffer R, Faibel M, Nass D, Hadani M, Ram Z. Convection‐enhanced delivery of paclitaxel for the treatment of recurrent malignant glioma: a phase I/II clinical study. J. Neurosurg. 2004; 100 ( 3 ): 472 – 479.
dc.identifier.citedreferenceLin YC, Wang CC, Wai YY, Wan YL, Ng SH, Chen YL, Liu HL, Wang JJ. Significant temporal evolution of diffusion anisotropy for evaluating early response to radiosurgery in patients with vestibular schwannoma: findings from functional diffusion maps. Am. J. Neuroradiol. 2010; 31 ( 2 ): 269 – 274.
dc.identifier.citedreferenceSchubert MI, Wilke M, Muller‐Weihrich S, Auer DP. Diffusion‐weighted magnetic resonance imaging of treatment‐associated changes in recurrent and residual medulloblastoma: preliminary observations in three children. Acta Radiol. 2006; 47 ( 10 ): 1100 – 1104.
dc.identifier.citedreferenceSinha S, Bastin ME, Whittle IR. Rapid clinical deterioration in a patient with multi‐focal glioma despite corticosteroid therapy: a quantitative MRI study. Br. J. Neurosurg. 2003; 17 ( 6 ): 537 – 540 discussion 540.
dc.identifier.citedreferenceArlinghaus LR, Li X, Rahman AR, Welch EB, Xu L, Gore JC, Yankeelov TE. On the relationship between the apparent diffusion coefficient and extravascular extracellular volume fraction in human breast cancer. Magn. Reson. Imaging 2011; 29 ( 5 ): 630 – 638.
dc.identifier.citedreferenceBelli P, Costantini M, Ierardi C, Bufi E, Amato D, Mule A, Nardone L, Terribile D, Bonomo L. Diffusion‐weighted imaging in evaluating the response to neoadjuvant breast cancer treatment. Breast J. 2011; 17 ( 6 ): 610 – 619.
dc.identifier.citedreferenceFangberget A, Nilsen LB, Hole KH, Holmen MM, Engebraaten O, Naume B, Smith HJ, Olsen DR, Seierstad T. Neoadjuvant chemotherapy in breast cancer‐response evaluation and prediction of response to treatment using dynamic contrast‐enhanced and diffusion‐weighted MR imaging. Eur. Radiol. 2011; 21 ( 6 ): 1188 – 1199.
dc.identifier.citedreferenceJensen LR, Garzon B, Heldahl MG, Bathen TF, Lundgren S, Gribbestad IS. Diffusion‐weighted and dynamic contrast‐enhanced MRI in evaluation of early treatment effects during neoadjuvant chemotherapy in breast cancer patients. J. Magn. Reson. Imaging 2011; 34 ( 5 ): 1099 – 1109.
dc.identifier.citedreferenceJinming X, Qi Z, Xiaoming Z, Jianming T. Primary non‐Hodgkin’s lymphoma of the breast: mammography, ultrasound, MRI and pathologic findings. Future Oncol. 2012; 8 ( 1 ): 105 – 109.
dc.identifier.citedreferenceKawamura M, Satake H, Ishigaki S, Nishio A, Sawaki M, Naganawa S. Early prediction of response to neoadjuvant chemotherapy for locally advanced breast cancer using MRI. Nagoya J. Med. Sci. 2011; 73 ( 3–4 ): 147 – 156.
dc.identifier.citedreferenceLi XR, Cheng LQ, Liu M, Zhang YJ, Wang JD, Zhang AL, Song X, Li J, Zheng YQ, Liu L. DW‐MRI ADC values can predict treatment response in patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy. Med. Oncol. 2012; 29 ( 2 ): 425 – 431.
dc.identifier.citedreferencePark SH, Moon WK, Cho N, Chang JM, Im SA, Park IA, Kang KW, Han W, Noh DY. Comparison of diffusion‐weighted MR imaging and FDG PET/CT to predict pathological complete response to neoadjuvant chemotherapy in patients with breast cancer. Eur. Radiol. 2012; 22 ( 1 ): 18 – 25.
dc.identifier.citedreferenceWang XH, Peng WJ, Tan HN, Xin C, Gu YJ, Tang F, Mao J. Value of diffusion weighted imaging (DWI) in evaluating early response to neoadjuvant chemotherapy in locally advanced breast cancer. Zhonghua zhong liu za zhi [Chin. J. Oncol.] 2010; 32 ( 5 ): 377 – 381.
dc.identifier.citedreferenceBuijs M, Kamel IR, Vossen JA, Georgiades CS, Hong K, Geschwind JF. Assessment of metastatic breast cancer response to chemoembolization with contrast agent enhanced and diffusion‐weighted MR imaging. J. Vasc. Intervent. Radiol. 2007; 18 ( 8 ): 957 – 963.
dc.identifier.citedreferenceMa B, Meyer CR, Pickles MD, Chenevert TL, Bland PH, Galban CJ, Rehemtulla A, Turnbull LW, Ross BD. Voxel‐by‐voxel functional diffusion mapping for early evaluation of breast cancer treatment. Proc. Conf. Inform. Process. Med. Imaging 2009; 21: 276 – 287.
dc.identifier.citedreferenceNilsen L, Fangberget A, Geier O, Olsen DR, Seierstad T. Diffusion‐weighted magnetic resonance imaging for pretreatment prediction and monitoring of treatment response of patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy. Acta Oncol. 2010; 49 ( 3 ): 354 – 360.
dc.identifier.citedreferenceTozaki M, Oyama Y, Fukuma E. Preliminary study of early response to neoadjuvant chemotherapy after the first cycle in breast cancer: comparison of 1 H magnetic resonance spectroscopy with diffusion magnetic resonance imaging. Jpn. J. Radiol. 2010; 28 ( 2 ): 101 – 109.
dc.identifier.citedreferenceManton DJ, Chaturvedi A, Hubbard A, Lind MJ, Lowry M, Maraveyas A, Pickles MD, Tozer DJ, Turnbull LW. Neoadjuvant chemotherapy in breast cancer: early response prediction with quantitative MR imaging and spectroscopy. Br. J. Cancer 2006; 94 ( 3 ): 427 – 435.
dc.identifier.citedreferenceHarry VN, Semple SI, Gilbert FJ, Parkin DE. Diffusion‐weighted magnetic resonance imaging in the early detection of response to chemoradiation in cervical cancer. Gynecol. Oncol. 2008; 111 ( 2 ): 213 – 220.
dc.identifier.citedreferenceLevy A, Caramella C, Chargari C, Medjhoul A, Rey A, Zareski E, Boulet B, Bidault F, Dromain C, Balleyguier C. Accuracy of diffusion‐weighted echo‐planar MR imaging and ADC mapping in the evaluation of residual cervical carcinoma after radiation therapy. Gynecol. Oncol. 2011; 123 ( 1 ): 110 – 115.
dc.identifier.citedreferenceLiu Y, Bai R, Sun H, Liu H, Zhao X, Li Y. Diffusion‐weighted imaging in predicting and monitoring the response of uterine cervical cancer to combined chemoradiation. Clin. Radiol. 2009; 64 ( 11 ): 1067 – 1074.
dc.identifier.citedreferenceMatge G. Anterior interbody fusion with the BAK‐cage in cervical spondylosis. Acta Neurochirurg. 1998; 140 ( 1 ): 1 – 8.
dc.identifier.citedreferenceMcVeigh PZ, Syed AM, Milosevic M, Fyles A, Haider MA. Diffusion‐weighted MRI in cervical cancer. Eur. Radiol. 2008; 18 ( 5 ): 1058 – 1064.
dc.identifier.citedreferenceRizzo S, Summers P, Raimondi S, Belmonte M, Maniglio M, Landoni F, Colombo N, Bellomi M. Diffusion‐weighted MR imaging in assessing cervical tumour response to nonsurgical therapy. Radiol. Med. 2011; 116 ( 5 ): 766 – 780.
dc.identifier.citedreferenceZhang Y, Chen JY, Xie CM, Mo YX, Liu XW, Liu Y, Wu PH. Diffusion‐weighted magnetic resonance imaging for prediction of response of advanced cervical cancer to chemoradiation. J. Comput. Assist. Tomogr. 2011; 35 ( 1 ): 102 – 107.
dc.identifier.citedreferenceZhang Y, Liang BL, Gao L, Ye RX, Shen J, Zhong JL. [Diffusion weighted imaging features of normal uterine cervix and cervical carcinoma]. Ai zheng = Aizheng [Chin. J. Cancer] 2007; 26 ( 5 ): 508 – 512.
dc.identifier.citedreferenceBuijs M, Vossen JA, Hong K, Georgiades CS, Geschwind JF, Kamel IR. Chemoembolization of hepatic metastases from ocular melanoma: assessment of response with contrast‐enhanced and diffusion‐weighted MRI. Am. J. Roentgenol. 2008; 191 ( 1 ): 285 – 289.
dc.identifier.citedreferencePoliti LS, Forghani R, Godi C, Resti AG, Ponzoni M, Bianchi S, Iadanza A, Ambrosi A, Falini A, Ferreri AJ, Curtin HD, Scotti G. Ocular adnexal lymphoma: diffusion‐weighted MR imaging for differential diagnosis and therapeutic monitoring. Radiology 2010; 256 ( 2 ): 565 – 574.
dc.identifier.citedreferenceHecht EM, Do RK, Kang SK, Bennett GL, Babb JS, Clark TW. Diffusion‐weighted imaging for prediction of volumetric response of leiomyomas following uterine artery embolization: a preliminary study. J. Magn. Reson. Imaging 2011; 33 ( 3 ): 641 – 646.
dc.identifier.citedreferenceSaraiya B, Chugh R, Karantza V, Mehnert J, Moss RA, Savkina N, Stein MN, Baker LH, Chenevert T, Poplin EA. Phase I study of gemcitabine, docetaxel and imatinib in refractory and relapsed solid tumors. Invest. New Drugs 2012; 30 ( 1 ): 258 – 265.
dc.identifier.citedreferenceVossen JA, Kamel IR, Buijs M, Liapi E, Georgiades CS, Hong K, Geschwind JF. Role of functional magnetic resonance imaging in assessing metastatic leiomyosarcoma response to chemoembolization. J. Comput. Assist. Tomogr. 2008; 32 ( 3 ): 347 – 352.
dc.identifier.citedreferenceHuang CF, Chiou SY, Wu MF, Tu HT, Liu WS, Chuang JC. Apparent diffusion coefficients for evaluation of the response of brain tumors treated by gamma knife surgery. J. Neurosurg. 2010; 113 ( Suppl ): 97 – 104.
dc.identifier.citedreferenceDudeck O, Zeile M, Wybranski C, Schulmeister A, Fischbach F, Pech M, Wieners G, Ruhl R, Grosser O, Amthauer H, Ricke J. Early prediction of anticancer effects with diffusion‐weighted MR imaging in patients with colorectal liver metastases following selective internal radiotherapy. Eur. Radiol. 2010; 20 ( 11 ): 2699 – 2706.
dc.identifier.citedreferenceKoh DM, Scurr E, Collins D, Kanber B, Norman A, Leach MO, Husband JE. Predicting response of colorectal hepatic metastasis: value of pretreatment apparent diffusion coefficients. Am. J. Roentgenol. 2007; 188 ( 4 ): 1001 – 1008.
dc.identifier.citedreferenceWybranski C, Zeile M, Lowenthal D, Fischbach F, Pech M, Rohl FW, Gademann G, Ricke J, Dudeck O. Value of diffusion weighted MR imaging as an early surrogate parameter for evaluation of tumor response to high‐dose‐rate brachytherapy of colorectal liver metastases. Radiat. Oncol. 2011; 6 ( 1 ): 43.
dc.identifier.citedreferenceZhang Y, Zhao J, Guo D, Zhong W, Ran L. Evaluation of short‐term response of high intensity focused ultrasound ablation for primary hepatic carcinoma: utility of contrast‐enhanced MRI and diffusion‐weighted imaging. Eur. J. Radiol. 2011; 79 ( 3 ): 347 – 352.
dc.identifier.citedreferenceDuke E, Deng J, Ibrahim SM, Lewandowski RJ, Ryu RK, Sato KT, Miller FH, Kulik L, Mulcahy MF, Larson AC, Salem R, Omary RA. Agreement between competing imaging measures of response of hepatocellular carcinoma to yttrium‐90 radioembolization. J. Vasc. Intervent. Radiol. 2010; 21 ( 4 ): 515 – 521.
dc.identifier.citedreferenceKubota K, Yamanishi T, Itoh S, Murata Y, Miyatake K, Yasunami H, Morio K, Hamada N, Nishioka A, Ogawa Y. Role of diffusion‐weighted imaging in evaluating therapeutic efficacy after transcatheter arterial chemoembolization for hepatocellular carcinoma. Oncol. Rep. 2010; 24 ( 3 ): 727 – 732.
dc.identifier.citedreferenceLiapi E, Geschwind JF, Vossen JA, Buijs M, Georgiades CS, Bluemke DA, Kamel IR. Functional MRI evaluation of tumor response in patients with neuroendocrine hepatic metastasis treated with transcatheter arterial chemoembolization. Am. J. Roentgenol. 2008; 190 ( 1 ): 67 – 73.
dc.identifier.citedreferenceEccles CL, Haider EA, Haider MA, Fung S, Lockwood G, Dawson LA. Change in diffusion weighted MRI during liver cancer radiotherapy: preliminary observations. Acta Oncol. 2009; 48 ( 7 ): 1034 – 1043.
dc.identifier.citedreferenceSchraml C, Schwenzer NF, Martirosian P, Bitzer M, Lauer U, Claussen CD, Horger M. Diffusion‐weighted MRI of advanced hepatocellular carcinoma during sorafenib treatment: initial results. Am. J. Roentgenol. 2009; 193 ( 4 ): W301 – W307.
dc.identifier.citedreferenceYuan Z, Ye XD, Dong S, Xu LC, Xu XY, Liu SY, Xiao XS. Role of magnetic resonance diffusion‐weighted imaging in evaluating response after chemoembolization of hepatocellular carcinoma. Eur. J. Radiol. 2010; 75 ( 1 ): e9 – e14.
dc.identifier.citedreferenceAnzidei M, Napoli A, Zaccagna F, Cartocci G, Saba L, Menichini G, Cavallo Marincola B, Marotta E, Di Mare L, Catalano C, Passariello R. Liver metastases from colorectal cancer treated with conventional and antiangiogenetic chemotherapy: evaluation with liver computed tomography perfusion and magnetic resonance diffusion‐weighted imaging. J. Comput. Assist. Tomogr. 2011; 35 ( 6 ): 690 – 696.
dc.identifier.citedreferenceBonekamp S, Shen J, Salibi N, Lai HC, Geschwind J, Kamel IR. Early response of hepatic malignancies to locoregional therapy – value of diffusion‐weighted magnetic resonance imaging and proton magnetic resonance spectroscopy. J. Comput. Assist. Tomogr. 2011; 35 ( 2 ): 167 – 173.
dc.identifier.citedreferenceYuan Z, Ye XD, Dong S, Xu LC, Sun ZC, Xiao XS. [Water mobility of diffusion MRI in prediction of response to chemoembolization in liver cancer]. Zhonghua zhong liu za zhi [Chin. J. Oncol.] 2009; 31 ( 4 ): 293 – 297.
dc.identifier.citedreferenceChung JC, Naik NK, Lewandowski RJ, Deng J, Mulcahy MF, Kulik LM, Sato KT, Ryu RK, Salem R, Larson AC, Omary RA. Diffusion‐weighted magnetic resonance imaging to predict response of hepatocellular carcinoma to chemoembolization. World J. Gastroenterol. 2010; 16 ( 25 ): 3161 – 3167.
dc.identifier.citedreferenceEl‐Khouli RH, Geschwind JF, Bluemke DA, Kamel IR. Solitary fibrous tumor of the liver: magnetic resonance imaging evaluation and treatment with transarterial chemoembolization. J. Comput. Assist. Tomogr. 2008; 32 ( 5 ): 769 – 771.
dc.identifier.citedreferenceChang Q, Wu N, Ouyang H, Huang Y. Diffusion‐weighted magnetic resonance imaging of lung cancer at 3.0 T: a preliminary study on monitoring diffusion changes during chemoradiation therapy. Clin. Imaging 2012; 36 ( 2 ): 98 – 103.
dc.identifier.citedreferenceOhno Y, Koyama H, Yoshikawa T, Matsumoto K, Aoyama N, Onishi Y, Sugimura K. Diffusion‐weighted MRI versus 18 F‐FDG PET/CT: performance as predictors of tumor treatment response and patient survival in patients with non‐small cell lung cancer receiving chemoradiotherapy. Am. J. Roentgenol. 2012; 198 ( 1 ): 75 – 82.
dc.identifier.citedreferenceOkuma T, Matsuoka T, Yamamoto A, Hamamoto S, Nakamura K, Inoue Y. Assessment of early treatment response after CT‐guided radiofrequency ablation of unresectable lung tumours by diffusion‐weighted MRI: a pilot study. Br. J. Radiol. 2009; 82 ( 984 ): 989 – 994.
dc.identifier.citedreferenceZhou R, Yu T, Feng C, Ma L, Wang Y, Li W, Wang Y. [Diffusion‐weighted imaging for assessment of lung cancer response to chemotherapy]. Zhongguo fei ai za zhi [Chin. J. Lung Cancer] 2011; 14 ( 3 ): 256 – 260.
dc.identifier.citedreferenceLin C, Itti E, Luciani A, Zegai B, Lin SJ, Kuhnowski F, Pigneur F, Gaillard I, Paone G, Meignan M, Haioun C, Rahmouni A. Whole‐body diffusion‐weighted imaging with apparent diffusion coefficient mapping for treatment response assessment in patients with diffuse large B‐cell lymphoma: pilot study. Invest. Radiol. 2011; 46 ( 5 ): 341 – 349.
dc.identifier.citedreferenceMarzolini M, Wong WL, Ardeshna K, Padhani A, D’Sa S. Diffusion‐weighted MRI compared to FDG PET‐CT in the staging and response assessment of Hodgkin lymphoma. Br. J. Haematol. 2012; 156 ( 5 ): 557.
dc.identifier.citedreferenceWu X, Kellokumpu‐Lehtinen PL, Pertovaara H, Korkola P, Soimakallio S, Eskola H, Dastidar P. Diffusion‐weighted MRI in early chemotherapy response evaluation of patients with diffuse large B‐cell lymphoma—a pilot study: comparison with 2‐deoxy‐2‐fluoro‐D‐glucose‐positron emission tomography/computed tomography. NMR Biomed. 2011; 24 ( 10 ): 1181 – 1190.
dc.identifier.citedreferenceFenchel M, Konaktchieva M, Weisel K, Kraus S, Claussen CD, Horger M. Response assessment in patients with multiple myeloma during antiangiogenic therapy using arterial spin labeling and diffusion‐weighted imaging: a feasibility study. Acad. Radiol. 2010; 17 ( 11 ): 1326 – 1323.
dc.identifier.citedreferenceHorger M, Weisel K, Horger W, Mroue A, Fenchel M, Lichy M. Whole‐body diffusion‐weighted MRI with apparent diffusion coefficient mapping for early response monitoring in multiple myeloma: preliminary results. Am. J. Roentgenol. 2011; 196 ( 6 ): W790 – W795.
dc.identifier.citedreferenceKyriazi S, Collins DJ, Messiou C, Pennert K, Davidson RL, Giles SL, Kaye SB, Desouza NM. Metastatic ovarian and primary peritoneal cancer: assessing chemotherapy response with diffusion‐weighted MR imaging—value of histogram analysis of apparent diffusion coefficients. Radiology 2011; 261 ( 1 ): 182 – 192.
dc.identifier.citedreferenceKyriazi S, Nye E, Stamp G, Collins DJ, Kaye SB, deSouza NM. Value of diffusion‐weighted imaging for assessing site‐specific response of advanced ovarian cancer to neoadjuvant chemotherapy: correlation of apparent diffusion coefficients with epithelial and stromal densities on histology. Cancer Biomark 2010; 7 ( 4 ): 201 – 210.
dc.identifier.citedreferenceSala E, Kataoka MY, Priest AN, Gill AB, McLean MA, Joubert I, Graves MJ, Crawford RA, Jimenez‐Linan M, Earl HM, Hodgkin C, Griffiths JR, Lomas DJ, Brenton JD. Advanced ovarian cancer: multiparametric MR imaging demonstrates response‐ and metastasis‐specific effects. Radiology 2012; 263 ( 1 ): 149 – 159.
dc.identifier.citedreferenceNiwa T, Ueno M, Ohkawa S, Yoshida T, Doiuchi T, Ito K, Inoue T. Advanced pancreatic cancer: the use of the apparent diffusion coefficient to predict response to chemotherapy. Br. J. Radiol. 2009; 82 ( 973 ): 28 – 34.
dc.identifier.citedreferenceBarrett T, Gill AB, Kataoka MY, Priest AN, Joubert I, McLean MA, Graves MJ, Stearn S, Lomas DJ, Griffiths JR, Neal D, Gnanapragasam VJ, Sala E. DCE and DW MRI in monitoring response to androgen deprivation therapy in patients with prostate cancer: a feasibility study. Magn. Reson. Med. 2012; 67 ( 3 ): 778 – 785.
dc.identifier.citedreferenceMessiou C, Collins DJ, Giles S, de Bono JS, Bianchini D, de Souza NM. Assessing response in bone metastases in prostate cancer with diffusion weighted MRI. Eur. Radiol. 2011; 21 ( 10 ): 2169 – 2177.
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