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Items: 1 to 20 of 67

1.

Texture Analysis as Imaging Biomarker for recurrence in advanced cervical cancer treated with CCRT.

Meng J, Liu S, Zhu L, Zhu L, Wang H, Xie L, Guan Y, He J, Yang X, Zhou Z.

Sci Rep. 2018 Jul 30;8(1):11399. doi: 10.1038/s41598-018-29838-0.

2.

Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT.

Meng J, Zhu L, Zhu L, Xie L, Wang H, Liu S, Yan J, Liu B, Guan Y, He J, Ge Y, Zhou Z, Yang X.

Oncotarget. 2017 Sep 28;8(54):92442-92453. doi: 10.18632/oncotarget.21374. eCollection 2017 Nov 3.

3.

Apparent diffusion coefficient histogram shape analysis for monitoring early response in patients with advanced cervical cancers undergoing concurrent chemo-radiotherapy.

Meng J, Zhu L, Zhu L, Wang H, Liu S, Yan J, Liu B, Guan Y, Ge Y, He J, Zhou Z, Yang X.

Radiat Oncol. 2016 Oct 22;11(1):141.

4.

Evaluating early response of cervical cancer under concurrent chemo-radiotherapy by intravoxel incoherent motion MR imaging.

Zhu L, Zhu L, Shi H, Wang H, Yan J, Liu B, Chen W, He J, Zhou Z, Yang X, Liu T.

BMC Cancer. 2016 Feb 10;16:79. doi: 10.1186/s12885-016-2116-5.

5.

Histogram analysis of apparent diffusion coefficient for monitoring early response in patients with advanced cervical cancers undergoing concurrent chemo-radiotherapy.

Meng J, Zhu L, Zhu L, Ge Y, He J, Zhou Z, Yang X.

Acta Radiol. 2017 Nov;58(11):1400-1408. doi: 10.1177/0284185117694509. Epub 2017 Feb 27.

PMID:
28273745
6.

Role of apparent diffusion coefficient as a biomarker in the evaluation of cervical cancer.

Dashottar S, Preeth Pany T, Lohia N.

Indian J Radiol Imaging. 2019 Jan-Mar;29(1):25-32. doi: 10.4103/ijri.IJRI_441_18.

7.

Predicting tumor recurrence in patients with cervical carcinoma treated with definitive chemoradiotherapy: value of quantitative histogram analysis on diffusion-weighted MR images.

Erbay G, Onal C, Karadeli E, Guler OC, Arica S, Koc Z.

Acta Radiol. 2017 Apr;58(4):481-488. doi: 10.1177/0284185116656492. Epub 2016 Jul 28.

PMID:
27445314
8.

Integrated radiomic framework for breast cancer and tumor biology using advanced machine learning and multiparametric MRI.

Parekh VS, Jacobs MA.

NPJ Breast Cancer. 2017 Nov 14;3:43. doi: 10.1038/s41523-017-0045-3. eCollection 2017.

9.

Predicting and Early Monitoring Treatment Efficiency of Cervical Cancer Under Concurrent Chemoradiotherapy by Intravoxel Incoherent Motion Magnetic Resonance Imaging.

Zhu L, Zhu L, Wang H, Yan J, Liu B, Chen W, He J, Zhou Z, Yang X.

J Comput Assist Tomogr. 2017 May/Jun;41(3):422-429. doi: 10.1097/RCT.0000000000000550.

PMID:
27824669
10.

Diffusion and perfusion MRI prediction of progression-free survival in patients with hepatocellular carcinoma treated with concurrent chemoradiotherapy.

Kim KA, Park MS, Ji HJ, Park JY, Han KH, Kim MJ, Kim KW.

J Magn Reson Imaging. 2014 Feb;39(2):286-92. doi: 10.1002/jmri.24161. Epub 2013 Dec 2.

PMID:
24302545
11.

Assessment of early response to concurrent chemoradiotherapy in cervical cancer: value of diffusion-weighted and dynamic contrast-enhanced MR imaging.

Park JJ, Kim CK, Park SY, Simonetti AW, Kim E, Park BK, Huh SJ.

Magn Reson Imaging. 2014 Oct;32(8):993-1000. doi: 10.1016/j.mri.2014.05.009. Epub 2014 Jun 23.

PMID:
24970025
12.

Comparison of FDG PET metabolic tumour volume versus ADC histogram: prognostic value of tumour treatment response and survival in patients with locally advanced uterine cervical cancer.

Ueno Y, Lisbona R, Tamada T, Alaref A, Sugimura K, Reinhold C.

Br J Radiol. 2017 Jul;90(1075):20170035. doi: 10.1259/bjr.20170035. Epub 2017 Jun 16.

13.

Locally advanced rectal cancer: predicting non-responders to neoadjuvant chemoradiotherapy using apparent diffusion coefficient textures.

Liu M, Lv H, Liu LH, Yang ZH, Jin EH, Wang ZC.

Int J Colorectal Dis. 2017 Jul;32(7):1009-1012. doi: 10.1007/s00384-017-2835-3. Epub 2017 May 11.

PMID:
28497403
14.

Pre-treatment MRI minimum apparent diffusion coefficient value is a potential prognostic imaging biomarker in cervical cancer patients treated with definitive chemoradiation.

Marconi DG, Fregnani JH, Rossini RR, Netto AK, Lucchesi FR, Tsunoda AT, Kamrava M.

BMC Cancer. 2016 Jul 28;16:556. doi: 10.1186/s12885-016-2619-0.

15.

Magnetic resonance based texture parameters as potential imaging biomarkers for predicting long-term survival in locally advanced rectal cancer treated by chemoradiotherapy.

Jalil O, Afaq A, Ganeshan B, Patel UB, Boone D, Endozo R, Groves A, Sizer B, Arulampalam T.

Colorectal Dis. 2017 Apr;19(4):349-362. doi: 10.1111/codi.13496.

PMID:
27538267
16.

Detection of prostate cancer by integration of line-scan diffusion, T2-mapping and T2-weighted magnetic resonance imaging; a multichannel statistical classifier.

Chan I, Wells W 3rd, Mulkern RV, Haker S, Zhang J, Zou KH, Maier SE, Tempany CM.

Med Phys. 2003 Sep;30(9):2390-8.

PMID:
14528961
17.

Association of Apparent Diffusion Coefficient with Disease Recurrence in Patients with Locally Advanced Cervical Cancer Treated with Radical Chemotherapy and Radiation Therapy.

Gladwish A, Milosevic M, Fyles A, Xie J, Halankar J, Metser U, Jiang H, Becker N, Levin W, Manchul L, Foltz W, Han K.

Radiology. 2016 Apr;279(1):158-66. doi: 10.1148/radiol.2015150400. Epub 2015 Oct 27.

PMID:
26505922
18.

Differentiation of true progression from pseudoprogression in glioblastoma treated with radiation therapy and concomitant temozolomide: comparison study of standard and high-b-value diffusion-weighted imaging.

Chu HH, Choi SH, Ryoo I, Kim SC, Yeom JA, Shin H, Jung SC, Lee AL, Yoon TJ, Kim TM, Lee SH, Park CK, Kim JH, Sohn CH, Park SH, Kim IH.

Radiology. 2013 Dec;269(3):831-40. doi: 10.1148/radiol.13122024. Epub 2013 Oct 28.

PMID:
23771912
19.

Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors.

Rodriguez Gutierrez D, Awwad A, Meijer L, Manita M, Jaspan T, Dineen RA, Grundy RG, Auer DP.

AJNR Am J Neuroradiol. 2014 May;35(5):1009-15. doi: 10.3174/ajnr.A3784. Epub 2013 Dec 5.

20.

Stability of radiomic features of apparent diffusion coefficient (ADC) maps for locally advanced rectal cancer in response to image pre-processing.

Traverso A, Kazmierski M, Shi Z, Kalendralis P, Welch M, Nissen HD, Jaffray D, Dekker A, Wee L.

Phys Med. 2019 May;61:44-51. doi: 10.1016/j.ejmp.2019.04.009. Epub 2019 Apr 28.

PMID:
31151578

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