Literature DB >> 22208967

Characterizing tumor heterogeneity with functional imaging and quantifying high-risk tumor volume for early prediction of treatment outcome: cervical cancer as a model.

Nina A Mayr1, Zhibin Huang, Jian Z Wang, Simon S Lo, Joline M Fan, John C Grecula, Steffen Sammet, Christina L Sammet, Guang Jia, Jun Zhang, Michael V Knopp, William T C Yuh.   

Abstract

PURPOSE: Treatment response in cancer has been monitored by measuring anatomic tumor volume (ATV) at various times without considering the inherent functional tumor heterogeneity known to critically influence ultimate treatment outcome: primary tumor control and survival. This study applied dynamic contrast-enhanced (DCE) functional MRI to characterize tumors' heterogeneous subregions with low DCE values, at risk for treatment failure, and to quantify the functional risk volume (FRV) for personalized early prediction of treatment outcome. METHODS AND MATERIALS: DCE-MRI was performed in 102 stage IB(2)-IVA cervical cancer patients to assess tumor perfusion heterogeneity before and during radiation/chemotherapy. FRV represents the total volume of tumor voxels with critically low DCE signal intensity (<2.1 compared with precontrast image, determined by previous receiver operator characteristic analysis). FRVs were correlated with treatment outcome (follow-up: 0.2-9.4, mean 6.8 years) and compared with ATVs (Mann-Whitney, Kaplan-Meier, and multivariate analyses).
RESULTS: Before and during therapy at 2-2.5 and 4-5 weeks of RT, FRVs >20, >13, and >5 cm(3), respectively, significantly predicted unfavorable 6-year primary tumor control (p = 0.003, 7.3 × 10(-8), 2.0 × 10(-8)) and disease-specific survival (p = 1.9 × 10(-4), 2.1 × 10(-6), 2.5 × 10(-7), respectively). The FRVs were superior to the ATVs as early predictors of outcome, and the differentiating power of FRVs increased during treatment. DISCUSSION: Our preliminary results suggest that functional tumor heterogeneity can be characterized by DCE-MRI to quantify FRV for predicting ultimate long-term treatment outcome. FRV is a novel functional imaging heterogeneity parameter, superior to ATV, and can be clinically translated for personalized early outcome prediction before or as early as 2-5 weeks into treatment.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 22208967      PMCID: PMC4373343          DOI: 10.1016/j.ijrobp.2011.08.011

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  34 in total

1.  Contrast enhanced dynamic MRI of cervical carcinoma during radiotherapy: early prediction of tumour regression rate.

Authors:  Q Y Gong; J N Brunt; C S Romaniuk; J P Oakley; L T Tan; N Roberts; G H Whitehouse; B Jones
Journal:  Br J Radiol       Date:  1999-12       Impact factor: 3.039

Review 2.  MR microcirculation assessment in cervical cancer: correlations with histomorphological tumor markers and clinical outcome.

Authors:  N A Mayr; H Hawighorst; W T Yuh; M Essig; V A Magnotta; M V Knopp
Journal:  J Magn Reson Imaging       Date:  1999-09       Impact factor: 4.813

3.  Cancer vascularization: implications in radiotherapy?

Authors:  M I Koukourakis; A Giatromanolaki; E Sivridis; I Fezoulidis
Journal:  Int J Radiat Oncol Biol Phys       Date:  2000-09-01       Impact factor: 7.038

4.  The outcome of advanced or recurrent non-squamous carcinoma of the uterine cervix after platinum-based combination chemotherapy.

Authors:  E Kastritis; A Bamias; E Efstathiou; D Gika; G Bozas; P Zorzou; K Sarris; C Papadimitriou; M A Dimopoulos
Journal:  Gynecol Oncol       Date:  2005-07-26       Impact factor: 5.482

5.  Binding of 3H-misonidazole to solid human tumors as a measure of tumor hypoxia.

Authors:  R C Urtasun; J D Chapman; J A Raleigh; A J Franko; C J Koch
Journal:  Int J Radiat Oncol Biol Phys       Date:  1986-07       Impact factor: 7.038

6.  Tumor perfusion studies using fast magnetic resonance imaging technique in advanced cervical cancer: a new noninvasive predictive assay.

Authors:  N A Mayr; W T Yuh; V A Magnotta; J C Ehrhardt; J A Wheeler; J I Sorosky; C S Davis; B C Wen; D D Martin; R E Pelsang; R E Buller; L W Oberley; D E Mellenberg; D H Hussey
Journal:  Int J Radiat Oncol Biol Phys       Date:  1996-10-01       Impact factor: 7.038

7.  The influence of tumor size and morphology on the outcome of patients with FIGO stage IB squamous cell carcinoma of the uterine cervix.

Authors:  P J Eifel; M Morris; J T Wharton; M J Oswald
Journal:  Int J Radiat Oncol Biol Phys       Date:  1994-04-30       Impact factor: 7.038

8.  Pelvic irradiation with concurrent chemotherapy versus pelvic and para-aortic irradiation for high-risk cervical cancer: an update of radiation therapy oncology group trial (RTOG) 90-01.

Authors:  Patricia J Eifel; Kathryn Winter; Mitchell Morris; Charles Levenback; Perry W Grigsby; Jay Cooper; Marvin Rotman; David Gershenson; David G Mutch
Journal:  J Clin Oncol       Date:  2004-03-01       Impact factor: 44.544

9.  Comparison of treatment tolerance and outcomes in patients with cervical cancer treated with concurrent chemoradiotherapy in a prospective randomized trial or with standard treatment.

Authors:  Mylin A Torres; Anuja Jhingran; Howard D Thames; Charles F Levenback; Diane C Bodurka; Lois M Ramondetta; Patricia J Eifel
Journal:  Int J Radiat Oncol Biol Phys       Date:  2007-09-14       Impact factor: 7.038

10.  Intratumoral heterogeneity as a confounding factor in clonogenic assays for tumour radioresponsiveness.

Authors:  R A Britten; A J Evans; M J Allalunis-Turner; A J Franko; R G Pearcey
Journal:  Radiother Oncol       Date:  1996-05       Impact factor: 6.280

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  25 in total

1.  A radiobiological model of radiotherapy response and its correlation with prognostic imaging variables.

Authors:  Mireia Crispin-Ortuzar; Jeho Jeong; Andrew N Fontanella; Joseph O Deasy
Journal:  Phys Med Biol       Date:  2017-01-31       Impact factor: 3.609

Review 2.  Biological imaging in clinical oncology: radiation therapy based on functional imaging.

Authors:  Yo-Liang Lai; Chun-Yi Wu; K S Clifford Chao
Journal:  Int J Clin Oncol       Date:  2016-07-06       Impact factor: 3.402

Review 3.  Predicting outcomes in radiation oncology--multifactorial decision support systems.

Authors:  Philippe Lambin; Ruud G P M van Stiphout; Maud H W Starmans; Emmanuel Rios-Velazquez; Georgi Nalbantov; Hugo J W L Aerts; Erik Roelofs; Wouter van Elmpt; Paul C Boutros; Pierluigi Granone; Vincenzo Valentini; Adrian C Begg; Dirk De Ruysscher; Andre Dekker
Journal:  Nat Rev Clin Oncol       Date:  2012-11-20       Impact factor: 66.675

Review 4.  The role of texture analysis in imaging as an outcome predictor and potential tool in radiotherapy treatment planning.

Authors:  S Alobaidli; S McQuaid; C South; V Prakash; P Evans; A Nisbet
Journal:  Br J Radiol       Date:  2014-07-23       Impact factor: 3.039

Review 5.  Clonal cooperativity in heterogenous cancers.

Authors:  Hengbo Zhou; Deepika Neelakantan; Heide L Ford
Journal:  Semin Cell Dev Biol       Date:  2016-08-28       Impact factor: 7.727

6.  MicroRNA-877 is downregulated in cervical cancer and directly targets MACC1 to inhibit cell proliferation and invasion.

Authors:  Fanxu Meng; Jian Ou; Jinyu Liu; Xindi Li; Yanli Meng; Ling Yan; Ping Deng; Baosheng Sun
Journal:  Exp Ther Med       Date:  2019-09-09       Impact factor: 2.447

7.  miR-197 is downregulated in cervical carcinogenesis and suppresses cell proliferation and invasion through targeting forkhead box M1.

Authors:  Qiyan Hu; Ke Du; Xiaogang Mao; Siqing Ning
Journal:  Oncol Lett       Date:  2018-04-25       Impact factor: 2.967

Review 8.  Clinical applications for diffusion magnetic resonance imaging in radiotherapy.

Authors:  Christina Tsien; Yue Cao; Thomas Chenevert
Journal:  Semin Radiat Oncol       Date:  2014-07       Impact factor: 5.934

9.  Residual tumour volumes and grey zones after external beam radiotherapy (with or without chemotherapy) in cervical cancer patients. A low-field MRI study.

Authors:  M P Schmid; B Mansmann; M Federico; J C A Dimopoulous; P Georg; E Fidarova; W Dörr; R Pötter
Journal:  Strahlenther Onkol       Date:  2013-01-25       Impact factor: 3.621

10.  Validation of optimal DCE-MRI perfusion threshold to classify at-risk tumor imaging voxels in heterogeneous cervical cancer for outcome prediction.

Authors:  Zhibin Huang; Kevin A Yuh; Simon S Lo; John C Grecula; Steffen Sammet; Christina L Sammet; Guang Jia; Michael V Knopp; Qiang Wu; Norman J Beauchamp; William T C Yuh; Roy Wang; Nina A Mayr
Journal:  Magn Reson Imaging       Date:  2014-08-29       Impact factor: 2.546

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