Literature DB >> 22580810

Assessment of response to chemoradiation therapy in rectal cancer using MR volumetry based on diffusion-weighted data sets: a preliminary report.

S F Carbone1, L Pirtoli, V Ricci, D Venezia, T Carfagno, S Lazzi, V Mourmouras, B Lorenzi, L Volterrani.   

Abstract

PURPOSE: This study evaluated the feasibility of magnetic resonance (MR) volumetry using a diffusion-weighted data set (V(DWI)) and compared it with conventional T2-weighted volumetry (V(C)) in patients affected by rectal cancer treated with chemoradiation therapy (CHRT).
MATERIALS AND METHODS: Fourteen patients with a biopsy diagnosis of rectal cancer underwent MR examination before and after CHRT. T2-weighted images were used to extrapolate V(C). A diffusion-weighted (DW) sequence was acquired [spin-echo diffusion-weighted echo-planar imaging (SE-DW-EPI)] with a b-value of 800 s/mm(2) and volume (V(DWI)) was calculated by semiautomatic segmentation of tumour hyperintensity. Two radiologists independently assessed volumes and analysed data in order to establish interobserver agreement and compare and correlate volumes to tumour regression grade (TRG), as evaluable at pathological examination of the surgical specimen.
RESULTS: Interobserver agreement was 0.977 [(95% confidence interval (CI) 0.954-0.989) and 0.956 (95% CI 0.905-0.980) for V(C) and V(DWI) and 0.964 (95% CI 0.896-0.988) and 0.271 (95% CI-0.267 to 0.686) between V(C) and V(DWI) before and after CHRT. The correlation between TRG and V(C) and V(DWI) was, respectively, rho = 0.597 (p<0.05) and r(2)=0.156 (p=0.162) and rho=0.847 (p<0.001).
CONCLUSIONS: V(DWI) seems to be a promising tool for assessing response to CHRT in rectal cancer. Further studies on large series of patients are needed to refine the technique and evaluate its potential predictive value.

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Year:  2012        PMID: 22580810     DOI: 10.1007/s11547-012-0829-3

Source DB:  PubMed          Journal:  Radiol Med        ISSN: 0033-8362            Impact factor:   3.469


  19 in total

1.  Comparison of CT, MRI and FDG-PET in response prediction of patients with locally advanced rectal cancer after multimodal preoperative therapy: is there a benefit in using functional imaging?

Authors:  T Denecke; B Rau; K-T Hoffmann; B Hildebrandt; J Ruf; M Gutberlet; M Hünerbein; R Felix; P Wust; H Amthauer
Journal:  Eur Radiol       Date:  2005-04-02       Impact factor: 5.315

2.  The relationship of pathologic tumor regression grade (TRG) and outcomes after preoperative therapy in rectal cancer.

Authors:  Fabio Maria Vecchio; Vincenzo Valentini; Bruce D Minsky; Gilbert D A Padula; Ennapadam S Venkatraman; Mario Balducci; Francesco Miccichè; Riccardo Ricci; Alessio Giuseppe Morganti; Maria Antonietta Gambacorta; Francesca Maurizi; Claudio Coco
Journal:  Int J Radiat Oncol Biol Phys       Date:  2005-07-01       Impact factor: 7.038

3.  Usefulness of tumor volumetry by magnetic resonance imaging in assessing response to radiation therapy in carcinoma of the uterine cervix.

Authors:  N A Mayr; V A Magnotta; J C Ehrhardt; J A Wheeler; J I Sorosky; B C Wen; C S Davis; R E Pelsang; B Anderson; J F Doornbos; D H Hussey; W T Yuh
Journal:  Int J Radiat Oncol Biol Phys       Date:  1996-07-15       Impact factor: 7.038

4.  Radiologic assessment of rectosigmoid cancer before and after neoadjuvant radiation therapy: comparison between quantitation techniques.

Authors:  Giacomo Luccichenti; Filippo Cademartiri; Mario Sianesi; Luigi Roncoroni; Paolo Pavone; Gabriel P Krestin
Journal:  AJR Am J Roentgenol       Date:  2005-02       Impact factor: 3.959

5.  MRI after preoperative radiotherapy for rectal cancer; correlation with histopathology and the role of volumetry.

Authors:  Michael R Torkzad; Johan Lindholm; Anna Martling; Björn Cedermark; Bengt Glimelius; Lennart Blomqvist
Journal:  Eur Radiol       Date:  2007-01-31       Impact factor: 5.315

6.  Clinical usefulness of diffusion-weighted imaging using low and high b-values to detect rectal cancer.

Authors:  Tomonori Hosonuma; Mitsuhiro Tozaki; Noriatsu Ichiba; Tohru Sakuma; Daichi Hayashi; Katsuhiko Yanaga; Kunihiko Fukuda
Journal:  Magn Reson Med Sci       Date:  2006-12       Impact factor: 2.471

7.  How accurate is magnetic resonance imaging in restaging rectal cancer in patients receiving preoperative combined chemoradiotherapy?

Authors:  Chien-Chih Chen; Rheun-Chuan Lee; Jen-Kou Lin; Ling-Wei Wang; Shung-Haur Yang
Journal:  Dis Colon Rectum       Date:  2005-04       Impact factor: 4.585

8.  Pathologic response assessed by Mandard grade is a better prognostic factor than down staging for disease-free survival after preoperative radiochemotherapy for advanced rectal cancer.

Authors:  J Suárez; R Vera; E Balén; M Gómez; F Arias; J M Lera; J Herrera; C Zazpe
Journal:  Colorectal Dis       Date:  2007-12-07       Impact factor: 3.788

Review 9.  Optimal methods for staging rectal cancer.

Authors:  V Raman Muthusamy; Kenneth J Chang
Journal:  Clin Cancer Res       Date:  2007-11-15       Impact factor: 12.531

10.  Tumor volume changes assessed by three-dimensional magnetic resonance volumetry in rectal cancer patients after preoperative chemoradiation: the impact of the volume reduction ratio on the prediction of pathologic complete response.

Authors:  Jeong Hyun Kang; Young Chul Kim; Hyunki Kim; Young Wan Kim; Hyuk Hur; Jin Soo Kim; Byung Soh Min; Hogeun Kim; Joon Seok Lim; Jinsil Seong; Ki Chang Keum; Nam Kyu Kim
Journal:  Int J Radiat Oncol Biol Phys       Date:  2009-08-03       Impact factor: 7.038

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  9 in total

Review 1.  Functional MRI for quantitative treatment response prediction in locally advanced rectal cancer.

Authors:  Trang T Pham; Gary P Liney; Karen Wong; Michael B Barton
Journal:  Br J Radiol       Date:  2017-03-07       Impact factor: 3.039

Review 2.  Diffusion MRI in early cancer therapeutic response assessment.

Authors:  C J Galbán; B A Hoff; T L Chenevert; B D Ross
Journal:  NMR Biomed       Date:  2016-01-15       Impact factor: 4.044

3.  Best MRI predictors of complete response to neoadjuvant chemoradiation in locally advanced rectal cancer.

Authors:  Kirthi Sathyakumar; Anuradha Chandramohan; Dipti Masih; Mark Ranjan Jesudasan; Anna Pulimood; Anu Eapen
Journal:  Br J Radiol       Date:  2016-02-01       Impact factor: 3.039

4.  Locally advanced rectal cancer: Qualitative and quantitative evaluation of diffusion-weighted MR imaging in the response assessment after neoadjuvant chemo-radiotherapy.

Authors:  Pietro Valerio Foti; Giuseppe Privitera; Sebastiano Piana; Stefano Palmucci; Corrado Spatola; Roberta Bevilacqua; Luigi Raffaele; Vincenzo Salamone; Rosario Caltabiano; Gaetano Magro; Giovanni Li Destri; Pietro Milone; Giovanni Carlo Ettorre
Journal:  Eur J Radiol Open       Date:  2016-07-18

5.  Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR.

Authors:  Stefano Trebeschi; Joost J M van Griethuysen; Doenja M J Lambregts; Max J Lahaye; Chintan Parmar; Frans C H Bakers; Nicky H G M Peters; Regina G H Beets-Tan; Hugo J W L Aerts
Journal:  Sci Rep       Date:  2017-07-13       Impact factor: 4.379

Review 6.  Rectal cancer MRI: protocols, signs and future perspectives radiologists should consider in everyday clinical practice.

Authors:  Andrea Delli Pizzi; Raffaella Basilico; Roberta Cianci; Barbara Seccia; Mauro Timpani; Alessandra Tavoletta; Daniele Caposiena; Barbara Faricelli; Daniela Gabrielli; Massimo Caulo
Journal:  Insights Imaging       Date:  2018-04-19

7.  MRI for Assessing Response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer Using DCE-MR and DW-MR Data Sets: A Preliminary Report.

Authors:  Mario Petrillo; Roberta Fusco; Orlando Catalano; Mario Sansone; Antonio Avallone; Paolo Delrio; Biagio Pecori; Fabiana Tatangelo; Antonella Petrillo
Journal:  Biomed Res Int       Date:  2015-08-27       Impact factor: 3.411

8.  Time-window of early detection of response to concurrent chemoradiation in cervical cancer by using diffusion-weighted MR imaging: a pilot study.

Authors:  Ying Liu; Haoran Sun; Renju Bai; Zhaoxiang Ye
Journal:  Radiat Oncol       Date:  2015-09-04       Impact factor: 3.481

9.  Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models.

Authors:  Georgios C Manikis; Kostas Marias; Doenja M J Lambregts; Katerina Nikiforaki; Miriam M van Heeswijk; Frans C H Bakers; Regina G H Beets-Tan; Nikolaos Papanikolaou
Journal:  PLoS One       Date:  2017-09-01       Impact factor: 3.240

  9 in total

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