Literature DB >> 25914930

Combined T2w volumetry, DW-MRI and DCE-MRI for response assessment after neo-adjuvant chemoradiation in locally advanced rectal cancer.

Martijn Intven1, Evelyn M Monninkhof2, Onne Reerink1, Marielle E P Philippens1.   

Abstract

BACKGROUND: To assess the value of combined T2-weighted magnetic resonance imaging (MRI) (T2w) volumetry, diffusion-weighted (DW)-MRI and dynamic contrast enhanced (DCE)-MRI for pathological response prediction after neo-adjuvant chemoradiation (CRT) in locally advanced rectal cancer (LARC).
MATERIAL AND METHODS: MRI with DW-MRI and DCE-MRI sequences was performed before start of CRT and before surgery. After surgery, the tumor regression grade (TRG) was obtained based on the score by Mandard et al. Pathological complete responders (pCR, TRG 1), and pathological good responders (GR, TRG 1 + 2) were compared to non-pCR and non-GR patients, respectively.
RESULTS: In total 55 patients were analyzed, six had a pCR (10.9%) and 10 a GR (18.2%). Favorable responders had a larger decrease in tumor volume and Ktrans and a larger increase in apparent diffusion coefficient (ADC) values compared to non-responders. ADC change showed the best diagnostic accuracy for pCR. For GR, the model including ADC change and volume change showed the best diagnostic performance. However, this performance was not statistically better compared to the model with ADC change alone. Inclusion of Ktrans change did not increase the diagnostic accuracy for pathological favorable response.
CONCLUSIONS: This explorative study showed that ADC change is a promising diagnostic tool for pCR and GR. Volume decrease showed potential limited additional diagnostic value for GR while Ktrans change showed no additional diagnostic value for pCR and GR.

Entities:  

Mesh:

Substances:

Year:  2015        PMID: 25914930     DOI: 10.3109/0284186X.2015.1037010

Source DB:  PubMed          Journal:  Acta Oncol        ISSN: 0284-186X            Impact factor:   4.089


  11 in total

Review 1.  Diffusion-weighted imaging in rectal cancer: current applications and future perspectives.

Authors:  Niels W Schurink; Doenja M J Lambregts; Regina G H Beets-Tan
Journal:  Br J Radiol       Date:  2019-03-05       Impact factor: 3.039

2.  Fractal-based radiomic approach to predict complete pathological response after chemo-radiotherapy in rectal cancer.

Authors:  Davide Cusumano; Nicola Dinapoli; Luca Boldrini; Giuditta Chiloiro; Roberto Gatta; Carlotta Masciocchi; Jacopo Lenkowicz; Calogero Casà; Andrea Damiani; Luigi Azario; Johan Van Soest; Andre Dekker; Philippe Lambin; Marco De Spirito; Vincenzo Valentini
Journal:  Radiol Med       Date:  2017-12-11       Impact factor: 3.469

Review 3.  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

4.  Quantitating whole lesion tumor biology in rectal cancer MRI: taking a lesson from FDG-PET tumor metrics.

Authors:  Marc J Gollub; Andreas M Hotker; Kaitlin M Woo; Yousef Mazaheri; Mithat Gonen
Journal:  Abdom Radiol (NY)       Date:  2018-07

Review 5.  [Local imaging of rectal cancer--update 2015: MRI as imaging biomarker].

Authors:  A-O Schäfer
Journal:  Radiologe       Date:  2015-11       Impact factor: 0.635

6.  Intravoxel incoherent motion diffusion-weighted imaging for discriminating the pathological response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

Authors:  Wen Lu; Hou Jing; Zhou Ju-Mei; Nie Shao-Lin; Cao Fang; Yu Xiao-Ping; Lu Qiang; Zeng Biao; Zhu Su-Yu; Hu Ying
Journal:  Sci Rep       Date:  2017-08-17       Impact factor: 4.379

7.  Accurate outcome prediction after neo-adjuvant radio-chemotherapy for rectal cancer based on a TCP-based early regression index.

Authors:  Claudio Fiorino; Paolo Passoni; Anna Palmisano; Calogero Gumina; Giovanni M Cattaneo; Sara Broggi; Alessandra Di Chiara; Antonio Esposito; Martina Mori; Monica Ronzoni; Riccardo Rosati; Najla Slim; Francesco De Cobelli; Riccardo Calandrino; Nadia G Di Muzio
Journal:  Clin Transl Radiat Oncol       Date:  2019-07-03

8.  Optimized Parameters of Diffusion-Weighted MRI for Prediction of the Response to Neoadjuvant Chemoradiotherapy for Locally Advanced Rectal Cancer.

Authors:  Jie Li; Jia Wang; Jing Pang; Shougen Cao; Jingjing Chen; Wenjian Xu
Journal:  Biomed Res Int       Date:  2019-10-13       Impact factor: 3.411

9.  A field strength independent MR radiomics model to predict pathological complete response in locally advanced rectal cancer.

Authors:  Davide Cusumano; Gert Meijer; Jacopo Lenkowicz; Giuditta Chiloiro; Luca Boldrini; Carlotta Masciocchi; Nicola Dinapoli; Roberto Gatta; Calogero Casà; Andrea Damiani; Brunella Barbaro; Maria Antonietta Gambacorta; Luigi Azario; Marco De Spirito; Martijn Intven; Vincenzo Valentini
Journal:  Radiol Med       Date:  2020-08-24       Impact factor: 3.469

10.  Multi-parametric magnetic resonance imaging assessment of whole tumour heterogeneity for chemoradiotherapy response prediction in rectal cancer.

Authors:  Trang Thanh Pham; Gary Liney; Karen Wong; Christopher Henderson; Robba Rai; Petra L Graham; Nira Borok; Minh Xuan Truong; Mark Lee; Joo-Shik Shin; Malcolm Hudson; Michael B Barton
Journal:  Phys Imaging Radiat Oncol       Date:  2021-04-13
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.