A Predictive Model of 2yDFS During MR-Guided RT Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Patients
PurposeDistant metastasis is the main cause of treatment failure in locally advanced rectal cancer (LARC) patients, despite the recent improvement in treatment strategies. This study aims to evaluate the “delta radiomics” approach in patients undergoing neoadjuvant chemoradiotherapy (nCRT) treated w...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-02-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.831712/full |
| _version_ | 1819279304363606016 |
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| author | Giuditta Chiloiro Luca Boldrini Francesco Preziosi Davide Cusumano Poonam Yadav Angela Romano Lorenzo Placidi Jacopo Lenkowicz Nicola Dinapoli Michael F. Bassetti Maria Antonietta Gambacorta Vincenzo Valentini |
| author_facet | Giuditta Chiloiro Luca Boldrini Francesco Preziosi Davide Cusumano Poonam Yadav Angela Romano Lorenzo Placidi Jacopo Lenkowicz Nicola Dinapoli Michael F. Bassetti Maria Antonietta Gambacorta Vincenzo Valentini |
| author_sort | Giuditta Chiloiro |
| collection | DOAJ |
| description | PurposeDistant metastasis is the main cause of treatment failure in locally advanced rectal cancer (LARC) patients, despite the recent improvement in treatment strategies. This study aims to evaluate the “delta radiomics” approach in patients undergoing neoadjuvant chemoradiotherapy (nCRT) treated with 0.35-T magnetic resonance-guided radiotherapy (MRgRT), developing a logistic regression model able to predict 2-year disease-free-survival (2yDFS).MethodsPatients affected by LARC were enrolled in this multi-institutional study. A predictive model of 2yDFS was developed taking into account both clinical and radiomics variables. Gross tumour volume (GTV) was delineated on the magnetic resonance (MR) images acquired during MRgRT, and 1,067 radiomic features (RF) were extracted using the MODDICOM platform. The performance of RF in predicting 2yDFS was investigated in terms of the Wilcoxon–Mann–Whitney test and area under receiver operating characteristic (ROC) curve (AUC).Results48 patients have been retrospectively enrolled, with 8 patients (16.7%) developing distant metastases at the 2-year follow-up. A total of 1,099 variables (1,067 RF and 32 clinical variables) were evaluated in two different models: radiomics and radiomics/clinical. The best-performing 2yDFS predictive model was a delta radiomics one, based on the variation in terms of area/surface ratio between biologically effective doses (BED) at 54 Gy and simulation (AUC of 0.92).ConclusionsThe results of this study suggest a promising role of delta radiomics analysis on 0.35-T MR images in predicting 2yDFS for LARC patients. Further analyses including larger cohorts of patients and an external validation are needed to confirm these preliminary results. |
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| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-24T00:25:46Z |
| publishDate | 2022-02-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Oncology |
| spelling | doaj.art-1d5a2946d3974ff9bcb91a08597862c62022-12-21T17:24:26ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-02-011210.3389/fonc.2022.831712831712A Predictive Model of 2yDFS During MR-Guided RT Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer PatientsGiuditta Chiloiro0Luca Boldrini1Francesco Preziosi2Davide Cusumano3Poonam Yadav4Angela Romano5Lorenzo Placidi6Jacopo Lenkowicz7Nicola Dinapoli8Michael F. Bassetti9Maria Antonietta Gambacorta10Vincenzo Valentini11Dipartimento Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia Fondazione Policlinico Universitario Agostino Gemelli Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, ItalyDipartimento Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia Fondazione Policlinico Universitario Agostino Gemelli Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, ItalyDipartimento Universitario di Scienze Radiologiche ed Ematologiche, Università Cattolica del Sacro Cuore, Rome, ItalyDipartimento Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia Fondazione Policlinico Universitario Agostino Gemelli Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, ItalyDepartment of Human Oncology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United StatesDipartimento Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia Fondazione Policlinico Universitario Agostino Gemelli Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, ItalyDipartimento Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia Fondazione Policlinico Universitario Agostino Gemelli Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, ItalyDipartimento Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia Fondazione Policlinico Universitario Agostino Gemelli Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, ItalyDipartimento Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia Fondazione Policlinico Universitario Agostino Gemelli Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, ItalyDepartment of Human Oncology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United StatesDipartimento Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia Fondazione Policlinico Universitario Agostino Gemelli Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, ItalyDipartimento Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia Fondazione Policlinico Universitario Agostino Gemelli Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, ItalyPurposeDistant metastasis is the main cause of treatment failure in locally advanced rectal cancer (LARC) patients, despite the recent improvement in treatment strategies. This study aims to evaluate the “delta radiomics” approach in patients undergoing neoadjuvant chemoradiotherapy (nCRT) treated with 0.35-T magnetic resonance-guided radiotherapy (MRgRT), developing a logistic regression model able to predict 2-year disease-free-survival (2yDFS).MethodsPatients affected by LARC were enrolled in this multi-institutional study. A predictive model of 2yDFS was developed taking into account both clinical and radiomics variables. Gross tumour volume (GTV) was delineated on the magnetic resonance (MR) images acquired during MRgRT, and 1,067 radiomic features (RF) were extracted using the MODDICOM platform. The performance of RF in predicting 2yDFS was investigated in terms of the Wilcoxon–Mann–Whitney test and area under receiver operating characteristic (ROC) curve (AUC).Results48 patients have been retrospectively enrolled, with 8 patients (16.7%) developing distant metastases at the 2-year follow-up. A total of 1,099 variables (1,067 RF and 32 clinical variables) were evaluated in two different models: radiomics and radiomics/clinical. The best-performing 2yDFS predictive model was a delta radiomics one, based on the variation in terms of area/surface ratio between biologically effective doses (BED) at 54 Gy and simulation (AUC of 0.92).ConclusionsThe results of this study suggest a promising role of delta radiomics analysis on 0.35-T MR images in predicting 2yDFS for LARC patients. Further analyses including larger cohorts of patients and an external validation are needed to confirm these preliminary results.https://www.frontiersin.org/articles/10.3389/fonc.2022.831712/fulldelta radiomicspredictive modelrectal cancerMRgRTneoadjuvant chemoradiotherapy |
| spellingShingle | Giuditta Chiloiro Luca Boldrini Francesco Preziosi Davide Cusumano Poonam Yadav Angela Romano Lorenzo Placidi Jacopo Lenkowicz Nicola Dinapoli Michael F. Bassetti Maria Antonietta Gambacorta Vincenzo Valentini A Predictive Model of 2yDFS During MR-Guided RT Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Patients Frontiers in Oncology delta radiomics predictive model rectal cancer MRgRT neoadjuvant chemoradiotherapy |
| title | A Predictive Model of 2yDFS During MR-Guided RT Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Patients |
| title_full | A Predictive Model of 2yDFS During MR-Guided RT Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Patients |
| title_fullStr | A Predictive Model of 2yDFS During MR-Guided RT Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Patients |
| title_full_unstemmed | A Predictive Model of 2yDFS During MR-Guided RT Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Patients |
| title_short | A Predictive Model of 2yDFS During MR-Guided RT Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Patients |
| title_sort | predictive model of 2ydfs during mr guided rt neoadjuvant chemoradiotherapy in locally advanced rectal cancer patients |
| topic | delta radiomics predictive model rectal cancer MRgRT neoadjuvant chemoradiotherapy |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2022.831712/full |
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