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Rengo M, Picchia S, Marzi S, Bellini D, Caruso D, Caterino M, Ciolina M, De Santis D, Musio D, Tombolini V, Laghi A. Magnetic resonance tumor regression grade (MR-TRG) to assess pathological complete response following neoadjuvant radiochemotherapy in locally advanced rectal cancer. Oncotarget 2017; 8:114746-114755. [PMID: 29383117 PMCID: PMC5777729 DOI: 10.18632/oncotarget.21778] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2017] [Accepted: 09/21/2017] [Indexed: 01/06/2023] Open
Abstract
This study aims to evaluate the feasibility of a magnetic resonance (MR) automatic method for quantitative assessment of the percentage of fibrosis developed within locally advanced rectal cancers (LARC) after neoadjuvant radiochemotherapy (RCT). A total of 65 patients were enrolled in the study and MR studies were performed on 3.0 Tesla scanner; patients were followed-up for 30 months. The percentage of fibrosis was quantified on T2-weighted images, using automatic K-Means clustering algorithm. According to the percentage of fibrosis, an optimal cut-off point for separating patients into favorable and unfavorable pathologic response groups was identified by ROC analysis and tumor regression grade (MR-TRG) classes were determined and compared to histopathologic TRG. An optimal cut-off point of 81% of fibrosis was identified to differentiate between favorable and unfavorable pathologic response groups resulting in a sensitivity of 78.26% and a specificity of 97.62% for the identification of complete responders (CRs). Interobserver agreement was good (0.85). The agreement between P-TRG and MR-TRG was excellent (0.923). Significant differences in terms of overall survival (OS) and disease free survival (DFS) were found between favorable and unfavorable pathologic response groups. The automatic quantification of fibrosis determined by MR is feasible and reproducible.
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Affiliation(s)
- Marco Rengo
- Department of Radiological Sciences, Oncology and Pathology. "Sapienza" - University of Rome, Diagnostic Imaging Unit - I.C.O.T. Hospital, Latina, Italy
| | - Simona Picchia
- Department of Radiological Sciences, Oncology and Pathology. "Sapienza" - University of Rome, Diagnostic Imaging Unit - I.C.O.T. Hospital, Latina, Italy
| | - Simona Marzi
- Medical Physics Laboratory, Regina Elena National Cancer Institute, Rome, Italy
| | - Davide Bellini
- Department of Radiological Sciences, Oncology and Pathology. "Sapienza" - University of Rome, Diagnostic Imaging Unit - I.C.O.T. Hospital, Latina, Italy
| | - Damiano Caruso
- Department of Radiological Sciences, Oncology and Pathology. "Sapienza" - University of Rome, Diagnostic Imaging Unit - I.C.O.T. Hospital, Latina, Italy
| | - Mauro Caterino
- Radiology Unit, Regina Elena National Cancer Institute, Rome, Italy
| | - Maria Ciolina
- Department of Radiological Sciences, Oncology and Pathology. "Sapienza" - University of Rome, Diagnostic Imaging Unit - I.C.O.T. Hospital, Latina, Italy
| | - Domenico De Santis
- Department of Radiological Sciences, Oncology and Pathology. "Sapienza" - University of Rome, Diagnostic Imaging Unit - I.C.O.T. Hospital, Latina, Italy
| | - Daniela Musio
- Department of Radiological Sciences, Oncology and Pathology. "Sapienza" - University of Rome, Radiotherapy Unit, Policlinico Umberto I, Rome, Italy
| | - Vincenzo Tombolini
- Department of Radiological Sciences, Oncology and Pathology. "Sapienza" - University of Rome, Radiotherapy Unit, Policlinico Umberto I, Rome, Italy
| | - Andrea Laghi
- Department of Radiological Sciences, Oncology and Pathology. "Sapienza" - University of Rome, Diagnostic Imaging Unit - I.C.O.T. Hospital, Latina, Italy
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