Radiomics and Magnetic Resonance Imaging of Rectal Cancer: From Engineering to Clinical Practice

被引:54
作者
Coppola, Francesca [1 ]
Giannini, Valentina [2 ]
Gabelloni, Michela [3 ]
Panic, Jovana [2 ]
Defeudis, Arianna [2 ]
Lo Monaco, Silvia [1 ]
Cattabriga, Arrigo [1 ]
Cocozza, Maria Adriana [1 ]
Pastore, Luigi Vincenzo [1 ]
Polici, Michela [4 ]
Caruso, Damiano [4 ]
Laghi, Andrea [4 ]
Regge, Daniele [2 ,5 ]
Neri, Emanuele [3 ]
Golfieri, Rita [1 ]
Faggioni, Lorenzo [3 ]
机构
[1] IRCCS Azienda Osped Univ Bologna, Dept Radiol, I-40138 Bologna, Italy
[2] Univ Turin, Dept Surg Sci, I-10124 Turin, Italy
[3] Univ Pisa, Dept Translat Res, Diagnost & Intervent Radiol, I-56126 Pisa, Italy
[4] Sapienza Univ Rome, Dept Surg & Med Sci & Translat Med, St Andrea Univ Hosp, Radiol Unit, I-00189 Rome, Italy
[5] FPO IRCCS, Candiolo Canc Inst, Dept Radiol, I-10060 Turin, Italy
关键词
rectal cancer; surgery; neoadjuvant chemoradiation therapy; magnetic resonance imaging; radiomics; deep learning; personalized medicine; MRI-BASED RADIOMICS; PREOPERATIVE CHEMORADIOTHERAPY; NEOADJUVANT CHEMORADIOTHERAPY; COLORECTAL-CANCER; MICROSATELLITE INSTABILITY; TEXTURE ANALYSIS; PREDICTION; FEATURES; SEGMENTATION; IMAGES;
D O I
10.3390/diagnostics11050756
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
While cross-sectional imaging has seen continuous progress and plays an undiscussed pivotal role in the diagnostic management and treatment planning of patients with rectal cancer, a largely unmet need remains for improved staging accuracy, assessment of treatment response and prediction of individual patient outcome. Moreover, the increasing availability of target therapies has called for developing reliable diagnostic tools for identifying potential responders and optimizing overall treatment strategy on a personalized basis. Radiomics has emerged as a promising, still fully evolving research topic, which could harness the power of modern computer technology to generate quantitative information from imaging datasets based on advanced data-driven biomathematical models, potentially providing an added value to conventional imaging for improved patient management. The present study aimed to illustrate the contribution that current radiomics methods applied to magnetic resonance imaging can offer to managing patients with rectal cancer.
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页数:15
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