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Optimization of Preoperative Lymph Node Staging in Patients with Muscle-Invasive Bladder Cancer Using Radiomics on Computed Tomography

by Starmans, Martijn P. A. , Klaver, Sjoerd , Cauberg, Evelyne C. C. , Ho, Li Shen , Boevé, Egbert R. , van der Heijden, Antoine G. , te Slaa, Ed , Beije, Nick , Klein, Stefan , de Kruijff, Inge , van de Luijtgaarden, Addy C. M. , van Melick, Harm H. E. , Somford, Diederik M. , van der Veldt, Astrid A. M. , Wijburg, Carl J. , Cauffman, Ella , Jacobs, Rens , Smits, Fokko , de Vries, Peter , de Jong, Joep J. , Visser, Jacob J. , Boormans, Joost L. , Niessen, Wiro J.

in Abdomen / Accuracy / Bladder cancer / Cancer therapies / Chemotherapy / Computed tomography / Dissection / Invasiveness / Lymph nodes / Lymphatic system / Medical imaging / Metastases / Metastasis / Patients / Precision medicine / Radiomics / Segmentation / Tomography / Tumors

2022

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Optimization of Preoperative Lymph Node Staging in Patients with Muscle-Invasive Bladder Cancer Using Radiomics on Computed Tomography

2022

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Optimization of Preoperative Lymph Node Staging in Patients with Muscle-Invasive Bladder Cancer Using Radiomics on Computed Tomography

2022

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Journal Article

Optimization of Preoperative Lymph Node Staging in Patients with Muscle-Invasive Bladder Cancer Using Radiomics on Computed Tomography

Starmans, Martijn P. A.,

Klaver, Sjoerd,

Cauberg, Evelyne C. C.,

Ho, Li Shen,

Boevé, Egbert R.,

van der Heijden, Antoine G.,

te Slaa, Ed,

Beije, Nick,

Klein, Stefan,

de Kruijff, Inge,

van de Luijtgaarden, Addy C. M.,

van Melick, Harm H. E.,

Somford, Diederik M.,

van der Veldt, Astrid A. M.,

Wijburg, Carl J.,

Cauffman, Ella,

Jacobs, Rens,

Smits, Fokko,

de Vries, Peter,

de Jong, Joep J.,

Visser, Jacob J.,

Boormans, Joost L.,

Niessen, Wiro J.

2022

Overview

Approximately 25% of the patients with muscle-invasive bladder cancer (MIBC) who are clinically node negative have occult lymph node metastases at radical cystectomy (RC) and pelvic lymph node dissection. The aim of this study was to evaluate preoperative CT-based radiomics to differentiate between pN+ and pN0 disease in patients with clinical stage cT2-T4aN0-N1M0 MIBC. Patients with cT2-T4aN0-N1M0 MIBC, of whom preoperative CT scans and pathology reports were available, were included from the prospective, multicenter CirGuidance trial. After manual segmentation of the lymph nodes, 564 radiomics features were extracted. A combination of different machine-learning methods was used to develop various decision models to differentiate between patients with pN+ and pN0 disease. A total of 209 patients (159 pN0; 50 pN+) were included, with a total of 3153 segmented lymph nodes. None of the individual radiomics features showed significant differences between pN+ and pN0 disease, and none of the radiomics models performed substantially better than random guessing. Hence, CT-based radiomics does not contribute to differentiation between pN+ and pN0 disease in patients with cT2-T4aN0-N1M0 MIBC.

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MDPI AG,MDPI

Subject

/ Computed tomography

/ Dissection