Prediction of burden and management of renal calculi from whole kidney radiomics: a multicenter study
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KIDNEYS, URETERS, BLADDER, RETROPERITONEUM
Prediction of burden and management of renal calculi from whole kidney radiomics: a multicenter study Fatemeh Homayounieh1 · Ruhani Doda Khera1 · Bernardo Canedo Bizzo1 · Shadi Ebrahimian1 · Andrew Primak2 · Bernhard Schmidt3 · Sanjay Saini1 · Mannudeep K. Kalra1 Received: 9 September 2020 / Revised: 6 November 2020 / Accepted: 11 November 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Purpose To assess if autosegmentation-assisted radiomics can predict disease burden, hydronephrosis, and treatment strategies in patients with renal calculi. Methods The local ethical committee-approved, retrospective study included 202 adult patients (mean age: 53 ± 17 years; male: 103; female: 99) who underwent clinically indicated, non-contrast abdomen-pelvis CT for suspected or known renal calculi. All CT examinations were reviewed to determine the presence (n = 123 patients) or absence (n = 79) of renal calculi. On CT images with renal calculi, each kidney stone was annotated and measured (maximum dimension, Hounsfield unit (HU), and combined and dominant stone volumes) using a HU threshold-based segmentation. We recorded the presence of hydronephrosis, number of renal calculi, and treatment strategies. Deidentified CT images were processed with the radiomics prototype (Radiomics, Frontier, Siemens Healthineers), which automatically segmented each kidney to obtain 1690 first-, shape-, and higher-order radiomics. Data were analyzed using multiple logistic regression analysis with areas under the curve (AUC) as output. Results Among 202 patients, only 28 patients (18%) needed procedural treatment (lithotripsy or ureteroscopic stone extraction). Gray-level co-occurrence matrix (GLCM) and gray-level run length matrix (GLRLM) differentiated patients with and without procedural treatment (AUC 0.91, 95% CI 0.85–0.92). Higher-order radiomics (gray-level size zone matrix – GLSZM) differentiated kidneys with and without hydronephrosis (AUC: 0.99, p 0.85. Keywords Renal calculi · Radiomics · CT · Disease burden · Hydronephrosis
Sanjay Saini and Mannudeep K. Kalra have contributed equally to this work.
Abbreviations CT Computed tomography IRB Institutional ethical board
* Fatemeh Homayounieh [email protected]
Sanjay Saini [email protected]
Ruhani Doda Khera [email protected]
Mannudeep K. Kalra [email protected]
Bernardo Canedo Bizzo [email protected]
1
Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 75 Blossom Court, Room 248, Boston, MA 02114, USA
2
Siemens Medical Solutions USA Inc, Malvern, PA, USA
3
Siemens Healthcare GmbH, Forchheim, Germany
Shadi Ebrahimian [email protected] Andrew Primak andrew.primak@siemens‑healthineers.com Bernhard Schmidt bernhard.schmidt@siemens‑healthineers.com
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ROC Receiver operating characteristic AUC Area under the curve DICOM Digital imaging and communication in medicine kV Kilovolt G
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