{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T00:22:50Z","timestamp":1766967770587,"version":"3.48.0"},"reference-count":21,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,12,27]],"date-time":"2025-12-27T00:00:00Z","timestamp":1766793600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>This retrospective diagnostic accuracy study compared radiologist-based qualitative assessments and radiomics-based analyses with an automated artificial intelligence (AI)\u2013based volumetric approach for evaluating changes in kidney stone burden on follow-up CT examinations. With institutional review board approval, 157 patients (mean age, 61 \u00b1 13 years; 99 men, 58 women) who underwent baseline and follow-up non-contrast abdomen\u2013pelvis CT for kidney stone evaluation were included. The index test was an automated AI-based whole-kidney and stone segmentation radiomics prototype (Frontier, Siemens Healthineers), which segmented both kidneys and isolated stone volumes using a fixed threshold of 130 Hounsfield units, providing stone volume and maximum diameter per kidney. The reference standard was a threshold-defined volumetric assessment of stone burden change between baseline and follow-up CTs. The radiologist\u2019s performance was assessed using (1) interpretations from clinical radiology reports and (2) an independent radiologist\u2019s assessment of stone burden change (stable, increased, or decreased). Diagnostic accuracy was evaluated using multivariable logistic regression and receiver operating characteristic (ROC) analysis. Automated volumetric assessment identified stable (n = 44), increased (n = 109), and decreased (n = 108) stone burden across the evaluated kidneys. Qualitative assessments from radiology reports demonstrated weak diagnostic performance (AUC range, 0.55\u20130.62), similar to the independent radiologist (AUC range, 0.41\u20130.72) for differentiating changes in stone burden. A model incorporating higher-order radiomics features achieved an AUC of 0.71 for distinguishing increased versus decreased stone burdens compared with the baseline CT (p &lt; 0.001), but did not outperform threshold-based volumetric assessment. The automated threshold-based volumetric quantification of kidney stone burdens provides higher diagnostic accuracy than qualitative radiologist assessments and radiomics-based analyses for identifying a stable, increased, or decreased stone burden on follow-up CT examinations.<\/jats:p>","DOI":"10.3390\/jimaging12010013","type":"journal-article","created":{"date-parts":[[2025,12,28]],"date-time":"2025-12-28T23:54:36Z","timestamp":1766966076000},"page":"13","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Assessing Change in Stone Burden on Baseline and Follow-Up CT: Radiologist and Radiomics Evaluations"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0911-7507","authenticated-orcid":false,"given":"Parisa","family":"Kaviani","sequence":"first","affiliation":[{"name":"Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA"},{"name":"MGB Center for Clinical Data Science, Boston, MA 02120, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8501-2147","authenticated-orcid":false,"given":"Matthias F.","family":"Froelich","sequence":"additional","affiliation":[{"name":"Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA"},{"name":"Department of Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9686-6751","authenticated-orcid":false,"given":"Bernardo","family":"Bizzo","sequence":"additional","affiliation":[{"name":"Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA"},{"name":"MGB Center for Clinical Data Science, Boston, MA 02120, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4349-5587","authenticated-orcid":false,"given":"Andrew","family":"Primak","sequence":"additional","affiliation":[{"name":"Siemens Medical Solutions USA Inc., Malvern, PA 19355, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9246-8265","authenticated-orcid":false,"given":"Giridhar","family":"Dasegowda","sequence":"additional","affiliation":[{"name":"Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA"},{"name":"MGB Center for Clinical Data Science, Boston, MA 02120, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emiliano","family":"Garza-Frias","sequence":"additional","affiliation":[{"name":"Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA"},{"name":"MGB Center for Clinical Data Science, Boston, MA 02120, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lina","family":"Karout","sequence":"additional","affiliation":[{"name":"Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA"},{"name":"MGB Center for Clinical Data Science, Boston, MA 02120, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anushree","family":"Burade","sequence":"additional","affiliation":[{"name":"Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA"},{"name":"MGB Center for Clinical Data Science, Boston, MA 02120, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seyedehelaheh","family":"Hosseini","sequence":"additional","affiliation":[{"name":"Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Javier Eduardo","family":"Contreras Yametti","sequence":"additional","affiliation":[{"name":"Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Keith","family":"Dreyer","sequence":"additional","affiliation":[{"name":"Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA"},{"name":"MGB Center for Clinical Data Science, Boston, MA 02120, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sanjay","family":"Saini","sequence":"additional","affiliation":[{"name":"Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mannudeep","family":"Kalra","sequence":"additional","affiliation":[{"name":"Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA"},{"name":"MGB Center for Clinical Data Science, Boston, MA 02120, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1301","DOI":"10.1007\/s00345-017-2008-6","article-title":"Epidemiology of stone disease across the world","volume":"35","author":"Sorokin","year":"2017","journal-title":"World J. Urol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.eururo.2012.03.052","article-title":"Prevalence of kidney stones in the United States","volume":"62","author":"Scales","year":"2012","journal-title":"Eur. Urol."},{"key":"ref_3","first-page":"267","article-title":"Recurrence after a single renal stone in a community practice","volume":"11","author":"Sutherland","year":"1985","journal-title":"Miner. Electrolyte Metab."},{"key":"ref_4","first-page":"1","article-title":"An overview of treatment options for urinary stones","volume":"7","author":"Shafi","year":"2016","journal-title":"Casp. J. Intern. Med."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1136\/bmj.39113.480185.80","article-title":"Management of kidney stones","volume":"334","author":"Miller","year":"2007","journal-title":"BMJ"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1097\/RUQ.0b013e3182625974","article-title":"ACR Appropriateness Criteria\u00ae acute onset flank pain\u2013suspicion of stone disease","volume":"28","author":"Coursey","year":"2012","journal-title":"Ultrasound Q."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1053\/j.ackd.2008.10.002","article-title":"Economics and cost of care of stone disease","volume":"16","author":"Lotan","year":"2009","journal-title":"Adv. Chronic Kidney Dis."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1016\/j.acra.2021.09.002","article-title":"FDA-regulated AI Algorithms: Trends, Strengths, and Gaps of Validation Studies","volume":"29","author":"Ebrahimian","year":"2021","journal-title":"Acad. Radiol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"714","DOI":"10.1136\/neurintsurg-2016-012845","article-title":"MACRA 2.0: Are you ready for MIPS?","volume":"9","author":"Hirsch","year":"2017","journal-title":"J. Neurointerv. Surg."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1007\/BF01888611","article-title":"Causes of error in gastrointestinal radiology","volume":"5","author":"Ott","year":"1980","journal-title":"Gastrointest. Radiol."},{"key":"ref_11","unstructured":"(2015, November 30). American Board of Urology [Internet]. Available online: http:\/\/www.abu.org\/certification\/qualifying-examination\/."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"766","DOI":"10.1177\/08927790251366899","article-title":"Accurate Assessment of Interval Change in Stone Burden Among Patients with Medullary Sponge Kidney: A Volumetric Approach","volume":"39","author":"Cumpanas","year":"2025","journal-title":"J. Endourol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.jacr.2008.06.011","article-title":"RADPEER\u2122 scoring white paper","volume":"6","author":"Jackson","year":"2009","journal-title":"J. Am. Coll. Radiol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1760","DOI":"10.1007\/s00330-005-2662-8","article-title":"Radiological error: Analysis, standard setting, targeted instruction and teamworking","volume":"15","author":"FitzGerald","year":"2005","journal-title":"Eur. Radiol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"949","DOI":"10.1259\/bjr.74.886.740949","article-title":"Error in radiology","volume":"74","author":"Goddard","year":"2001","journal-title":"Br. J. Radiol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1173","DOI":"10.2214\/AJR.06.1270","article-title":"Accuracy of diagnostic procedures: Has it improved over the past five decades?","volume":"188","author":"Berlin","year":"2007","journal-title":"Am. J. Roentgenol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1952","DOI":"10.1007\/s00330-010-1763-1","article-title":"Abdominal and pelvic computed tomography (CT) interpretation: Discrepancy rates among experienced radiologists","volume":"20","author":"Abujudeh","year":"2010","journal-title":"Eur. Radiol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.urology.2017.10.002","article-title":"Variation in radiologic and urologic computed tomography interpretation of urinary tract stone burden: Results from the registry for stones of the kidney and ureter","volume":"111","author":"Tzou","year":"2018","journal-title":"Urology"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.crad.2016.10.008","article-title":"The accuracy of interpretation of emergency abdominal CT in adult patients who present with non-traumatic abdominal pain: Results of a UK national audit","volume":"72","author":"Howlett","year":"2017","journal-title":"Clin. Radiol."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Zhang, G., Zhang, P., Xia, Y., Shi, F., Zhang, Y., and Ding, D. (2025). Radiomics Analysis of Whole-Kidney Non-Contrast CT for Early Identification of Chronic Kidney Disease Stages 1\u20133. Bioengineering, 12.","DOI":"10.3390\/bioengineering12050454"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2545","DOI":"10.1002\/mp.15518","article-title":"A deep learning system for automated kidney stone detection and volumetric segmentation on noncontrast CT scans","volume":"49","author":"Elton","year":"2022","journal-title":"Med. Phys."}],"container-title":["Journal of Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2313-433X\/12\/1\/13\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T00:18:08Z","timestamp":1766967488000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2313-433X\/12\/1\/13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,27]]},"references-count":21,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,1]]}},"alternative-id":["jimaging12010013"],"URL":"https:\/\/doi.org\/10.3390\/jimaging12010013","relation":{},"ISSN":["2313-433X"],"issn-type":[{"value":"2313-433X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,27]]}}}