{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T09:25:00Z","timestamp":1786958700512,"version":"build-2736575974"},"reference-count":28,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T00:00:00Z","timestamp":1786924800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Life"],"abstract":"<jats:p>Background: The kidneys maintain systemic homeostasis, making renal size assessment essential for evaluating various disorders. Renal volume represents a critical morphometric parameter with distinct clinical significance. This study investigated age-, sex-, and laterality-related differences in renal volume and surface area within an adult population. Methods: A total of 582 kidneys from 291 individuals aged 19 to 89 who underwent abdominal CT scans were retrospectively examined. The images were imported into the 3D Slicer software (version 5.6.2) in DICOM format, and automatic segmentation was performed using the Total Segmentator module. The volumes and surface areas of both kidneys were measured and compared according to age and sex groups. Results: Kidney volume and surface area values were found to be significantly higher in men than in women (p &lt; 0.05). This difference was particularly pronounced in the 30\u201369 age range. The highest volume values were found in women in the 40\u201349 age group, while in men, they were found in the 30\u201359 age group. However, in groups over seventy years old, the gender difference lost its statistical significance. Additionally, the left kidney was found to be significantly larger than the right kidney (p &lt; 0.05). As age increases, a gradual decrease in kidney volume and surface area is observed in both sexes. Conclusions: The progressive decline in renal metrics and the disappearance of sex-based differences after 70 years align with age-related parenchymal atrophy, nephron loss, and reduced blood flow. These findings support the establishment of data baselines for clinical monitoring and surgical planning.<\/jats:p>","DOI":"10.3390\/life16081347","type":"journal-article","created":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T08:05:41Z","timestamp":1786953941000},"page":"1347","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Age, Sex, and Laterality-Based Evaluation of Renal Volume and Surface Area Using CT-Based Three-Dimensional Segmentation"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9946-3026","authenticated-orcid":false,"given":"Ayse Gamze","family":"Ozcan","sequence":"first","affiliation":[{"name":"Department of Anatomy, Faculty of Medicine, Selcuk University, 42130 Konya, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Busra","family":"Pirinc","sequence":"additional","affiliation":[{"name":"Department of Anatomy, Faculty of Medicine, Selcuk University, 42130 Konya, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Betul","family":"Sevindik","sequence":"additional","affiliation":[{"name":"Department of Anatomy, Faculty of Medicine, Selcuk University, 42130 Konya, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5091-0251","authenticated-orcid":false,"given":"Ekrem","family":"Solmaz","sequence":"additional","affiliation":[{"name":"Department of Anatomy, Faculty of Medicine, Selcuk University, 42130 Konya, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mustafa","family":"Koplay","sequence":"additional","affiliation":[{"name":"Department of Radiology, Faculty of Medicine, Selcuk University, 42130 Konya, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmet Kagan","family":"Karabulut","sequence":"additional","affiliation":[{"name":"Department of Anatomy, Faculty of Medicine, Selcuk University, 42130 Konya, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Quaia, E., Martingano, P., Cavallaro, M., Premm, M., and Angileri, R. (2014). Normal Radiological Anatomy and Anatomical Variants of the Kidney, Springer.","DOI":"10.1007\/978-3-642-54047-9_2"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1087","DOI":"10.1259\/0007-1285-68-814-1087","article-title":"How reliable are ultrasound measurements of renal length in adults?","volume":"68","author":"Ablett","year":"1995","journal-title":"Br. J. Radiol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"262","DOI":"10.3349\/ymj.2009.50.2.262","article-title":"Measurement of kidney volume with multi-detector computed tomography scanning in young Korean","volume":"50","author":"Shin","year":"2009","journal-title":"Yonsei Med. J."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.jasi.2017.02.005","article-title":"Comparison of the planimetry and point-counting methods for estimating kidney volume using magnetic resonance imaging","volume":"65","author":"Sagiroglu","year":"2016","journal-title":"J. Anat. Soc. India"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/j.juro.2011.09.005","article-title":"Relationship among total kidney volume, renal function and age","volume":"187","author":"Gong","year":"2012","journal-title":"J. Urol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.neucom.2021.08.157","article-title":"Liver, kidney and spleen segmentation from CT scans and MRI with deep learning: A survey","volume":"490","author":"Altini","year":"2022","journal-title":"Neurocomputing"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1804","DOI":"10.3390\/tomography8040152","article-title":"Deep learning automation of kidney, liver, and spleen segmentation for organ volume measurements in autosomal dominant polycystic kidney disease","volume":"8","author":"Sharbatdaran","year":"2022","journal-title":"Tomography"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1186\/s41747-024-00507-4","article-title":"Segmentation-based quantitative measurements in renal CT imaging using deep learning","volume":"8","author":"Koukoutegos","year":"2024","journal-title":"Eur. Radiol. Exp."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1323","DOI":"10.1016\/j.mri.2012.05.001","article-title":"3D Slicer as an image computing platform for the Quantitative Imaging Network","volume":"30","author":"Fedorov","year":"2012","journal-title":"Magn. Reson. Imaging"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2408","DOI":"10.1007\/s00261-022-03521-5","article-title":"Automated measurement of total kidney volume from 3D ultrasound images of patients affected by polycystic kidney disease and comparison to MR measurements","volume":"47","author":"Jagtap","year":"2022","journal-title":"Abdom. Radiol."},{"key":"ref_11","first-page":"161","article-title":"Usefulness of radiomics and kidney volume based on non-enhanced computed tomography in chronic kidney disease: Initial report","volume":"50","author":"Dobek","year":"2025","journal-title":"Kidney Blood Press. Res."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1016\/j.euf.2020.06.003","article-title":"Developing free three-dimensional software for surgical planning for kidney stones: Volume is better than diameter","volume":"7","author":"Panthier","year":"2021","journal-title":"Eur. Urol. Focus"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1013","DOI":"10.1016\/j.jsurg.2020.03.012","article-title":"Three dimensionally printed interactive training model for kidney transplantation","volume":"77","author":"Claflin","year":"2020","journal-title":"J. Surg. Educ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1007\/s10796-024-10485-y","article-title":"Comprehensive 3D Analysis of the Renal System and Stones: Segmenting and Registering Non-Contrast and Contrast Computed Tomography Images","volume":"27","author":"Chen","year":"2025","journal-title":"Inf. Syst. Front."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/j.transproceed.2023.02.015","article-title":"Reproducibility of Computed Tomography Volumetry for Predicting Post-Donation Remnant Renal Function: A Retrospective Analysis","volume":"55","author":"Nishimura","year":"2023","journal-title":"Transplant. Proc."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.cmpb.2018.01.014","article-title":"Kidney segmentation in ultrasound, magnetic resonance and computed tomography images: A systematic review","volume":"157","author":"Torres","year":"2018","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1007\/s00276-024-03319-8","article-title":"Analysis of sphenoid sinus and ethmoid sinus volume and asymmetry by sex: A 3D-CT study","volume":"46","author":"Akman","year":"2024","journal-title":"Surg. Radiol. Anat."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"e230024","DOI":"10.1148\/ryai.230024","article-title":"TotalSegmentator: Robust segmentation of 104 anatomic structures in CT images","volume":"5","author":"Wasserthal","year":"2023","journal-title":"Radiol. Artif. Intell."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"52","DOI":"10.5395\/rde.2013.38.1.52","article-title":"Statistical notes for clinical researchers: Assessing normal distribution (2) using skewness and kurtosis","volume":"38","author":"Kim","year":"2013","journal-title":"Restor. Dent. Endod."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Glodny, B., Unterholzner, V., Taferner, B., Hofmann, K.J., Rehder, P., Strasak, A., and Petersen, J. (2009). Normal kidney size and its influencing factors-a 64-slice MDCT study of 1.040 asymptomatic patients. BMC Urol., 9.","DOI":"10.1186\/1471-2490-9-19"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"83","DOI":"10.2214\/ajr.160.1.8416654","article-title":"Kidney dimensions at sonography: Correlation with age, sex, and habitus in 665 adult volunteers","volume":"160","author":"Emamian","year":"1993","journal-title":"Am. J. Roentgenol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"561","DOI":"10.7326\/0003-4819-152-9-201005040-00006","article-title":"The association between age and nephrosclerosis on renal biopsy among healthy adults","volume":"152","author":"Rule","year":"2010","journal-title":"Ann. Intern. Med."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"7169","DOI":"10.1097\/JS9.0000000000002030","article-title":"The role of artificial intelligence measured preoperative kidney volume in predicting kidney function loss in elderly kidney donors: A multicenter cohort study","volume":"110","author":"Jo","year":"2024","journal-title":"Int. J. Surg."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3315","DOI":"10.1016\/j.csbj.2023.05.029","article-title":"Current progress in artificial intelligence-assisted medical image analysis for chronic kidney disease: A literature review","volume":"21","author":"Zhao","year":"2023","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"616","DOI":"10.1111\/j.1600-6143.2005.01225.x","article-title":"Donor kidney volume and outcomes following live donor kidney transplantation","volume":"6","author":"Poggio","year":"2006","journal-title":"Am. J. Transplant."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1007\/s10157-017-1454-1","article-title":"The assessment of renal cortex and parenchymal volume using automated CT volumetry for predicting renal function after donor nephrectomy","volume":"22","author":"Mitsui","year":"2018","journal-title":"Clin. Exp. Nephrol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"151","DOI":"10.7863\/jum.1983.2.4.151","article-title":"Ultrasonographic determination of renal mass and renal volume","volume":"2","author":"Jones","year":"1983","journal-title":"J. Ultrasound Med."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Choi, Y.H., Jo, S., Lee, R.W., Kim, J.E., Paek, J.H., Kim, B., Shin, S.-Y., Hwang, S.D., Lee, S.W., and Song, J.H. (2023). Changes in CT-based morphological features of the kidney with declining glomerular filtration rate in chronic kidney disease. 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