Age-related morphometrics of normal adrenal glands based on deep learning-aided segmentation
Objective.This study aims to evaluate the morphometrics of normal adrenal glands in adult patients semiautomatically using a deep learning-based segmentation model.Materials and Methods.A total of 520 abdominal CT image series with normal findings, from January 1, 2016, to March 14, 2019, were retro...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-06-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023040173 |
| _version_ | 1797809764644683776 |
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| author | Yuanchong Chen Jiejin Yang Yaofeng Zhang Yumeng Sun Xiaodong Zhang Xiaoying Wang |
| author_facet | Yuanchong Chen Jiejin Yang Yaofeng Zhang Yumeng Sun Xiaodong Zhang Xiaoying Wang |
| author_sort | Yuanchong Chen |
| collection | DOAJ |
| description | Objective.This study aims to evaluate the morphometrics of normal adrenal glands in adult patients semiautomatically using a deep learning-based segmentation model.Materials and Methods.A total of 520 abdominal CT image series with normal findings, from January 1, 2016, to March 14, 2019, were retrospectively collected for the training of the adrenal segmentation model. Then, 1043 portal venous phase image series of inpatient contrast-enhanced abdominal CT examinations with normal adrenal glands were included for analysis and grouped by every 10-year gap. A 3D U-Net-based segmentation model was used to predict bilateral adrenal labels followed by manual modification of labels as appropriate. Quantitative parameters (volume, CT value, and diameters) of the bilateral adrenal glands were then analyzed.Results.In the study cohort aged 18–77 years old (554 males and 489 females), the left adrenal gland was significantly larger than the right adrenal gland [all patients, 2867.79 (2317.11–3499.89) mm3 vs. 2452.84 (1983.50–2935.18) mm3, P < 0.001]. Male patients showed a greater volume of bilateral adrenal glands than females in all age groups (all patients, left: 3237.83 ± 930.21 mm3 vs. 2646.49 ± 766.42 mm3, P < 0.001; right: 2731.69 ± 789.19 mm3 vs. 2266.18 ± 632.97 mm3, P = 0.001). Bilateral adrenal volume in male patients showed an increasing then decreasing trend as age increased that peaked at 38–47 years old (left: 3416.01 ± 886.21 mm3, right: 2855.04 ± 774.57 mm3).Conclusions.The semiautomated measurement revealed that the adrenal volume differs as age increases. Male patients aged 38–47 years old have a peaked adrenal volume. |
| first_indexed | 2024-03-13T06:58:42Z |
| format | Article |
| id | doaj.art-2824f1cc576743f9ae812597bb7d04db |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-13T06:58:42Z |
| publishDate | 2023-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-2824f1cc576743f9ae812597bb7d04db2023-06-07T04:49:14ZengElsevierHeliyon2405-84402023-06-0196e16810Age-related morphometrics of normal adrenal glands based on deep learning-aided segmentationYuanchong Chen0Jiejin Yang1Yaofeng Zhang2Yumeng Sun3Xiaodong Zhang4Xiaoying Wang5Department of Radiology, Peking University First Hospital, Beijing, 100034, ChinaDepartment of Radiology, Peking University First Hospital, Beijing, 100034, ChinaBeijing Smart-imaging Technology Co. Ltd., Beijing, 100011, ChinaBeijing Smart-imaging Technology Co. Ltd., Beijing, 100011, ChinaDepartment of Radiology, Peking University First Hospital, Beijing, 100034, ChinaDepartment of Radiology, Peking University First Hospital, Beijing, 100034, China; Corresponding author. Department of Radiology, Peking University First Hospital No. 8 Xishiku St., Xicheng District, Beijing, 100034, China.Objective.This study aims to evaluate the morphometrics of normal adrenal glands in adult patients semiautomatically using a deep learning-based segmentation model.Materials and Methods.A total of 520 abdominal CT image series with normal findings, from January 1, 2016, to March 14, 2019, were retrospectively collected for the training of the adrenal segmentation model. Then, 1043 portal venous phase image series of inpatient contrast-enhanced abdominal CT examinations with normal adrenal glands were included for analysis and grouped by every 10-year gap. A 3D U-Net-based segmentation model was used to predict bilateral adrenal labels followed by manual modification of labels as appropriate. Quantitative parameters (volume, CT value, and diameters) of the bilateral adrenal glands were then analyzed.Results.In the study cohort aged 18–77 years old (554 males and 489 females), the left adrenal gland was significantly larger than the right adrenal gland [all patients, 2867.79 (2317.11–3499.89) mm3 vs. 2452.84 (1983.50–2935.18) mm3, P < 0.001]. Male patients showed a greater volume of bilateral adrenal glands than females in all age groups (all patients, left: 3237.83 ± 930.21 mm3 vs. 2646.49 ± 766.42 mm3, P < 0.001; right: 2731.69 ± 789.19 mm3 vs. 2266.18 ± 632.97 mm3, P = 0.001). Bilateral adrenal volume in male patients showed an increasing then decreasing trend as age increased that peaked at 38–47 years old (left: 3416.01 ± 886.21 mm3, right: 2855.04 ± 774.57 mm3).Conclusions.The semiautomated measurement revealed that the adrenal volume differs as age increases. Male patients aged 38–47 years old have a peaked adrenal volume.http://www.sciencedirect.com/science/article/pii/S2405844023040173Adrenal glandDeep learningMorphometricsComputed tomography |
| spellingShingle | Yuanchong Chen Jiejin Yang Yaofeng Zhang Yumeng Sun Xiaodong Zhang Xiaoying Wang Age-related morphometrics of normal adrenal glands based on deep learning-aided segmentation Heliyon Adrenal gland Deep learning Morphometrics Computed tomography |
| title | Age-related morphometrics of normal adrenal glands based on deep learning-aided segmentation |
| title_full | Age-related morphometrics of normal adrenal glands based on deep learning-aided segmentation |
| title_fullStr | Age-related morphometrics of normal adrenal glands based on deep learning-aided segmentation |
| title_full_unstemmed | Age-related morphometrics of normal adrenal glands based on deep learning-aided segmentation |
| title_short | Age-related morphometrics of normal adrenal glands based on deep learning-aided segmentation |
| title_sort | age related morphometrics of normal adrenal glands based on deep learning aided segmentation |
| topic | Adrenal gland Deep learning Morphometrics Computed tomography |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023040173 |
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