Radiomic-enhanced multimodal ultrasound for early detection of acute kidney injury secondary to renal vein thrombosis: a preclinical diagnostic modeling study
Acute kidney injury (AKI) resulting from acute renal vein thrombosis (ARVT) is uncommon, yet it can progress swiftly, requiring prompt diagnosis and intervention. This study aimed to investigate the various multimodal ultrasound techniques, specifically conventional ultrasound (CUS), microvascular f...
Αποθηκεύτηκε σε:
| Κύριοι συγγραφείς: | , , , |
|---|---|
| Μορφή: | Άρθρο |
| Γλώσσα: | Αγγλικά |
| Έκδοση: |
Taylor & Francis Group
2025-12-01
|
| Σειρά: | Renal Failure |
| Θέματα: | |
| Διαθέσιμο Online: | https://www.tandfonline.com/doi/10.1080/0886022X.2025.2525472 |
| Ετικέτες: |
Προσθήκη ετικέτας
Δεν υπάρχουν, Καταχωρήστε ετικέτα πρώτοι!
|
| _version_ | 1839645751040278528 |
|---|---|
| author | Ziyi Xu Xinghua Wang Nan Qiao Tao Zhang |
| author_facet | Ziyi Xu Xinghua Wang Nan Qiao Tao Zhang |
| author_sort | Ziyi Xu |
| collection | DOAJ |
| description | Acute kidney injury (AKI) resulting from acute renal vein thrombosis (ARVT) is uncommon, yet it can progress swiftly, requiring prompt diagnosis and intervention. This study aimed to investigate the various multimodal ultrasound techniques, specifically conventional ultrasound (CUS), microvascular flow imaging (MFI), contrast-enhanced ultrasound (CEUS), and shear wave elastography (SWE), in conjunction with radiomics for early diagnosis and assessment of AKI resulting from ARVT using a rabbit model. Twenty healthy adult New Zealand white rabbits with 40 kidneys were included in this study. The left kidneys were designated as the experimental group (n = 20), whereas the right kidneys served as the control group(n = 20). Throughout the study, multimodal ultrasound techniques were employed for image acquisition and analysis. The ultrasound images underwent processing, segmentation, feature extraction, and model construction. The dataset was randomly divided in a 7:3 ratio, and the performance of models was assessed through the Receiver Operating Characteristic Curve (ROC) analysis along with key performance metrics. In CUS images, the experimental group showed notable increases in renal volume, cortical thickness, and enhanced cortical echogenicity (p < 0.001, p = 0.032, p < 0.001). In the CDFI, MFI, and CEUS, the experimental group exhibited significant reductions in blood flow perfusion (p < 0.001). In SWE, Young’s modulus values for the cortex, medulla, and sinus were significantly elevated in the experimental group (p < 0.001). The strongest correlations were found for creatinine, renal volume, peak systolic velocity of the arcuate artery, time from peak to half-value of sinus, and Young’s modulus value for cortex minimum, with Area Under the Curve(AUC) values of 0.600, 0.868, 0.560, 0.503, and 0.982, respectively. The CUS, CDFI, MFI, CEUS, SWE, and CUS+CDFI+MFI+CEUS+SWE radiomics models demonstrated stronger performance, achieving AUC values of 0.899, 0.861, 0.899, 0.833, 0.861, and 0.734, respectively. Multimodal ultrasound combined with radiomics can significantly improve early diagnosis of AKI following ARVT, providing valuable insights for clinical research. |
| format | Article |
| id | doaj-art-0d3392481adf4e24bf6310f412ccca76 |
| institution | Matheson Library |
| issn | 0886-022X 1525-6049 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Renal Failure |
| spelling | doaj-art-0d3392481adf4e24bf6310f412ccca762025-07-01T09:29:44ZengTaylor & Francis GroupRenal Failure0886-022X1525-60492025-12-0147110.1080/0886022X.2025.2525472Radiomic-enhanced multimodal ultrasound for early detection of acute kidney injury secondary to renal vein thrombosis: a preclinical diagnostic modeling studyZiyi Xu0Xinghua Wang1Nan Qiao2Tao Zhang3Department of Ultrasound, Shanxi Provincial People’s Hospital Affiliated to Shanxi Medical University, Taiyuan, ChinaDepartments of Ultrasound, Second Hospital of Shanxi Medical University, Taiyuan, ChinaShanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, ChinaMedical Imaging Department of Shanxi Medical University, Taiyuan, ChinaAcute kidney injury (AKI) resulting from acute renal vein thrombosis (ARVT) is uncommon, yet it can progress swiftly, requiring prompt diagnosis and intervention. This study aimed to investigate the various multimodal ultrasound techniques, specifically conventional ultrasound (CUS), microvascular flow imaging (MFI), contrast-enhanced ultrasound (CEUS), and shear wave elastography (SWE), in conjunction with radiomics for early diagnosis and assessment of AKI resulting from ARVT using a rabbit model. Twenty healthy adult New Zealand white rabbits with 40 kidneys were included in this study. The left kidneys were designated as the experimental group (n = 20), whereas the right kidneys served as the control group(n = 20). Throughout the study, multimodal ultrasound techniques were employed for image acquisition and analysis. The ultrasound images underwent processing, segmentation, feature extraction, and model construction. The dataset was randomly divided in a 7:3 ratio, and the performance of models was assessed through the Receiver Operating Characteristic Curve (ROC) analysis along with key performance metrics. In CUS images, the experimental group showed notable increases in renal volume, cortical thickness, and enhanced cortical echogenicity (p < 0.001, p = 0.032, p < 0.001). In the CDFI, MFI, and CEUS, the experimental group exhibited significant reductions in blood flow perfusion (p < 0.001). In SWE, Young’s modulus values for the cortex, medulla, and sinus were significantly elevated in the experimental group (p < 0.001). The strongest correlations were found for creatinine, renal volume, peak systolic velocity of the arcuate artery, time from peak to half-value of sinus, and Young’s modulus value for cortex minimum, with Area Under the Curve(AUC) values of 0.600, 0.868, 0.560, 0.503, and 0.982, respectively. The CUS, CDFI, MFI, CEUS, SWE, and CUS+CDFI+MFI+CEUS+SWE radiomics models demonstrated stronger performance, achieving AUC values of 0.899, 0.861, 0.899, 0.833, 0.861, and 0.734, respectively. Multimodal ultrasound combined with radiomics can significantly improve early diagnosis of AKI following ARVT, providing valuable insights for clinical research.https://www.tandfonline.com/doi/10.1080/0886022X.2025.2525472Multimodalultrasoundradiomicsacute kidney injuryacute renal vein thrombosis |
| spellingShingle | Ziyi Xu Xinghua Wang Nan Qiao Tao Zhang Radiomic-enhanced multimodal ultrasound for early detection of acute kidney injury secondary to renal vein thrombosis: a preclinical diagnostic modeling study Renal Failure Multimodal ultrasound radiomics acute kidney injury acute renal vein thrombosis |
| title | Radiomic-enhanced multimodal ultrasound for early detection of acute kidney injury secondary to renal vein thrombosis: a preclinical diagnostic modeling study |
| title_full | Radiomic-enhanced multimodal ultrasound for early detection of acute kidney injury secondary to renal vein thrombosis: a preclinical diagnostic modeling study |
| title_fullStr | Radiomic-enhanced multimodal ultrasound for early detection of acute kidney injury secondary to renal vein thrombosis: a preclinical diagnostic modeling study |
| title_full_unstemmed | Radiomic-enhanced multimodal ultrasound for early detection of acute kidney injury secondary to renal vein thrombosis: a preclinical diagnostic modeling study |
| title_short | Radiomic-enhanced multimodal ultrasound for early detection of acute kidney injury secondary to renal vein thrombosis: a preclinical diagnostic modeling study |
| title_sort | radiomic enhanced multimodal ultrasound for early detection of acute kidney injury secondary to renal vein thrombosis a preclinical diagnostic modeling study |
| topic | Multimodal ultrasound radiomics acute kidney injury acute renal vein thrombosis |
| url | https://www.tandfonline.com/doi/10.1080/0886022X.2025.2525472 |
| work_keys_str_mv | AT ziyixu radiomicenhancedmultimodalultrasoundforearlydetectionofacutekidneyinjurysecondarytorenalveinthrombosisapreclinicaldiagnosticmodelingstudy AT xinghuawang radiomicenhancedmultimodalultrasoundforearlydetectionofacutekidneyinjurysecondarytorenalveinthrombosisapreclinicaldiagnosticmodelingstudy AT nanqiao radiomicenhancedmultimodalultrasoundforearlydetectionofacutekidneyinjurysecondarytorenalveinthrombosisapreclinicaldiagnosticmodelingstudy AT taozhang radiomicenhancedmultimodalultrasoundforearlydetectionofacutekidneyinjurysecondarytorenalveinthrombosisapreclinicaldiagnosticmodelingstudy |