Purpose: This study aimed to analyze the predictive value of caudate to right lobe ratio (CRL-R) and liver segmental volume ratio (LSVR) for chronic liver disease (CLD) on routine abdominal CT scans and their association with 5-year decompensation- and transplant-free survival.
Method: This retrospective study included 108 patients without CLD and 98 patients with biopsy-proven CLD. All patients underwent abdominal CT scans between 03/2015 and 08/2017. Patients with CLD were divided into three groups: early CLD (F0-F2; eCLD; n = 40), advanced CLD (F3-F4; aCLD; n = 20), and aCLD with clinically significant portal hypertension (aCLDPH; n = 38). CRL-R and LSVR were compared between groups using Kruskal-Wallis test and ROC analysis to determine cutoff-values. 5-year decompensation- and transplant-free survival were assessed by Kaplan-Meier curve analysis.
Results: CRL-R and LSVR were significantly different between all groups (p < 0.001). A CRL-R cutoff-value of > 0.99 predicted aCLD with a sensitivity of 69% and a specificity of 80% (AUC = 0.75, p < 0.001), while LSVR > 0.37 had a sensitivity of 67% and a specificity of 84% (AUC = 0.80, p < 0.001). CLD-patients with both CRL-R > 0.99 and LSVR > 0.37 had a significantly lower probability of 5-year decompensation-free survival (31%) as well as lower probability of 5-year transplant-free survival (41%) than those with a CRL-R < 0.99 and/or LSVR < 0.37 (70%, 62%, p = 0.006, p = 0.038).
Conclusion: CRL-R and LSVR showed a high predictive value for CLD on routine abdominal CT scans. In patients with CLD, both CRL-R and LSVR may be combined and are associated with 5-year decompensation-free and transplant-free survival.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/s00261-024-04552-w | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Diagnostic Challenges of Medullary Carcinoma of the Small Intestine During the COVID-19 Pandemic.
J Clin Med
January 2025
Department of Pharmacology, Faculty of Medicine, Wrocław Medical University, 50-345 Wrocław, Poland.
: Medullary carcinoma of the small intestine is an exceptionally rare subtype of gastrointestinal cancer, characterized by its solid growth pattern and lack of glandular structures, which complicate timely diagnosis. During the COVID-19 pandemic, diagnostic delays for rare cancers became increasingly common due to the prioritization of COVID-related cases and patient reluctance to seek medical attention. : We present the case of a 70-year-old male initially misdiagnosed with COVID-19, whose persistent symptoms led to the eventual discovery of medullary carcinoma.
View Article and Find Full Text PDFPostoperative Outcomes After Robotic Liver Resection of Caudate Lobe: A Systematic Review.
Medicina (Kaunas)
December 2024
Division of Hepato-Pancreato-Biliary, Oncologic and Robotic Surgery, Azienda Ospedaliero-Universitaria SS. Antonio e Biagio e Cesare Arrigo, 15121 Alessandria, Italy.
: Resection of the caudate lobe of the liver is considered a highly challenging surgical procedure due to the deep anatomic location of this segment and the relationships with major vessels. There is no clear evidence about the safety and effectiveness of robotic resection of the caudate lobe. The aim of this systematic review was to report data about the safety, technical feasibility, and postoperative outcomes of robotic caudate lobectomy.
View Article and Find Full Text PDFTransRAUNet: A Deep Neural Network with Reverse Attention Module Using HU Windowing Augmentation for Robust Liver Vessel Segmentation in Full Resolution of CT Images.
Diagnostics (Basel)
January 2025
Department of Medical Device and Healthcare, Dongguk University, Seoul 04620, Republic of Korea.
Liver cancer has a high mortality rate worldwide, and clinicians segment liver vessels in CT images before surgical procedures. However, liver vessels have a complex structure, and the segmentation process is conducted manually, so it is time-consuming and labor-intensive. Consequently, it would be extremely useful to develop a deep learning-based automatic liver vessel segmentation method.
View Article and Find Full Text PDFAdaptive Evolutionary Optimization of Deep Learning Architectures for Focused Liver Ultrasound Image Segmentation.
Diagnostics (Basel)
January 2025
Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA 92093, USA.
Liver ultrasound segmentation is challenging due to low image quality and variability. While deep learning (DL) models have been widely applied for medical segmentation, generic pre-configured models may not meet the specific requirements for targeted areas in liver ultrasound. Quantitative ultrasound (QUS) is emerging as a promising tool for liver fat measurement; however, accurately segmenting regions of interest within liver ultrasound images remains a challenge.
View Article and Find Full Text PDFComprehensive evaluation of the ramification patterns of hepatic vascular anatomy based on three-dimensional visualization technology.
Updates Surg
January 2025
Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Avenue, Wuhan, 1095, China.
The liver segmentation method proposed by Couinaud is widely accepted by surgeons because of its convenience and practicality. However, this conventional eight-segment classification does not reflect realistic details of the liver and thus requires further adjustments to promote improvements in surgical strategies. This study aimed to explore the ramification patterns of the hepatic vasculature comprehensively.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!