Recent developments in MRI contrast agents give new perspectives in radiological diagnosis and therapy planning, but require specific image analysis methods. By employment of an academic research grid, we are currently validating and optimizing a recently developed fully automatic method for liver segmentation in Gd-EOB enhanced MRI. The grid enables extensive parameter scans and evaluation against expert's reference segmentation. The implementation layout and so far reached results are presented. Furthermore, experiences made in the production phase and consequences resulting for the exploitation of publicly funded research grids for Healthgrid applications are given.
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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 PDFMedicina (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 PDFDiagnostics (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 PDFDiagnostics (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 PDFUpdates 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.
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