We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




Pioneering Digital Pathology Solution Adopted by a University Hospital in The Netherlands

By MedImaging International staff writers
Posted on 06 Jul 2015
Print article
A university hospital in the Netherlands has become one of the first such hospitals in the world to fully digitize its pathology department.

The solution significantly increases the efficiency of the pathology workflow by enabling pathologists to review primary diagnostics cases digitally, and also improves collaboration between radiologists and pathologists, leading to more efficient care of cancer patients.

The digital pathology solution was provided by Sectra (Linköping, Sweden) and implemented by the University Medical Center Utrecht (UMCU; Utrecht, Netherlands), and enables the hospital to store, view and share digital pathology images.

The digital pathology solution uses the same platform as Sectra’s radiology Picture Archiving and Communication System (PACS), a system that the UMCU has been using for ten years to store and manage radiology images. Cancer diagnosis and treatment both depend on the collective findings from pathology and radiology. Treating clinicians, surgeons, and oncologists, also require access to sufficient clinical data to be able to create useful and accurate reports. The common integrated PACS/pathology platform allows clinicians from the two specialties to collaborate, and share images, improving the speed and accuracy of diagnosis.

Paul van Diest, head of the UMCU pathology department, said, “By reviewing tissue and cells digitally, our workflow will become more efficient. We are no longer tied to that one workplace: the microscope. We can request the opinion of expert colleagues much more easily and can review cases faster when a patient is referred. With the use of computer technology, the pathologist has assistance in interpreting images, making the overall quality of diagnosis more reliable.”

Related Links:

Sectra
University Medical Center Utrecht 


New
Gold Member
X-Ray QA Meter
T3 AD Pro
Portable X-ray Unit
AJEX130HN
NMUS & MSK Ultrasound
InVisus Pro
Ultrasound Color LCD
U156W

Print article
Radcal

Channels

Radiography

view channel
Image: The new X-ray detector produces a high-quality radiograph (Photo courtesy of ACS Central Science 2024, DOI: https://doi.org/10.1021/acscentsci.4c01296)

Highly Sensitive, Foldable Detector to Make X-Rays Safer

X-rays are widely used in diagnostic testing and industrial monitoring, from dental checkups to airport luggage scans. However, these high-energy rays emit ionizing radiation, which can pose risks after... Read more

MRI

view channel
Image: Artificial intelligence models can be trained to distinguish brain tumors from healthy tissue (Photo courtesy of 123RF)

AI Can Distinguish Brain Tumors from Healthy Tissue

Researchers have made significant advancements in artificial intelligence (AI) for medical applications. AI holds particular promise in radiology, where delays in processing medical images can often postpone... Read more

Nuclear Medicine

view channel
Image: Example of AI analysis of PET/CT images (Photo courtesy of Academic Radiology; DOI: 10.1016/j.acra.2024.08.043)

AI Analysis of PET/CT Images Predicts Side Effects of Immunotherapy in Lung Cancer

Immunotherapy has significantly advanced the treatment of primary lung cancer, but it can sometimes lead to a severe side effect known as interstitial lung disease. This condition is characterized by lung... Read more

General/Advanced Imaging

view channel
Image: Cleerly offers an AI-enabled CCTA solution for personalized, precise and measurable assessment of plaque, stenosis and ischemia (Photo courtesy of Cleerly)

AI-Enabled Plaque Assessments Help Cardiologists Identify High-Risk CAD Patients

Groundbreaking research has shown that a non-invasive, artificial intelligence (AI)-based analysis of cardiac computed tomography (CT) can predict severe heart-related events in patients exhibiting symptoms... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.