• AI
  • Molecular Imaging
  • CT
  • X-Ray
  • Ultrasound
  • MRI
  • Facility Management
  • Mammography

Storing only postprocessed images reduces demands on PACS

Article

Huge data sets from the newer MR and CT scanners not only tax radiologists, they overburden a PACS as well. Researchers at Bundang Seoul National University Hospital in Korea have a solution: split the PACS and use smaller postprocessed data sets for

Huge data sets from the newer MR and CT scanners not only tax radiologists, they overburden a PACS as well. Researchers at Bundang Seoul National University Hospital in Korea have a solution: split the PACS and use smaller postprocessed data sets for most routine clinical work.

An institution performing 100 MDCT exams a day may generate 12 TB/year of data, resulting in $1 million in short-term storage costs alone. The constant avalanche of data can result in degraded system performance and frequent reinvestment in PACS expansion.

"Initial image data sets are stored in RawData PACS, then automatically routed to the relevant radiologist's postprocessing/analysis workstation," said RawData developer Dr. Kyoung Ho Lee, a clinical instructor in the Bundang diagnostic radiology department.

Under RawData PACS, only selected slices and postprocessed images are sent to the main PACS.

One of the main headaches in data storage is that source data from newer modalities are accessed by only a few users. Since source data are not for busy outpatient clinics, but only for image postprocessing and analysis, there is no need to keep the data in expensive short-term PACS storage for long periods of time. The extra data can be seen as troublesome by many clinicians who won't ever access it.

"Because initial image data sets are rarely retrieved, and only a few if any medical personnel access this data, a low-cost, small-capacity PACS can work effectively," Lee said.

The source data are permanently stored in the miniPACS, so the response time for data access is, effectively, zero. The fast access time enables postprocessing and analysis of every exam.

According to Lee, the RawData PACS technique can also be applied to other modality data sets, such as functional MR and contrast-enhanced ultrasound cine clips.

The RawData PACS frees the main PACS from the burden of handling data generated by the newest imaging techniques, avoiding unexpected and undesirable expansion of the entire PACS and leading to overall cost saving, Lee said.

"The cost-saving effect will also help in expanding application of the newest imaging techniques in daily practice," he said.

Recent Videos
Current and Emerging Insights on AI in Breast Imaging: An Interview with Mark Traill, Part 1
Addressing Cybersecurity Issues in Radiology
Computed Tomography Study Shows Emergence of Silicosis in Engineered Stone Countertop Workers
Can an Emerging AI Software for DBT Help Reduce Disparities in Breast Cancer Screening?
Skeletal Muscle Loss and Dementia: What Emerging MRI Research Reveals
Magnetoencephalopathy Study Suggests Link Between Concussions and Slower Aperiodic Activity in Adolescent Football Players
Radiology Study Finds Increasing Rates of Non-Physician Practitioner Image Interpretation in Office Settings
Assessing a Landmark Change in CMS Reimbursement for Diagnostic Radiopharmaceuticals
Addressing the Early Impact of National Breast Density Notification for Mammography Reports
2 KOLs are featured in this series.
Related Content
© 2024 MJH Life Sciences

All rights reserved.