Analysis of existing archives of lung CT images collected during the COVID-19 pandemic for malignant neoplasms (MN) and their characteristics, LUNG-RADS recommendations
The algorithm processes CT lung images, highlighting potentially dangerous areas and drawing the specialist's attention to nodular masses. If the AI "sees" a neoplasm 4 mm in size, it highlights all nodules on the image regardless of their size. The doctor then analyzes the images and makes a final decision.
How it works
How it works
1. The algorithm works with existing archives and retrospectively analyzes DICOM studies without contrast.
2. The images are processed by artificial intelligence, after processing the doctor receives images with the identification of potentially dangerous areas and text description of the study.
3. AI-confirmed cases are automatically sent to the MDDC Reference Center or to the regional oncological dispensary for verification by specialist physicians.
Mass screening of the population through the use of off-the-shelf CT scans
Increasing early detection of cancer
Saving the time and efforts of radiologists
Increasing the effectiveness of treatment through early detection
Reducing the burden on the patient using heavy diagnostic equipment
Increased diagnostic speed and accuracy
Karachay-Cherkessia Oncologic Dispensary named after S.P. Butov. S.P. Butov
Karachay-Cherkessia Republican Clinical Hospital
During the pandemic in the region the "CT Lung" service was integrated to detect COVID-19 on the images.
The CT images accumulated during the pandemic were further analyzed by artificial intelligence for cancer detection.
The retrospective analysis allowed mass screening of patients without additional CT scans.
The pilot project "Retrospective analysis of pulmonary CT scans" was conducted from 01.09.2021-18.09.2021 in the Karachay-Cherkess Republic.
~ 1 500
depersonalized images were analyzed for nodular neoplasms
patients in whom AI detected nodular neoplasms on archived images collected for COVID-19 detection
cases with detected neoplasms with confirmed signs of cancer
Nizhny Novgorod region
Analysis of all CT scans of the region,
to detect early signs of cancer.
The Medical Digital Diagnostic Center (MDDC) platform is directly connected to the Medical Information System (MIS) in Nizhny Novgorod Oblast.
The central archive of medical images receives lung CT scans taken in all medical institutions of the region. The data are automatically transferred to the MDDC platform and analyzed by the AI.
Regular online analysis of chest CT scans using AI. Every week the algorithm processes about 300 studies.
After verification by MDDC doctors, a report with detected cases of nodular neoplasms in the lungs is sent to the Nizhny Novgorod Oncological Dispensary.
Nizhny Novgorod region
Period from April to July 2022
MO Nizhny Novgorod Oncological Dispensary
images were analyzed for the presence of nodular neoplasms
cases of possible neoplasms were identified by AI and sent images for additional verification to MDDC doctors
Lung CT scans were sent to Nizhny Novgorod Oncologic Dispensary physicians for decision-making on further routing and further examination of patients
“The use of artificial intelligence technologies is one of the main trends in modern medicine. For example, during the COVID-19 pandemic in many regions of Russia, artificial intelligence was connected to revise CT studies of patients. However, no less important is the use of high technology in oncology. Algorithms reduce the time of medical data processing, freeing doctors from routine work. This is especially important for oncologists, because sometimes lives can be saved by timely diagnosis”
Zuber Makhov, M.D., is a senior freelance oncologist of Karachay-Cherkessia, and head doctor at the S.P. Butov Karachay-Cherkessia Oncology Center