DCR Identifies Pleural Invasion of Lung Tumors
|
By MedImaging International staff writers Posted on 15 Feb 2021 |

Image: Examples of DCR images (Photo courtesy of Rie Tanaka/ Kanazawa University)
Dynamic chest radiography (DCR) holds promise for assessment of tumor invasion and adhesion in the parietal pleura, according to a new study.
Researchers at Kanazawa University (Japan), Duke University (Durham NC, USA), and Yokohama City University (Japan) conducted a proof-of-concept study to investigate the feasibility of preoperative evaluation of pleural invasion/adhesion of lung tumors with DCR, using a four‐dimensional (4D) extended cardiac‐torso (XCAT) computational phantom with simulated respiratory and cardiac motions; to simulate lung tumors, a 30‐mm diameter sphere was inserted into each lobe of the phantom.
The virtual patient during respiration was virtually projected using an X‐ray simulator in posteroanterior (PA) and oblique directions, and sequential bone suppression (BS) images were created. Measurement points (tumor, rib, and diaphragm) were automatically tracked on the simulated images by a template matching technique. The researchers then calculated five quantitative metrics related to the movement distance and directions of the targeted tumor, and evaluated whether DCR could distinguish between tumors with and without pleural invasion/adhesion.
The results showed precise tracking of the targeted tumor, without undue influence of rib shadows. There was a significant difference in all five quantitative metrics between the lung tumors with and without pleural invasion. Metrics related to movement distance were effective for tumors in the middle and lower lobes, while those related to movement directions were effective for tumors close to the frontal chest wall on the oblique projection view. The oblique views were useful for the evaluation of the space between the chest wall and a moving tumor. The study was published on February 3, 2021, in Medical Physics.
“Imaging modalities like cine MRI or breathing chest CT can be used to assess tumor invasion and adhesion, but both are more costly than x-ray; MRI often isn't available, while CT carries a higher radiation burden than radiography,” said lead author Rie Tanaka, PhD, of Kanazawa University. “With DCR, a series of sequential chest radiographs are obtained of a standing patient through a 10-second respiratory cycle. Except for the breathing pattern, images are acquired in the same manner as a conventional radiograph.”
Preoperative assessment of tumor invasion and adhesion is imperative when planning surgical excision of lung tumors. If the tumor moves independent of parietal or mediastinal pleura, it means that it is not invasive or strongly adheres to lung tissue, and therefore may be easier to remove surgically.
Related Links:
Kanazawa University
Duke University
Yokohama City University
Researchers at Kanazawa University (Japan), Duke University (Durham NC, USA), and Yokohama City University (Japan) conducted a proof-of-concept study to investigate the feasibility of preoperative evaluation of pleural invasion/adhesion of lung tumors with DCR, using a four‐dimensional (4D) extended cardiac‐torso (XCAT) computational phantom with simulated respiratory and cardiac motions; to simulate lung tumors, a 30‐mm diameter sphere was inserted into each lobe of the phantom.
The virtual patient during respiration was virtually projected using an X‐ray simulator in posteroanterior (PA) and oblique directions, and sequential bone suppression (BS) images were created. Measurement points (tumor, rib, and diaphragm) were automatically tracked on the simulated images by a template matching technique. The researchers then calculated five quantitative metrics related to the movement distance and directions of the targeted tumor, and evaluated whether DCR could distinguish between tumors with and without pleural invasion/adhesion.
The results showed precise tracking of the targeted tumor, without undue influence of rib shadows. There was a significant difference in all five quantitative metrics between the lung tumors with and without pleural invasion. Metrics related to movement distance were effective for tumors in the middle and lower lobes, while those related to movement directions were effective for tumors close to the frontal chest wall on the oblique projection view. The oblique views were useful for the evaluation of the space between the chest wall and a moving tumor. The study was published on February 3, 2021, in Medical Physics.
“Imaging modalities like cine MRI or breathing chest CT can be used to assess tumor invasion and adhesion, but both are more costly than x-ray; MRI often isn't available, while CT carries a higher radiation burden than radiography,” said lead author Rie Tanaka, PhD, of Kanazawa University. “With DCR, a series of sequential chest radiographs are obtained of a standing patient through a 10-second respiratory cycle. Except for the breathing pattern, images are acquired in the same manner as a conventional radiograph.”
Preoperative assessment of tumor invasion and adhesion is imperative when planning surgical excision of lung tumors. If the tumor moves independent of parietal or mediastinal pleura, it means that it is not invasive or strongly adheres to lung tissue, and therefore may be easier to remove surgically.
Related Links:
Kanazawa University
Duke University
Yokohama City University
Latest Radiography News
- Routine Mammograms Could Predict Future Cardiovascular Disease in Women
- AI Detects Early Signs of Aging from Chest X-Rays
- X-Ray Breakthrough Captures Three Image-Contrast Types in Single Shot
- AI Generates Future Knee X-Rays to Predict Osteoarthritis Progression Risk
- AI Algorithm Uses Mammograms to Accurately Predict Cardiovascular Risk in Women
- AI Hybrid Strategy Improves Mammogram Interpretation
- AI Technology Predicts Personalized Five-Year Risk of Developing Breast Cancer
- RSNA AI Challenge Models Can Independently Interpret Mammograms
- New Technique Combines X-Ray Imaging and Radar for Safer Cancer Diagnosis
- New AI Tool Helps Doctors Read Chest X‑Rays Better
- Wearable X-Ray Imaging Detecting Fabric to Provide On-The-Go Diagnostic Scanning
- AI Helps Radiologists Spot More Lesions in Mammograms
- AI Detects Fatty Liver Disease from Chest X-Rays
- AI Detects Hidden Heart Disease in Existing CT Chest Scans
- Ultra-Lightweight AI Model Runs Without GPU to Break Barriers in Lung Cancer Diagnosis
- AI Radiology Tool Identifies Life-Threatening Conditions in Milliseconds
Channels
MRI
view channel
AI Model Reads and Diagnoses Brain MRI in Seconds
Brain MRI scans are critical for diagnosing strokes, hemorrhages, and other neurological disorders, but interpreting them can take hours or even days due to growing demand and limited specialist availability.... Read moreMRI Scan Breakthrough to Help Avoid Risky Invasive Tests for Heart Patients
Heart failure patients often require right heart catheterization to assess how severely their heart is struggling to pump blood, a procedure that involves inserting a tube into the heart to measure blood... Read more
MRI Scans Reveal Signature Patterns of Brain Activity to Predict Recovery from TBI
Recovery after traumatic brain injury (TBI) varies widely, with some patients regaining full function while others are left with lasting disabilities. Prognosis is especially difficult to assess in patients... Read moreUltrasound
view channel
AI Model Accurately Detects Placenta Accreta in Pregnancy Before Delivery
Placenta accreta spectrum (PAS) is a life-threatening pregnancy complication in which the placenta abnormally attaches to the uterine wall. The condition is a leading cause of maternal mortality and morbidity... Read more
Portable Ultrasound Sensor to Enable Earlier Breast Cancer Detection
Breast cancer screening relies heavily on annual mammograms, but aggressive tumors can develop between scans, accounting for up to 30 percent of cases. These interval cancers are often diagnosed later,... Read more
Portable Imaging Scanner to Diagnose Lymphatic Disease in Real Time
Lymphatic disorders affect hundreds of millions of people worldwide and are linked to conditions ranging from limb swelling and organ dysfunction to birth defects and cancer-related complications.... Read more
Imaging Technique Generates Simultaneous 3D Color Images of Soft-Tissue Structure and Vasculature
Medical imaging tools often force clinicians to choose between speed, structural detail, and functional insight. Ultrasound is fast and affordable but typically limited to two-dimensional anatomy, while... Read moreNuclear Medicine
view channel
Radiopharmaceutical Molecule Marker to Improve Choice of Bladder Cancer Therapies
Targeted cancer therapies only work when tumor cells express the specific molecular structures they are designed to attack. In urothelial carcinoma, a common form of bladder cancer, the cell surface protein... Read more
Cancer “Flashlight” Shows Who Can Benefit from Targeted Treatments
Targeted cancer therapies can be highly effective, but only when a patient’s tumor expresses the specific protein the treatment is designed to attack. Determining this usually requires biopsies or advanced... Read moreGeneral/Advanced Imaging
view channel
AI Tool Offers Prognosis for Patients with Head and Neck Cancer
Oropharyngeal cancer is a form of head and neck cancer that can spread through lymph nodes, significantly affecting survival and treatment decisions. Current therapies often involve combinations of surgery,... Read more
New 3D Imaging System Addresses MRI, CT and Ultrasound Limitations
Medical imaging is central to diagnosing and managing injuries, cancer, infections, and chronic diseases, yet existing tools each come with trade-offs. Ultrasound, X-ray, CT, and MRI can be costly, time-consuming,... Read moreImaging IT
view channel
New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible
Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology
The global artificial intelligence (AI) in medical diagnostics market is expanding with early disease detection being one of its key applications and image recognition becoming a compelling consumer proposition... Read moreIndustry News
view channel
Nuclear Medicine Set for Continued Growth Driven by Demand for Precision Diagnostics
Clinical imaging services face rising demand for precise molecular diagnostics and targeted radiopharmaceutical therapy as cancer and chronic disease rates climb. A new market analysis projects rapid expansion... Read more







