October 16 2022
2 minutes to read
Source / Disclosures
Madsen K et al. Original investigations: new aids in diagnosing lung cancer: rules and robotics. Presented at: CHEST Annual Meeting; 16-19 October 2022; Nashville, Tennessee.
Styrvoky does not report any relevant financial disclosures.
NASHVILLE, TN – Shape-sensing robot-assisted bronchoscopy with cone computed tomography (CT) has shown promise in diagnosing central, distal, and peripheral pulmonary lesions in a single-center study presented at the Annual Chest Meeting.
“Shape-sensing robot-assisted bronchoscopy combined with advanced imaging techniques such as cone CT is a new approach that allows us to diagnose and stage lung cancer in a single procedure with high diagnostic accuracy and an excellent safety profile. It has the potential to become the standard of care for the diagnosis of pulmonary lesions if We have more studies confirming these findings,” Kim Stefocki, MD, An assistant professor of medicine at the University of Texas Southwestern Medical Center, told Healio.
Styrvoky and colleagues report the results of a retrospective analysis of the first 200 biopsy procedures of 209 lung lesions assessed using robot-assisted bronchoscopy (Ion, Intuitive) and cone CT scans at UT Southwestern from December 2020 to February 2022.
Often, patients with suspicious lung lesions undergo a non-surgical biopsy before definitive treatment; This can be with interventional radiology with CT-guided biopsies or endoscopic biopsies. The goal of bronchoscopy is that if we are able to diagnose these pulmonary nodules and perform mediastinal staging in a single procedure that would allow patients not to repeat procedures with risks of further complications or delaying their care. Current bronchoscopy techniques for biopsy of lung lesions are limited. There have been recent advances in this area in an effort to improve this diagnostic yield.”
Shape-sensing robot-assisted bronchoscopy is a newer technology that features a maneuverable catheter that allows for more precise guidance and direct visualization while navigating the airways. It enables active automated control of the catheter on the go and the biopsy process, according to Styrvoky. Combined with a real-time CT scan, this allows the doctor to confirm whether the catheter and lesion are well positioned.
“We hope that together, these two technologies will produce a better diagnosis,” Styrvoky said.
The results of the first 200 procedures to sample 209 lesions in 198 patients were as follows:
- Lesions ranged from 7 mm to 73 mm and the mean diameter of the largest lesion was 22.6 mm;
- The overall prevalence of malignancies was 64.1%, mostly lung cancer but also including metastatic disease from other primaries;
- The non-diagnostic sampling rate was 11% (23 of 209 samples);
- Diagnostic accuracy was 91.4%;
- The sensitivity was 87.3% and the specificity was 98.7%. And the
- The negative predictive value was 81.3% and the positive predictive value was 99.2%.
It’s worth noting, “We didn’t just look at nodules; we biopsied solid lesions, ground vitreous lesions, infiltrates, mass-like opacities—anything that really needed targeted sampling that we’ve included in this study, and it’s similar to what people would do in real practice. It is not restricted to a particular population,” Stefocki said.
The procedure resulted in a lower risk of complications. According to the results, only two patients developed pneumothorax and there were no major bleeding events.
“In addition to lung cancer, this technology also has the potential to be used in non-malignant operations,” Stefocki said. “Ultimately, I think this technology can be used as a safe way to get targeted samples into the lungs.”
The researchers plan to continue the future evaluation of shape-sensing robot-assisted bronchoscopy using cone CT scans to assess outcomes, factors that improve diagnostic accuracy, reduce radiation exposure, and ultimately fine-tune the procedure to make it as effective and safe for patients as possible, says Styrvoky.
This study is presented at Novel Aids in Lung Cancer Diagnostics: Rules and Robots session on Monday, October 17, at 1:30 p.m.
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