The AI-powered qCT LN Quant software reportedly generates 2D and 3D reconstructions and facilitates assessment of morphologic data across multiple thoracic studies.
Offering advanced quantitative evaluation of solid lung nodules, the artificial intelligence (AI)-powered software qCT LN Quant has garnered 510(k) clearance from the Food and Drug Administration (FDA).
In addition to providing short-axis, long-axis and average diameter measurements of lung nodules, the qCT LN Quant software enables radiologists to determine estimated volume doubling time and assess nodule tracking for multiple thoracic studies, according to Qure.ai, the developer of qCT LN Quant.
The newly FDA-cleared qCT LN Quant software enables radiologists to determine estimated volume doubling time and assess nodule tracking for multiple thoracic studies, according to Qure.ai, the developer of qCT LN Quant. (Image courtesy of Qure.ai.)
The company also points out that qCT LN Quant provides Brock malignancy risk scoring, 2D and 3D image reconstructions and management suggestions based on Fleischner Society guidelines.
“(qCT LN Quant is) the next stage solution in the AI-optimized patient pathway to evaluate lung nodules on at-risk patient CT scans, giving precise quantitative characterization, plus tracking volumetric growth over time,” noted Bhargava Reddy, the chief business officer of oncology at Qure.ai.
In regard to reimbursement for use of qCT LN Quant, Qure.ai said the software is “potentially eligible” for the 3D reconstruction CPT code as well as the CPT 0722T code for tissue quantification.
Photon-Counting Computed Tomography: Eleven Takeaways from a New Literature Review
May 27th 2025In a review of 155 studies, researchers examined the capabilities of photon-counting computed tomography (PCCT) for enhanced accuracy, tissue characterization, artifact reduction and reduced radiation dosing across thoracic, abdominal, and cardiothoracic imaging applications.
Emerging AI Mammography Model May Enhance Clarity for Initial BI-RADS 3 and 4 Classifications
May 21st 2025In a study involving over 12,000 Asian women, researchers found that an artificial intelligence (AI) model converted over 83 percent of false positives in patients with initial BI-RADS 3 and 4 assessments into benign BI-RADS categories.
CT Perfusion Study Shows Enhanced Detection of Medium Vessel Occlusions with Emerging AI Software
May 21st 2025The Rapid CTP AI software offered 23 percent greater detection of medium vessel occlusions in comparison to the Viz CTP AI software, according to research presented at the European Stroke (Organization) Conference (ESOC).