- AI
- Molecular Imaging
- CT
- X-Ray
- Ultrasound
- MRI
- Facility Management
- Mammography
FDA Grants 510(k) Clearance for AI Detection and Triage of Cervical Spine Fractures
The CINA-CSpine AI software reportedly demonstrated a 90.3 percent sensitivity rate for cervical spine fractures in validation testing on more than 300 non-contrast CT scans.
The CINA-CSpine artificial intelligence (AI) software has garnered 510(k) clearance from the Food and Drug Administration (FDA) for the detection and triage of cervical spine fractures on computed tomography (CT) scans.
Facilitating timely treatment of cervical spine fractures, the CINA-CSpine software provides automated flagging of suspected acute fractures and subsequent alerts to reviewing radiologists, according to Avicenna.AI, the developer of the software.
In validation testing involving over 300 CT scans acquired from 36 scanner models and five different vendors, the company said the newly FDA-cleared CINA-CSpine software demonstrated a 90.3 percent sensitivity for cervical spine fractures. (Photo courtesy of Avicenna.AI .)
In validation testing involving over 300 CT scans acquired from 36 scanner models and five different vendors, the company said the CINA-CSpine software demonstrated a 90.3 percent sensitivity rate and a 91.9 percent specificity rate for cervical spine fractures.
"These results demonstrate that our CINA-CSpine algorithm is capable of providing prompt and accurate findings that could positively guide physicians towards better assessments and improved patient outcomes," added Cyril Di Grandi, the co-founder and chief executive officer of Avicenna.ai.
New CT and MRI Research Shows Link Between LR-M Lesions and Rapid Progression of Early-Stage HCC
January 2nd 2025Seventy percent of LR-M hepatocellular carcinoma (HCC) cases were associated with rapid growth in comparison to 12.5 percent of LR-4 HCCs and 28.5 percent of LR-4 HCCs, according to a new study.
Study Examines Impact of Deep Learning on Fast MRI Protocols for Knee Pain
December 17th 2024Ten-minute and five-minute knee MRI exams with compressed sequences facilitated by deep learning offered nearly equivalent sensitivity and specificity as an 18-minute conventional MRI knee exam, according to research presented recently at the RSNA conference.
Mammography Study Suggests DBT-Based AI May Help Reduce Disparities with Breast Cancer Screening
December 13th 2024New research suggests that AI-powered assessment of digital breast tomosynthesis (DBT) for short-term breast cancer risk may help address racial disparities with detection and shortcomings of traditional mammography in women with dense breasts.
Can AI Facilitate Single-Phase CT Acquisition for COPD Diagnosis and Staging?
December 12th 2024The authors of a new study found that deep learning assessment of single-phase CT scans provides comparable within-one stage accuracies to multiphase CT for detecting and staging chronic obstructive pulmonary disease (COPD).
