Lunit INSIGHT DBT (V1.2)
K253796Lunit, Inc. · cleared 2026-03-26 · product code QDQ · Radiology
Premarket evidence — what FDA accepted
source quote (p.6)
“Lunit INSIGHT DBT is a computer-assisted detection/diagnosis (CADe/x) Software as a Medical Device that provides information about the presence, location and characteristics of lesions suspicious for breast cancer to assist interpreting physicians in making diagnostic decisions when reading digital breast tomosynthesis (DBT) images.”
source quote (p.6)
“The software automatically analyzes digital breast tomosynthesis slices via artificial intelligence technology that has been trained via deep learning.”
Validation studies (2)
Standalone
n=3,277 cases
endpoints: demonstrate that the lower bound of 95% CI of device’s ROC AUC in standalone performance was greater than 0.903 and p-value was less than the significance level of 5% (0.05); JAFROC AUC; Sensitivity at the default operating point (0.1); specificity; Sensitivity at the supplementary ‘0.3’ operating point; specificity at the supplementary ‘0.3’ operating point; Sensitivity at the supplementary ‘0.6’ point; specificity at the supplementary ‘0.6’ point; lesion type agreement analysis
standards: IEC 62304: 2006/A1: 2016, IEC 62366-1:2015+AMD1:2020
Reader study (MRMC)
n=258 cases
endpoints: AI standalone AUROC compared with the average radiologist using the Obuchowski–Rockette (OR) method; AI standalone sensitivity at the highest threshold (Score 60); AI standalone specificity at this threshold
Reported performance (9 observations)
source quote (p.9)
“Sensitivity at the default operating point (0.1) was 91.11% (95% CI: 89.66, 92.57) and specificity was 77.62% (95% CI: 75.70, 79.54), respectively.”
source quote (p.9)
“Sensitivity at the default operating point (0.1) was 91.11% (95% CI: 89.66, 92.57) and specificity was 77.62% (95% CI: 75.70, 79.54), respectively.”
source quote (p.9)
“ROC AUC in the standalone performance analysis was 0.9388 (95% CI: 0.9304, 0.9472) with statistical significance (p < 0.05).”
source quote (p.9)
“For the secondary endpoints, the result of the JAFROC AUC was 0.9206 (95% CI: 0.9117, 0.9295).”
source quote (p.9)
“Sensitivity at the supplementary ‘0.3’ operating point was 88.38% (95% CI: 86.74, 90.02) and specificity was 83.68% (95% CI: 81.98, 85.38), respectively.”
source quote (p.9)
“Sensitivity at the supplementary ‘0.3’ operating point was 88.38% (95% CI: 86.74, 90.02) and specificity was 83.68% (95% CI: 81.98, 85.38), respectively.”
source quote (p.9)
“Sensitivity at the supplementary ‘0.6’ point was 81.48% (95% CI: 79.49, 83.47) and specificity was 93.44% (95% CI: 92.30, 94.58), respectively.”
source quote (p.9)
“Sensitivity at the supplementary ‘0.6’ point was 81.48% (95% CI: 79.49, 83.47) and specificity was 93.44% (95% CI: 92.30, 94.58), respectively.”
source quote (p.9)
“For lesion type agreement analysis, the matching proportion of the agreement between CAD and ground truther in 3-way classification of lesion type agreement was 75.61% (95% CI: 73.40, 77.80).”
Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.
Predicate network
Postmarket — what happened after clearance
Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device). Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.
Reimbursement — how devices like this got paid
Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).