The goal of this clinical trial is to evaluate performance and clinical applicability of AI-assisted radiotherapy contouring software (iCurveE) for thoracic organs at risk. The main question it aims to answer is: • Does AI-assisted contouring (AI contouring with manual modification) offer greater accuracy and time efficiency compared to manual contouring? After screening, the qualified participants' thoracic CT images will be anonymized and segmented using three methods: manual, AI (AI-only), and AI-assisted contouring. The researchers will compare the results generated by the three different contouring methods with the ground truth established by expert consensus, in order to evaluate both accuracy and time-related parameters
Study Type
OBSERVATIONAL
Enrollment
500
Tianjin Medical University Cancer Institute and Hospital, Tianjin Key Laboratory of Cancer Prevention and Therapy
Tianjin, Tianjin Municipality, China
volumetric DICE similarity coefficient, vDSC
vDSC= 2×（A∩B）/(A+B), where A refers to the volume of the ground truth, and B refers to the volume of the manual, AI, or AI-assisted contour.
Time frame: Within 6 months after enrollment
Contouring time (min)
Manual contouring time is recorded from the time the CT is loaded on the contouring platform to the completion of contouring. AI-assisted contouring time is defined as the sum of the auto-segmentation model runtime, the transfer to the contouring platform, and the subsequent manual modification.
Time frame: Within 6 months after enrollment
95th percentile Hausdorff Distance, HD95
HD95(A, B) = max (h95(A, B), h95(B, A)), where h95(A, B) is the 95th percentile of the shortest distances from all points on surface A to surface B, and vice-versa for h95(B, A). A represents the ground truth and B represents the manual, AI or AI-assisted delineation
Time frame: Within 6 months after enrollment
Surface DICE similarity coefficient, sDSC
sDSC = (\|S(A) ∩ S(B)τ\| + \|S(B) ∩ S(A)τ\|) / (\|S(A)\| + \|S(B)\|), where S(A) and S(B) are the sets of points on the surfaces of A and B, S(B)τ represents the points on surface B that are within the tolerance τ of surface A, and S(A)τ represents the points on surface A that are within the tolerance τ of surface B. A represents the ground truth and B represents the manual, AI or AI-assisted delineation
Time frame: Within 6 months after enrollment
Rate of time efficiency improvement
Rate of efficiency time improvement= (manual contouring duration - AI-assisted contouring duration)/ manual contouring duration\*100%
Time frame: Within 6 months after enrollment
Volumetric revision index, VRI
VRI = \[(A- A∩B) + (B- A∩B)\] /A, where A refers to the volume of the ground truth, and B refers to the volume of the manual, AI, or AI-assisted contour.
Time frame: Within 6 months after enrollment
Recall, Rec
Rec = \| A∩B\| / A, where A refers to the volume of the ground truth, and B refers to the volume of the manual, AI, or AI-assisted contour.
Time frame: Within 6 months after enrollment
Precision, Pre
Pre= \|A∩B\| / B, where A refers to the volume of the ground truth, and B refers to the volume of manual, AI, or AI-assisted contour.
Time frame: Within 6 months after enrollment
Relative volume difference, RVD
RVD = \|A-B\| /A, where A refers to the volume of the ground truth, and B refers to the volume of the manual, AI, or AI-assisted contour.
Time frame: Within 6 months after enrollment
Investigators satisfaction score for AI contouring
Evaluated on a 1-5 Likert scale: 1 - strongly dissatisfied, 2 - dissatisfied, 3 - neutral, 4 - satisfied, 5 - strongly satisfied.
Time frame: Within 6 months after enrollment
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.