Health Condition 1: D499- Neoplasm of unspecified behavior of unspecified site
Conditions
Interventions
Intervention1: Deep Learning based Radiotherapy Autosegmentation: In this study, the DRAW autosegmentation system will be used to delineate structures on the planning CT scans of patients planned for
Sponsors
Tata Medical Center
Eligibility
Inclusion criteria
Inclusion criteria: The target population is patients with cancer being treated with radiotherapy for whom automatic segmentation models are available in the DRAW system. Currently this includes: 1. CNS malignancies 2. Breast cancers 3. Head Neck cancers 4. Lung cancers 5. Esophageal cancers 6. Prostate cancers 7. Gynecological cancers 8. Rectal cancers
Exclusion criteria
Exclusion criteria: Model not available for the cancer site for automatic segmentation
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Qualitative Validation: Number of cases where no or minor modifications were required.Timepoint: 24 months | — |
Secondary
| Measure | Time frame |
|---|---|
| Time taken for modification: The estimated time required for making the modifications required for the cases after automatic segmentation will be reported.Timepoint: 24 months;Quantitative Validation: Average volumetric dice similarity between the autosegmented contours and the manually segmented structure sets. This will be compared against the reference VDS value.Timepoint: 24 months | — |
Countries
India
Contacts
Public ContactSantam Chakraborty
Tata Medical Center
Outcome results
None listed