Application of CT-Linac-Based "All-in-One" One-Stop Radiotherapy in Breast Cancer
Application of CT-Linac-Based "All-in-One" One-Stop Radiotherapy in All-Scenario Breast Cancer Radiotherapy: A Prospective Clinical Study
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Contact
Study Contact
- Name: Xiaoli Yu, MD, PhD
- Phone Number: +86-021-64175590
- Email: xiaoliyu@fudan.edu.cn
Study Contact Backup
- Name: Xiaofang Wang, MD, PhD
- Phone Number: +86 18017317247
- Email: xiaofang0708@yeah.net
Study Locations
-
-
Shanghai Municipality
-
Shanghai, Shanghai Municipality, China, 200032
- Recruiting
- Fudan University Shanghai Cancer Center
-
Contact:
- Xiaofang Wang Wang
- Phone Number: +86 18017317247
- Email: xiaofang0708@yeah.net
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Histologically or pathologically confirmed breast cancer with definitive indications for radiotherapy (preoperative, postoperative, or radical)
- ECOG performance status of 0-2
- Able to remain still and supine on the treatment couch for up to 30 minutes
- Provision of signed, written informed consent
- Able to comply with daily follow-ups and blood sample collections
Exclusion Criteria:
- Palliative radiotherapy for concurrent distant metastasis
- Incomplete or ongoing chemotherapy
- Synchronous multiple primary tumors
- Current pregnancy or lactation
- Prior history of radiotherapy to the ipsilateral breast, chest wall, thorax, or regional lymph nodes
- Severe non-malignant comorbidities (e.g., cardiovascular or pulmonary diseases, systemic lupus erythematosus, scleroderma) resulting in a short life expectancy or inability to tolerate radical radiotherapy
- Inability or unlikelihood to comply with study follow-up
- Inability or unwillingness to provide written informed consent
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Other
- Allocation: Non-Randomized
- Interventional Model: Sequential Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Other: ARM1: AI-empowered AIO WBI
Evaluates the feasibility, safety, and patient experiences of the AI-empowered AIO workflow in breast cancer patients undergoing whole-breast irradiation (WBI) without regional nodal involvement.
|
The workflow relies on specialized convolutional neural networks for automated segmentation and dose-prediction auto-planning.
These breast cancer models were trained on 285 historical institutional cases spanning radical mastectomy and breast-conserving surgery over five years.
Auto-delineated structures include the clinical target volume, regional lymph nodes (if involved), tumor bed (identified by surgical clips), heart, bilateral lungs, unaffected breast, spinal cord, esophagus, thyroid, and affected humeral head.
These contours guide dose prediction to generate deliverable tangential arc plans via clinical-goal-guided automated optimization in the treatment planning system.
To adapt to the on-couch treatment scenario, models were validated on retrospective data and offline routines to maximize target delineation accuracy and the first-approval rate of auto-plans.
|
|
Other: ARM2: Expanded-Scenario AIO RT
Evaluates the feasibility, safety, and patient experiences of the AI-empowered AIO workflow in breast cancer patients with broader radiotherapy indications, including breast/chest wall irradiation with or without regional nodal radiotherapy.
|
The workflow relies on specialized convolutional neural networks for automated segmentation and dose-prediction auto-planning.
These breast cancer models were trained on 285 historical institutional cases spanning radical mastectomy and breast-conserving surgery over five years.
Auto-delineated structures include the clinical target volume, regional lymph nodes (if involved), tumor bed (identified by surgical clips), heart, bilateral lungs, unaffected breast, spinal cord, esophagus, thyroid, and affected humeral head.
These contours guide dose prediction to generate deliverable tangential arc plans via clinical-goal-guided automated optimization in the treatment planning system.
To adapt to the on-couch treatment scenario, models were validated on retrospective data and offline routines to maximize target delineation accuracy and the first-approval rate of auto-plans.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Acute adverse events
Time Frame: 6 months
|
The incidence and severity of acute adverse event include radiation dermatitis, pruritus, skin pain, radiation esophagitis, and radiation pneumonitis.
|
6 months
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Accuracy
Time Frame: 2 months
|
Auto-segmentation accuracy was assessed by comparing automatically generated contours against the final physician-approved contours
|
2 months
|
|
Success rate
Time Frame: 2 months
|
Record AIO workflow success rate: online planning one-pass optimization success rate.
|
2 months
|
|
Quality of life (QoL)
Time Frame: 6 months
|
Quality of life will be evaluated via standardized QoL scales.
|
6 months
|
|
Time efficiency
Time Frame: 2 months
|
The time efficiency of the workflow was automatically recorded by the system
|
2 months
|
|
Full-Workflow Patient Intrafraction Motion
Time Frame: 2 months
|
Evaluated based on geometric deviations between pretreatment image-guided radiotherapy (IGRT), posttreatment imaging, and the baseline simulation CT
|
2 months
|
|
Correlation of Patient Metrology with Setup Error and Dosimetric Performance
Time Frame: 2 months
|
Evaluation of how Body Mass Index (BMI) and weight fluctuations correlate with geometric setup errors and in vivo gamma pass rates
|
2 months
|
|
Correlation of Anatomical Scale with Setup Error and Dosimetric Performance
Time Frame: 2 months
|
Evaluation of how anatomical scale/breast size correlates with geometric setup errors and in vivo gamma pass rates
|
2 months
|
Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- FDRT-BC029
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Sharing Supporting Information Type
- STUDY_PROTOCOL
- ICF
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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