Randomized Evaluation of Machine Learning Assisted Radiation Treatment Planning vs Standard Radiation Treatment Planning

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ACTIVE_NOT_RECRUITING

Clinical Phase

NA

Total Enrollment

204 participants

Study Classification

INTERVENTIONAL

Study Start Date

2023-08-07

Study Completion Date

2025-12-16

Brief Summary

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The purpose of this study is to determine the magnitude of clinical benefit achieved through machine learning assisted radiation treatment planning (MLAP) on post-treatment clinical outcomes such as acute toxicity and patient reported outcomes.

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Detailed Description

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This is a randomized phase III trial to evaluate the effectiveness of MLAP compared to Standard of Care. Patients will undergo a randomization procedure with a variable allocation ratio where the first third of patients are randomized 3:1 in favor of SOC, the next third randomized 1:1, and the last third randomized 1:3 in favor of MLAP. This is done to give dosimetrists time to optimize the MLAP workflow. Since the treatment team may learn to improve their treatment planning process in the SOC arm through interactions with RapidPlan, as a sensitivity analysis, the primary and secondary goals will be re-analyzed including time of registration as a moderator of the treatment effect.

Conditions

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Cancer Head Neck Cancer, Head Cancer Neck

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

SINGLE_GROUP

Primary Study Purpose

TREATMENT

Blinding Strategy

NONE

Study Groups

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Arm A: Standard of care (SOC) treatment planning

Patients randomized to the SOC treatment planning arm will receive a treatment planning computed tomography (CT) scan followed by dosimetric planning with a medical dosimetrist; and the plan will be reviewed by a medical physicist and radiation oncologist. This is the current standard practice for all radiation oncology patients.

Group Type OTHER

Radiation Therapy Standard of Care (SOC)

Intervention Type RADIATION

Radiation therapy simulation, target delineation, dosing, localization, and follow-up will be followed per standard of care practices and/or at the discretion of the treating radiation oncologist. To elaborate, patients will receive a treatment planning CT (computed tomography) scan, followed by normal tissue delineation through the physician and/or medical dosimetry assistant, followed by target delineation by the physician, followed by radiation treatment planning with the dosimetrist and medical physicist, followed by plan change requests and approval by the physician.

Arm B: Machine Learning Assisted Planning (MLAP)

Patients randomized to the MLAP arm will receive a treatment planning scan followed by MLAP through the RapidPlan module produced by Varian. Of note, RapidPlan is an FDA cleared module with treatment planning being the approved usage for the program. The RapidPlan module has site specific treatment packages for different disease sites. These separate disease specific packages have different capabilities. For example, the Head and Neck package currently audits dosimetrist-generated plans for possible improvements. The MLAP arm of the trial will leverage the RapidPlan module's full capabilities upwards to the FDA-approved usage.

Group Type ACTIVE_COMPARATOR

Machine Learning Assisted Radiation (MLAP) RapidPlan

Intervention Type RADIATION

Radiation therapy simulation, target delineation, dosing, localization, and follow-up will be followed per standard of care practices and/or at the discretion of the treating radiation oncologist. To elaborate, patients will receive a treatment planning CT (computed tomography) scan, followed by normal tissue delineation through the physician and/or medical dosimetry assistant, followed by target delineation by the physician, followed by radiation treatment planning with the dosimetrist and medical physicist. The preliminary plan will be run through the RapidPlan module, which will give a list of possible improvements to the plan. The dosimetrist will then make an amendment to the plan according to RapidPlan suggestions, followed by plan change requests and approval by the physician.

Interventions

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Machine Learning Assisted Radiation (MLAP) RapidPlan

Radiation therapy simulation, target delineation, dosing, localization, and follow-up will be followed per standard of care practices and/or at the discretion of the treating radiation oncologist. To elaborate, patients will receive a treatment planning CT (computed tomography) scan, followed by normal tissue delineation through the physician and/or medical dosimetry assistant, followed by target delineation by the physician, followed by radiation treatment planning with the dosimetrist and medical physicist. The preliminary plan will be run through the RapidPlan module, which will give a list of possible improvements to the plan. The dosimetrist will then make an amendment to the plan according to RapidPlan suggestions, followed by plan change requests and approval by the physician.

Intervention Type RADIATION

Radiation Therapy Standard of Care (SOC)

Radiation therapy simulation, target delineation, dosing, localization, and follow-up will be followed per standard of care practices and/or at the discretion of the treating radiation oncologist. To elaborate, patients will receive a treatment planning CT (computed tomography) scan, followed by normal tissue delineation through the physician and/or medical dosimetry assistant, followed by target delineation by the physician, followed by radiation treatment planning with the dosimetrist and medical physicist, followed by plan change requests and approval by the physician.

Intervention Type RADIATION

Eligibility Criteria

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Inclusion Criteria

* Age ≥ 18 years at time of registration
* Receiving curative intent intensity modulated radiotherapy for head and neck primary cancer at the discretion of the treating medical doctor (MD)
* Provide written informed consent or allow legally authorized representative to consent on behalf of a participant
* Willing to return to enrolling institution for study follow-up visit