Daily AI-Based Treatment Adaptation under Weekly Offline MR Guidance in Chemoradiotherapy for Cervical Cancer 1: The AIM-C1 Trial.
Fabian WeykampEva MeixnerNathalie AriansPhilipp Hoegen-SaßmannshausenJi-Young KimBouchra TawkMaximilian KnollPeter HuberLaila KönigAnja SanderTheresa MokryClara MeinzerHeinz-Peter SchlemmerOliver JäkelJürgen DebusJuliane Hörner-RieberPublished in: Journal of clinical medicine (2024)
(1) Background: External beam radiotherapy (EBRT) and concurrent chemotherapy, followed by brachytherapy (BT), offer a standard of care for patients with locally advanced cervical carcinoma. Conventionally, large safety margins are required to compensate for organ movement, potentially increasing toxicity. Lately, daily high-quality cone beam CT (CBCT)-guided adaptive radiotherapy, aided by artificial intelligence (AI), became clinically available. Thus, online treatment plans can be adapted to the current position of the tumor and the adjacent organs at risk (OAR), while the patient is lying on the treatment couch. We sought to evaluate the potential of this new technology, including a weekly shuttle-based 3T-MRI scan in various treatment positions for tumor evaluation and for decreasing treatment-related side effects. (2) Methods : This is a prospective one-armed phase-II trial consisting of 40 patients with cervical carcinoma (FIGO IB-IIIC1) with an age ≥ 18 years and a Karnofsky performance score ≥ 70%. EBRT (45-50.4 Gy in 25-28 fractions with 55.0-58.8 Gy simultaneous integrated boosts to lymph node metastases) will be accompanied by weekly shuttle-based MRIs. Concurrent platinum-based chemotherapy will be given, followed by 28 Gy of BT (four fractions). The primary endpoint will be the occurrence of overall early bowel and bladder toxicity CTCAE grade 2 or higher (CTCAE v5.0). Secondary outcomes include clinical feasibility, quality of life, and imaging-based response assessment.
Keyphrases
- locally advanced
- artificial intelligence
- rectal cancer
- lymph node
- computed tomography
- healthcare
- machine learning
- physical activity
- clinical trial
- risk assessment
- high resolution
- spinal cord injury
- metabolic syndrome
- quality improvement
- adipose tissue
- deep learning
- study protocol
- chronic pain
- pain management
- radiation induced
- weight loss
- cone beam