Radiotherapy, also known as radiation therapy, is a treatment that uses high-energy radiation to kill cancer cells or shrink tumors. It can be used as a standalone treatment or in conjunction with other treatments such as surgery or chemotherapy.
Consultation with a Radiation Oncologist
During the initial consultation, the radiation oncologist reviews the patient’s medical history, diagnostic imaging, biopsy results, and history of surgeries. A physical examination is conducted, and the potential benefits and risks of radiotherapy are discussed with the patient. This step is crucial for determining the appropriateness of radiotherapy as a treatment option for the patient’s specific type of cancer.
Treatment planning and simulation
Once radiotherapy is deemed appropriate, the next step is treatment planning. This involves a simulation process using imaging studies like CT scans, MRI scans, or PET scans to precisely locate the tumor and map out the treatment area. The aim is to target the radiation as accurately as possible while minimizing damage to healthy tissues.
From the simulation of the treatment area to creating a treatment plan
This phase begins with the marking of the treatment area, a procedure that may involve placing tiny tattoo dots on the skin. These marks serve as precise reference points to align the radiation beams consistently in each treatment session, ensuring the radiation targets the exact same area every time.
Following the marking, a simulation session is conducted using advanced imaging techniques, such as CT scans, to create a detailed map of the patient’s anatomy in the treatment area. This simulation ensures that the patient’s position during radiation delivery mirrors the position they were in when the images were taken, aiding in the precision of treatment.
The radiation oncologist, in collaboration with a medical physicist and a dosimetrist, uses these images to meticulously plan the treatment. This involves a series of complex calculations to determine the optimal angles, intensities, and shapes of the radiation beams. The aim is to maximize the dose to the tumor while minimizing exposure to surrounding healthy tissues and organs, a principle known as dose optimization.
Automatic segmentation and its benefits
A pivotal advancement in treatment planning is the use of automatic segmentation technology. This involves artificial intelligence (AI) or machine learning algorithms automatically identifying and outlining the tumor and critical structures (such as organs at risk) on the imaging scans. This process, traditionally done manually by the radiation oncologist or dosimetrist, is time-consuming and can vary in accuracy depending on the individual’s expertise.
The integration of automatic segmentation into the treatment planning phase represents a significant leap forward in radiotherapy. It enhances the treatment’s accuracy, safety, and effectiveness, ultimately contributing to better patient outcomes. By leveraging these technological advancements, the multidisciplinary team can deliver highly personalized and precise radiotherapy, optimizing the balance between treating the cancer and preserving the patient’s quality of life.
Treatment Delivery and Follow-Up
During treatment delivery, the patient is positioned on a treatment table, and the radiation machine is adjusted according to the treatment plan. The process is usually painless and can take from a few minutes to half an hour. After completing the radiotherapy course, regular follow-up appointments are scheduled to monitor the treatment effects, manage side effects, and check for signs of cancer recurrence.
Looking ahead, the ongoing integration of technology in oncology holds the promise of further breakthroughs, offering hope for even more effective cancer treatments in the future.
Author: Remus Stoica, MD, Radiation Oncologist
References:
- Basic Radiation Oncology, Murat B., Introduction and History.
- Fiagbedzi E, Hasford F, Tagoe SN. The influence of artificial intelligence on the work of the medical physicist in radiotherapy practice: a short review. BJR Open. 2023 Oct 19;5(1):20230003. doi: 10.1259/bjro.20230003. PMID: 37942499; PMCID: PMC10630976.
- Thompson RF, Valdes G, Fuller CD, Carpenter CM, Morin O, Aneja S, Lindsay WD, Aerts HJWL, Agrimson B, Deville C Jr, Rosenthal SA, Yu JB, Thomas CR Jr. Artificial intelligence in radiation oncology: A specialty-wide disruptive transformation? Radiother Oncol. 2018 Dec;129(3):421-426. doi: 10.1016/j.radonc.2018.05.030. Epub 2018 Jun 12. PMID: 29907338; PMCID: PMC9620952.