I AM
JOÃO VITOR M. FERNANDEZ
Medical Physicist
Healthcare Data Science & AI Specialist
Medical Physicist
Healthcare Data Science & AI Specialist
The constantly evolving field of radiotherapy requires a combination of hard and soft skills. Here are mine:
Treatment planning experience
Treatment Planning Systems and Record & Verify experience
Machine QA, PSQA and dosimetry skills
Artificial intelligence skills
Computer skills
Postgraduate lato sensu program with 362 hours at Data Science Academy (DSA), focused on improving the use of artificial intelligence (AI) in radiotherapy workflows and expanding my knowledge beyond my main field. The course covered topics such as advanced AI methods, medical image analysis, large language models (LLMs), creating and using predictive models, ethical issues, data privacy in AI, and practical projects with real healthcare data.
Completed 5,760 hours of specialized training in a modern clinical environment. Gained practical experience in simulation, treatment planning, and dose delivery using advanced techniques like 3DCRT, Dynamic Arc, IMRT, and VMAT for external beam radiotherapy. Worked with different treatments such as conventional, SBRT, and SRS, and also with brachytherapy (LDR and HDR). Developed skills in IGRT technologies like CBCT, ExacTrac, and surface-guided radiation therapy (SGRT) using OSMS. Performed monthly quality control based on TG-198, dosimetry following TRS-398, and patient-specific quality assurance (PSQA). My final project was about validating the 3D printing process of customized bolus using PLA.
A 300-hour professional development course at Data Science Academy (DSA) aimed at learning how to integrate artificial intelligence (AI) algorithms into radiotherapy, covering treatment planning, risk management, and quality control. The curriculum included health data analysis , applying machine learning to data, medical image analysis with AI , and some automation in medicine using AI and RPA of clinical workflows and processes. I was invited to participate in the DSA podcast to share my insights on artificial intelligence in the field of radiotherapy.
Bachelor’s degree in Physics with a minor in Medical Physics plus 930 hours of extracurricular courses including Modern Optics and Photonics, Quantum Technology, Computer-Aided Technical Drawing, Laser Physics, Electronics, among others. During my undergraduate studies, I actively participated in the research project Fabrication of interdigital transducers and growth of ZnO films for the generation of surface acoustic waves Additionally, I developed an automated temperature-controlled TLD irradiator which supported my undergraduate research focused on a study of the thermoluminescent properties of apatite from the Durango region in Mexico.
Worked as a medical physicist in radiotherapy, doing conformal treatment planning (using XiO and Monaco) and VMAT planning (with Monaco). Prepared treatment records and performed quality assurance, including mechanical QA (following AAPM TG-142), dosimetric QA (following IAEA TRS-398), and patient-specific QA (PSQA). Also helped with management tasks, creating protocols, and setting up safety procedures. Built strong skills in working with high patient numbers in a clinic with limited resources and gained experience solving important mechanical and dosimetric problems on the Elekta platform.
Shadowing experience in a clinical environment that provides care to cancer patients in Brazil’s public health system (SUS). Learned about 2D radiotherapy treatment planning for breast cancer using CAT3D software and 3D conformal planning with the Eclipse treatment planning system (Varian). Also participated in starting treatments, performing machine adjustments (Clinac iX, 600C, and Unique), and doing dosimetry following IAEA TRS-398 guidelines.
Extracurricular internship at Vila Nova Star Hospital (São Paulo, Brazil), where I learned about radiotherapy treatments on three different platforms: TrueBeam (Varian), TomoTherapy, and CyberKnife (Accuray). Observed treatment planning using Eclipse and Precision, and helped with quality assurance on each machine. Main highlights were a liver SBRT case with tracking on CyberKnife and a neuroaxis treatment done with TomoTherapy.
Extracurricular internship at Sievert Laboratory and Environmental Services (São Paulo, Brazil), focused on learning more about radiation dose estimation for imaging and environmental exposure. Worked on collecting data, running simulations, and calculating radiation doses from inhalation of naturally occurring radioactive materials (NORMs) by miners. Also did a comparison of different computational methods used for dose calculation in this area.
Mandatory curricular internship divided into three areas of medical physics: Radiotherapy (120 hours), Diagnostic Radiology (120 hours), and Nuclear Medicine (120 hours). Activities included following the daily work in each department and doing specific quality control tests. In the radiotherapy part, I also worked on conformal treatment planning for prostate and breast cancer using XiO software.
Part of the mandatory curricular internship in radiotherapy was done at CAISM. Activities included observing quality control routines, dosimetry procedures, and doing 2D and 3D conformal treatment planning for breast cancer using XiO software (Elekta).
Observed the daily work of the radiotherapy department, taking part in all steps of the treatment process, including simulation and treatment planning for external beam radiotherapy using 3DCRT, IMRT, and VMAT, as well as HDR brachytherapy. Also learned about special treatments like Total Body Irradiation (TBI) and blood irradiation for transplants. This experience was a strong motivation for me to follow a career in radiotherapy.
Covered key pediatric tumor types, treatment planning strategies, team emotional preparedness, and patient-centered care approaches, including imobilizationmask decoration to support a more humanized experience.
Focused on the entire treatment workflow—from simulation to quality assurance—this course also included hands-on planning cases using the Shulman method to achieve optimal treatment plans.
Continuing education course on radiosurgery techniques, covering technologies employed, treatment planning approaches, quality assurance procedures, and clinical cases of tumors in the central nervous system, as well as functional radiosurgery (e.g., depression, trigeminal neuralgia, and Parkinson's disease).
This traditional annual course hosted by Hospital Sírio-Libanês provides updates and fosters discussion on cutting-edge advances in radiation therapy and associated quality control protocols.
This workshop addressed the theoretical and practical aspects of low-dose-rate (LDR) brachytherapy for prostate cancer. In the 2023 edition, I had the honor of participating as a resident, contributing to volume analysis, needle preparation, and assisting in the implantation procedure.
This 40 hour course offered by the Brazilian National Cancer Institute (INCA) aimed to develop competencies in the clinical application of electron beams in radiation therapy. The curriculum covered the fundamental physics of electrons, clinical indications, and protocols for performing accurate electron beam dosimetry procedures and corresponding quality assurance tests with effectiveness and safety.
Radiological emergencies, such as the loss of a brachytherapy source, must be rigorously prevented. Nevertheless, in the event they do occur, they demand prompt and effective response measures. This course offered by the IRD addressed the entire response framework — from preparedness and planning to the management of emergency situations — including the appropriate use of personal protective equipment (PPE) and radiation detection procedures in emergency contexts.
With advances in imaging technologies, it has become possible to diagnose tumors with greater precision and to treat them using specialized techniques such as stereotactic radiosurgery (SRS). This short course introduced the Elements software, Brainlab's solution for SRS planning.
To uphold Hippocrates' maxim "Primum non nocere" ("First, do no harm"), high-quality radiotherapy must be delivered safely. This course addressed several tools for mitigating incidents, such as FMEA (Failure Modes and Effects Analysis) and FTA (Fault Tree Analysis), as well as incident learning systems in radiotherapy, such as SAFRON.
Since radiotherapy relies primarily on CT imaging, it is essential to understand the parameters that affect image quality, as well as dose optimization techniques and specific protocols — particularly for pediatric patients and pregnant individuals.
This hands-on workshop, offered by Varian during the XXV Brazilian Congress of Medical Physics (CBFM), covered radiotherapy treatment planning using Varian’s state-of-the-art technology. Topics included automatic contouring and AI-assisted treatment planning.
To better fight cancer, it is important to understand key aspects of its cellular origin and epidemiology. This way, it is possible to define habits for prevention and, if needed, use screening techniques to detect cancer at an early stage and improve treatment effectiveness.
This course covered the basic principles of radiotherapy, indications, patient selection, curative and palliative treatment, emergencies and benign diseases, and radiotherapy techniques: 3DCRT, IMRT, VMAT, SBRT, and SABR.
