Medical Physics

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Research Projects

Medical Physics has ongoing research that covers a broad range of topics. All research topics are related to the understanding of fundamental aspects of imaging processes, including efforts to improve image quality and control radiation doses.

MRI Stereotactic Radiosurgery Planning

Developing a custom head phantom to validate the accuracy of magnetic resonance imaging-based stereotactic radiosurgery planning

We have developed MRI-only stereotactic radiosurgery (SRS) treatment planning, a method of using geometrically corrected MR images for accurate tumor delineation in combination with synthetic CT images derived directly from MR images for more accurate SRS dose calculation and planning. To enter the clinical routine, this procedure must be accurately evaluated and tested as a part of a routine quality control (QC) procedure. The goal of this project is to develop a custom head phantom and use it 1) to validate the accuracy of using MR images for SRS treatment planning and dose delivery; 2) for routine QC.

The standard of care for treating malignant brain tumors includes SRS; the goal is to maximize radiation delivery to tumor tissue while sparing adjacent healthy brain tissue. In the process of radiation treatment planning, MRI or CT images are used for delineating target and healthy tissue. CT imaging is widely available and routinely used for SRS planning, but MRI offers higher soft tissue contrast with the advantage of no ionizing radiation exposure. Thus, MRI improves the accuracy of target delineation, offers better characterization of relevant tumor properties, and reduces the radiation dose to patient.

However, MR images suffer from geometric distortion and a lack of electron density information necessary for dose calculation, which is usually obtained and corrected from and with CT images. Consequently, image registration between MR and CT is necessary. This procedure requires high precision, accuracy, reproducibility and optimized clinical workflow; otherwise, it will cost additional time, money and radiation exposure for the patient, and may introduce inaccuracies to the treatment plan.

Some quality control phantoms are commercially available, but they have major limitations, such as 1) not mimicking brain tissue and air cavities, the major sources of MR image distortion; 2) lacking bone structure, used to validate the accuracy of synthetic CT images; 3) lacking markers and deformable object to check MRI/CT rigid and non-rigid registration; and finally, 4) not offering dosimetric modules (film or ion chamber) to validate the dosimetric accuracy of plans and perform patient-specific QC. Therefore, we propose to develop a MRI-only SRS-appropriate QC phantom, which we hypothesize will increase treatment accuracy and patient safety, save time, and improve clinical outcomes.

Intracranial tumor (GBM) response based on RANO criteria


A computational environment (GUI) that allows to determine in a simple, exact and fast way the response of intracranial tumors (e.g. Glioblastoma Multiforme) through the Response Assessment in Neuro-Oncology (RANO) criteria is being developed.

The GUI will have an image assistant that will allow the user to measure the lengths of the evaluated tumor(s). The set of length results will be automatically exported to a visual environment where the user, besides visualizing the tumor(s) and their most significant measurements, will be able to obtain the result of the analysis based on the RANO criteria.

Radiomics predict response/outcome in head & neck cancer patients treated with chemoradiation


Surveillance imaging for patients who are treated with definitive chemoradiation has inherent pitfalls due to the difficulty to differentiate residual disease from radiation changes. These shortcomings in the imaging might lead to unnecessary interventions including salvage surgery, thus resulting in worse Quality of Life for the patients and increased health care expenses. This study assessed the response and progress of tonsillar cancer patients treated with chemoradiation with the purpose of differentiate between residual tumor and radiation changes through radiomics features extracted from pre-treatment and post-treatment CT images.

Radiomics in Radiation Oncology


Definition of radiotherapy target volume is a critical step in treatment planning for all tumor sites. Conventional magnetic resonance imaging (MRI) pulse sequences are used for the definition of gross target volume (GTV) and contouring of glioblastoma multiforme (GBM), meningioma and, other types of intracranial tumors. We are using multiparametric MRI combined with radiomic features to improve the texture-based differentiation of tumor from edema for GTV definition, and to differentiate vasogenic from tumor cell infiltration edema.

So far, it has been possible to select a small number of radiological texture characteristics from a set of several hundred parameters initially calculated through different scenarios, different MRI sequences and various approaches. The selected parameters allowed the segregation of the tumor regions in the brain and the differentiation of edema and tumor tissue. Additional regions of interest (e.g. necrotic region, etc.) will be included in our next studies.

In addition, we are performing an assessment using different modalities (MRI, CT, PET) correlated with histopathology, pre and post dosimetry planning and tumor response evaluation.

Dosimetry in Y-90 Radioembolization


Current imaging assessment requires one to two months post-treatment to determine effectiveness due to radical changes that occur to the tissue in response to radiation. This delay is a hindrance to providing better patient outcomes, and, thus, there is a need to identify faster biomarkers to determine treatment success.

We will assess Y-90 dosimetry preplanning using MRI, CT and SPECT MAA images using a software called Simplicity. Then, the result will be correlated with post dosimetry map using PET and tumor response based on physician evaluation and histopathology results.

Updated 4/25/2019