Healthcare Software: Treatment Planning

Improving Patient Care

The development of treatment and procedural plans are crucial in the provision of efficient, accurate and quality healthcare. Researchers at Emory University have worked to develop several planning models, software, and algorithms to personalize and improve the efficiency and accuracy of multiple popular medical procedures. These new tools can serve to improve a patient's experience and treatment success.

Accurate Prostate Cancer Imaging for High-Dose-Rate Brachytherapy Planning

High-dose-rate (HDR) brachytherapy, which delivers radiotherapeutics to the prostate through small inserted catheters, is a common treatment for patients suffering from prostate cancer. To optimize treatment placement of said catheters is extremely important. Unfortunately, current methods to identify potential treatment targets of effective catheter sites are not wholly accurate. Emory researchers were consequently inspired to develop a treatment planning model that uses 3-D intra-operative ultrasound (TRUS) images of the prostate after catheter insertions and post-operative CT scans to better understand the 3D volume of a patient's prostate. This new planning method allows doctors to use the more accurate 3D volume of a prostate to increase treatment accuracy and decrease the risk of affecting neighboring healthy tissue. (View our technology brief - Techid: 13115)

Clear View: Radiation Therapy Optimization Software

During radiation therapy treatments, a patient lays of a couch while a linear accelerator (LINAC) mounted on a rotating gantry circles them, releasing an external beam that traces a pre-planned treatment program. However, both the gantry that the LINAC is mounted on and the couch that the patient is on are not completely stationary creating a possible threat that the LINAC gantry may collide with stationary objects in the treatment environment. This dilemma encouraged Emory inventors to develop software that visualizes patient specific points of potential collisions between the gantry and other environmental objects. This software creates a 3-D model to simulate patient, gantry, and couch positions, which can indicate to doctors the optimal gantry and couch positions to reduce the threat of environmental collisions, thereby increasing treatment accuracy.(View our technology brief - Techid: 14007)

High-Resolution Field Inhomogeneity Correction for Magnetic Resonance Spectroscopy

MR spectroscopy (MRS) is a non-invasive technique to detect metabolic changes in the tissues of the human body. CEST is an MR technique that enables imaging of certain compounds at concentrations that are often too low to be imaged directly, such as glutamate and phosphocreatine. Although CEST MRI has been adopted in the clinical setting, it suffers from relatively low contrast and no algorithm is able to overcome the intravoxel inhomogeneity in spectroscopy (both routine MRS and CEST MRI spectroscopy). Emory researcher Dr. Sun, however, has developed a high-resolution field map-based deconvolution algorithm for the correction of intravoxel field inhomogeneity in MR spectroscopy. Dr. Sun's CEST intravoxel inhomogeneity correction (CIVIC) approach may assist in imaging certain compounds for the diagnosis of diseases. (View our technology brief - Techid: 19102)

Imaging-Based Software to Determine Lead Placement of Cardiac Pacemakers

Cardiac resynchronization therapy is a risky treatment that uses an implanted bi-ventricular pacing device to resynchronize the heart ventricle's contractions using electrical pulses. Unfortunately, about one third of patients do not respond positively to this treatment method. Dr. John Oshinski and his colleagues hypothesized that these poor treatment responses may be induced by poor patient selection criteria or poor device implementation. Oshinski is currently developing novel software in hopes of improving the accuracy of device placement, thereby improving patient outcomes. This software will use imaging to analyze a patient's left ventricle contraction timing, myocardial scar distribution, and coronary vein anatomy. This analysis will help create a more precise plan for placement of the pacing device. (View our feature; view our technology brief - Techid: 11149)

Imaging Software for Individualized Treatment with Radiotherapy

Prostate cancer is the most prevalent form of cancer seen in American men. A new predictive mathematical model has been developed at Emory to improve the accuracy and specificity of radiation margins for each individual patient undergoing image-guided radiation therapy. Current methods of radiotherapy run the risk of missing treatment margins and exposing the patient to more radiation than is strictly necessary. This occurs because during and between radiotherapy treatments a patient's prostate can shift positions. In a study, the current, non-patient specific 2 mm margin approach predicted future prostate motion for only 50% (12) of the patients. This new treatment model predicted prostate motion for 91.7% (22) patients. This software can improve radiotherapy accuracy and safety for future prostate cancer patients. (View our technology brief - Techid: 13004)

Magnetic Resonance Based Pseudo-Computed Tomography (CT)

Computed tomography (CT) is an invaluable imaging tool in clinical practice but it is difficult to detect poor soft tissue contrast in tumor delineation. Though the compensation of magnetic resonance (MR) imaging technique helps provide greater soft tissue details, its image misalignment often impacts results. To alleviate the problem, Emory inventors have developed a software solution to convert MR images into pseudo-CT images using a patch-based, random machine learning framework. This prediction model can help simplify patients' diagnostic process and reduce their exposure to radiation from X-rays. (View our technology brief - Techid: 17073)

RTAnalytics: Radiation Treatment Planning Software Using Image Databases

Approximately one half of all cancer patients require radiation therapy at some point in their treatment process. However, current radiation therapy planning is neither automated nor is based on prior knowledge or existing databases. Consequently, current methods of radiation therapy planning are inefficient and untimely. To alleviate this issue, Emory researchers developed software that finds and compares similar Volumetric Modulated Arc Therapy (VMAT) cases with that of an individual patient. This software analyzes previous patient cases that are similar to the current case and uses data from those cases to suggest irradiation settings and attainable constraints. The development of this software and the use of VMAT increases both radiation therapy efficiency and treatment accuracy. (View our technology brief - Techid: 13058)

Smart Start Treatment Planning

One of the most common treatment methods for men suffering from early stage prostate cancer is low dose (LDR) brachytherapy. This treatment is a form of radiotherapy that uses a sealed radiation source inside or in close proximity to the treatment area. Existing brachytherapy planning software does not use a knowledge-based treatment planning platform. Researchers at Emory have developed treatment planning software tailored to physician preferences for prostate brachytherapy. This software uses a starting point of previous physician specific therapy plans. The algorithm then compares data from past cases to the current case in order to form a LDR plan that is optimal for both the patient and the physician. This software can help standardize plan quality of LDR treatment delivery, while simultaneously decreasing planning time. (View our technology brief - Techid: 15114)

Software for Reviewing Patients in Radiotherapy Chart Rounds

A communication method in current radiation therapy is through a manual weekly chart review of each patient's treatment record. The chart review is laborious, inefficient, and easy to delay the detection of a potential treatment error. Emory inventors have developed a software system to automate chart checks and streamline peer-review for radiotherapy patients. Not only can the software allow streamlined review of documentation and data, but it also employs artificial intelligence to help check treatment accuracy. The software offers a quality assurance platform for chart rounds review and has been used at Emory University since 2016. (View our technology brief - Techid: 18008)