Correlating Neurocognitive Outcomes with Radiation Dosimetry Metrics for Pediatric Medulloblastoma Patients

Dr. Matthew Ladra is up to big things these days. Big ideas, big data, and big impact.

Dr. Ladra is the Director of Pediatric Radiation Oncology at Sibley Memorial Hospital at The Johns Hopkins School of Medicine. He also happens to be one of the early adopters of ProKnow DS, the new cloud-based RT-PACS and big data analytics software.

Big data aggregation and analysis are key to studying radiation therapy late effects, and Dr. Ladra’s team has hit the ground running! Together with Children’s National neuropsychologist Kristina Hardy, PhD, they have been compiling hundreds of retrospective patient cases to investigate the correlation of neurocognitive outcomes in pediatric patients treated for standard risk medulloblastoma with the dosimetry to key central nervous system (CNS) structures.

Study Summary

“Patients in our study were randomized to receive either low- or standard-dose craniospinal radiation and a boost to either the posterior fossa or tumor bed,” explained Dr. Ladra, “and neurocognitive outcomes were collected at intervals up to 5 years after the completion of radiation.”

Some interesting and significant trends emerged. Said Dr. Ladra, “We saw that children who received low dose craniospinal radiation (CSI) had higher IQ scores 2-5 years after treatment than their standard-dose CSI counterparts, as did children who received a tumor bed boost rather than a whole posterior fossa boost. To identify which brain regions receiving a lower radiation dose were responsible for these improved IQ scores, we recontoured 10 important brain structures in our 130 medulloblastoma patients and then correlated the DVH data with the resulting cognitive outcomes.”

Preliminary Results & Next Steps

Based on this first phase of research, the Johns Hopkins team has already generated compelling data. “Our preliminary analyses have shown that every increase of 1-2 Gy to the mean dose of sensitive brain regions leads to a loss of 2-3 IQ points in older children and 3-4 points in younger children,” said Dr. Ladra. “These results emphasize that accurate contouring and high-quality planning with the aim to avoid some of these sensitive regions can impact the long term cognitive potential of our children.”

Based on this initial success, Dr. Ladra plans to expand the studies. “We are applying for funding to carry out a similar study for nearly 700 patients with a variety of brain tumors,” said Ladra, “with hopes to generate guidelines which apply to all tumor types in the brain. We expect to use the comparative planning functions in Proknow DS to take what we have learned from these analyses and create automated neurocognitive protective plans directed at improving the intellectual outcomes and quality of life of our pediatric patients.”

The Technology Behind the Study

An efficient study of this kind requires several key technology components, including:

1. An unlimited and practical RT-PACS storage system that provides for batch upload and auto-organization of archived data files as well as data transfer via direct export from a treatment planning system (TPS).
2. An interactive patient data viewer, allowing for comprehensive review of volumetric datasets comprised of CT and MRI images, anatomical contours, radiation plan information, and calculated radiation dose.
3. Contouring tools to create and edit contours, either prospectively or retrospectively.
4. A universal DVH calculator to ensure that all raw inputs (e.g, anatomical structure sets and 3D dose grids) are re-processed to DVH data that are consistent across all modalities, and of high accuracy.
5. Automatic structure renaming tools to enforce standardized naming conventions across historical datasets.
6. Batch extraction of user-defined dose- and DVH-based metrics across all patient datasets.
7. Interactive graphical and statistical tools such as population histograms and Population DVH to study variation, and scatter plots to study correlation, across a large cohort of patients.
8. Access via the cloud so the research is not limited by user location, client operating system, or expensive (and/or limited) software licenses.

Thankfully for Dr. Ladra and his team, ProKnow DS offers all of the above.

“Proknow DS has been an incredibly useful tool for us, increasing the speed and analytical power of our research,” he explained. “It allows us to quickly upload radiation plans and MRI imaging from various data locations and store it in an organized and centralized database, accessible via the internet anywhere we need it.”

“We design project-specific scorecards to generate the desired DVH data for each patient automatically, which is vital when navigating many hundreds of datasets and tens of thousands of data files. The graphing and histogram functions allow us to analyze these data instantly, showing results in presentation-ready graphs and plots. All graphs are interactive, too, meaning they allow us to quickly identify any outliers that might result from incomplete contours or incorrect RT plans. With a single click from the population analysis tools, we can access individual plans to make corrections without having to log in to any separate planning or contouring system.””

Dr. Ladra reflected on their workflow after using ProKnow for just a few months: “Compared to the workflow we used previously, Proknow DS has already saved us many weeks of time that we used to spend on cumbersome data mining, manual data extraction, and graph plotting and formatting.”

Into the Future

Dr. Ladra and his team hope to become trailblazers into the future of radiation late effects analysis. While their current studies are focused on pediatric patients and neurocognitive endpoints, their methods can be used across any patient cohort, anatomic treatment site, and across all radiation treatment modalities.

“These tools can be applied to any body site and across all treatment types. In fact, we are already exploring quantitative studies of salivary gland protection in adult head and neck cancer patients.”

More Information

Research Team

Matthew Ladra, MD, MPH, is an Assistant Professor of Radiation Oncology and Molecular Radiation Sciences and the Director of Pediatric Radiation Oncology at Sibley Memorial Hospital, which is part of The Johns Hopkins School of Medicine and Children’s National Medical Center. Interested in his research? You can contact him via email (mladra@jhmi.edu).

ProKnow® DS

ProKnow DS is a transformational new radiation therapy software system developed by ProKnow Systems. It allows organizations of all sizes to distribute tasks, centralize knowledge, and harness the power of big data. ProKnow DS is 510k pending in the USA and scheduled for release in October 2018, but is currently available for qualifying retrospective research studies. If this is the solution you have been waiting for and you would like to know more, please contact Ben Nelms, PhD (bnelms@proknow.com).