CHICAGO — For several years, there’s been a push in health care – particularly in pharmaceuticals – toward personalized medicine. By using a patient’s genetics to better target their medications and therapies, the medical industry has achieved improved patient outcomes.
But, what if you could launch individualized care at an earlier stage – at the point of pathological diagnosis? According to radiology and pathology experts at the 2014 Radiological Society of North America annual meeting, this could be the next wave that takes personalized medicine to the next level.
“The idea is to personalize how we treat patients based on their unique characteristics,” said Mitch Schnall, MD, PhD, radiology department chair, University of Pennsylvania. “The idea of developing data that characterizes someone really gets to the heart of what diagnosis is about. It’s crucial to realizing any benefit.”
In this case, it’s pairing the high-definition, advanced imaging from radiology with existing high-tech tools from pathology to render the most detailed, accurate diagnosis possible. Providing pathologists with advanced images down to micro-level accuracy allows them to better see tissue architectures and abnormalities. The added logistical data from imaging studies could make it easier for pathologists to sample and analyze the correct part of the tissue sample, said Michael Feldman, pathology and laboratory medicine associate professor at the Hospital of the University of Pennsylvania.
A greater link between radiology and pathology could also increase radiology’s involvement in molecular medicine, as well as a wide variety of medical research endeavors, said Martin Pomper, MD, PhD, a Johns Hopkins radiologist with an interest in pathobiology.
There will be challenges, however, said Curtis Langlotz, MD, PhD, medicine and radiology professor at Stanford University Medical Center. And, finding a point where these two specialties can meet in the middle will likely be the biggest one.
“Pathology is where radiology was with respect to digital imaging 10 years ago – where we know it’s going to happen. There’s promising technology out there, but it hasn’t yet happened to the point where it’s widely adopted and standardized,” said Langlotz, who has a research interest in biomedical informatics. “I think both radiology and pathology have recognized the need for structured reporting – where you actually have a standard for reporting certain things. And, pathology has just been at it longer.”
Integrating the workflow for radiology and pathology could be problematic, he said, because the cultures are fundamentally different. Radiologists have a daily run-down of the advanced imaging studies they will perform, so they’re able to plan their schedules. Pathology, however, never knows what might land on its doorstep – some days could be empty, some could be overflowing.
Creating that greater partnership between the two specialties could also alter how they’ve traditionally viewed themselves, Schnall said.
“Radiologists are used to ordering tests and having them come back to them so they can make a decision,” he said. “Now, we’re developing a diagnostic process with pathology that runs parallel to and supports them. It’ll change roles, and that might be the biggest challenge to making things a reality.”
As with most changes in radiology, Feldman said, meshing the skill sets of these specialties will require a plan for interoperability and standardization between vendor solutions. There also need to be clear clinical reasons to support having radiology and pathology work more closely together. A digital pathology solution designed to improve pathology workflow is currently available in Europe by Sectra. The platform, which is largely used with breast cancer diagnosis allows pathologists to access images from a variety of vendor products and enables simultaneous viewing of histology and cytology images, said Andrea Sowitch, North American marketing director, Sectra.
Ultimately, he said, fusing the specialties in this way could speed up diagnosis, improve accuracy, prompt better outcomes, and lead to better diagnostic and therapeutic resource management. It could ensure that the right tests are done at the right time and at a lower cost.
“It’s all about driving value to the patient at the workflow, imaging, and text-mining levels to improve outcomes,” Feldman said. “It makes for a more efficient diagnostic process, better informed practitioners, and an environment of reduced errors.”