Diagnostic imaging runs the risk of becoming invisible in medicine unless it changes with the times, health IT expert Dr. Eliot L. Siegel warned conference-goers at the New York Imaging and Informatics Symposium on Monday.
In the era of evidence-based care, procedures will need to be tied to metrics around performance, efficacy, safety and cost-efficiency driven by the collection of big data.
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But this poses a problem for radiology, since it's difficult to mine much information from a radiology study compared to, say, a blood test.
"Many people think of radiology as artwork," Siegel said, adding that radiology runs the risk of becoming commoditized unless it can deliver personalized care using detailed information about the patient. "The problem is, many of the rules we have are one size fits all."
Personalized medicine generally refers to the ability of what Siegel calls the "omics" — genomics, metabolomics, and proteomics — to provide tailored medical care to patients based on their unique genetic and physiological makeup.
Indeed, personalized, genetics-based medicine has received high-profile attention lately. Movie actress Angelina Jolie boosted awareness on the topic when she made headlines this May
for undergoing a mastectomy based on a genetic test.
This trend is only expected to accelerate further as patients' genetic data become easier and less costly to access. The cost of mapping human DNA has already plummeted drastically in a short span of time, from $10 million in 2007 to $100 in 2012.
To a certain extent, the imaging community has already tried to seize on the term "personalized medicine" when referring to nuclear imaging modalities such as PET/CT and SPECT/CT, which can actually provide information about the patient on a molecular level.
But could traditional imaging also provide personalized care? According to Siegel, the answer is yes.
Diagnosis beyond imaging
To stay medically relevant, imaging studies must go beyond answering immediate clinical questions by collecting other, routine information about the patient. "I would know whether this patient had osteoporosis or coronary artery calcification," Siegel said.
For example, while a patient was undergoing a scan for an unrelated part of the body, the image report might register that the patient's aorta had reached a size threshold that put the patient at higher risk for developing an aneurysm and alert the doctor.
Continue reading Will big data rescue or ruin diagnostic imaging?...