The dawn of quantitative imaging

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Lisa Fratt - FOR LEAD ONLY - 118.11 Kb

Early June typically marks the 2012 annual meeting of the Society for Imaging Informatics in Medicine (SIIM). And as I prep for this year’s meeting, I can’t help but notice some interesting parallels between the meeting program and’s June advanced visualization portal.

Notably, SIIM is debuting a new learning track: Quantitative Imaging.

According to the society, “In recent years, the focus has changed such that for some disease categories (e.g. oncology) we now perceive medical imaging as a phenotypic expression of the genetic makeup of that disease. To that end, imaging now serves as a biomarker of genetic disease subtypes with features that may offer clues to understanding the natural behavior of the disease and specific changes that may occur as part of a therapeutic response. It is now well recognized that there is a substantial amount of objective information contained within diagnostic imaging studies that can be exploited beyond the level of simple measurements.”

As SIIM presenters ponder the revolution and evolution of quantitative imaging, researchers are exploring and demonstrating its potential. A diffusional kurtosis model, for example, may help radiologists better distinguish benign from malignant regions of prostate cancer, and perhaps, determine the aggressiveness of malignant prostate cancer sextants. Ultimately, such data could help clinicians fine-tune treatments to better target disease, spare normal tissue and reduce the chance of complications.

The shortcomings of using pure anatomic data to assess malignancies and response to therapy are well-recognized and spurred researchers to propose PET Response Criteria in Solid Tumors (PERCIST) as an alternative or adjunct to Response Evaluation Criteria in Solid Tumors (RECIST).

A group of Japanese researchers compared the two measures among patients undergoing neoadjuvant therapy for esophageal cancer and reported that the PET-based measure better predicted patient outcomes.

We are just starting to see the promise and potential of quantitative imaging. By harnessing the tools of advanced visualization, quantitative imaging equips clinicians to better understand disease and response to treatment. It provides them with the data to personalize clinical decisions. SIIM presenters and radiology and informatics researchers around the globe seem to concur—quantitative imaging represents the next great leap in advanced visualization.

How do you see quantitative imaging transforming practice? Let us know.

Lisa Fratt, editor