Prediction of Low Quality ADC Maps from T2 Scans

Motivation: ADC maps are an essential tool for early prostate cancer detection but are often uninterpretable due to imaging artifactsGoal(s): Detect problems early in the imaging procedure using T2 images to predict the future quality of the ADC mapApproach: Constructed a multisite corpus of 486 patients imaged at both the NIH and outside. Investigated the influence of acquisition parameters on image quality and the predictive power of neural networks and simple anatomy measurements from the T2 imageResults: ADC image quality can be predicted from the T2 image using either a neural network approach or measurement of the rectal cross-sectionImpact: The probability of a low quality, uninterpretable ADC maps can be inferred early in the imaging process, allowing corrective action (e.g. removal of gas by a muscle relaxant) to be employed