Machine Intelligence for Accurate X-ray Screening and Read-out Prioritization: PICC line Detection Study

A peripherally inserted central catheter (PICC) is a thin, flexible plastic tube that provides medium-term intravenous access for medicine, fluid, and chemotherapy administration. These are inserted into arm veins and threaded into the patient until the catheter tip reaches a large vein near the heart. As malpositioned PICCs can have potentially, serious complications, final position of all PICCs are always confirmed with a chest radiograph immediately after insertion. This radiograph requires timely and accurate interpretation by a highly-trained domain expert in medical imaging interpretation – a Radiologist. Although the error rate for radiologists misinterpreting PICC location is likely extremely low, delays in interpretation can be substantial—particularly when this radiograph is one of many to be interpreted with imaging studies from many different modalities and different patients also requiring diagnostic attention. However, machine intelligence techniques can help prioritize and triage the review of radiographs to the top of a radiologist’s queue, improving workflow and turn-around-time (TAT). Such prioritization does not require high specificity, but rather high sensitivity; they should alert the radiologist to all potentially important radiographs requiring immediate attention with a low false negative rate.