Lung cancer is frequently overlooked in chest radiographs (CXR), often caused by overprojection of bone structures in the image. Bone suppression imaging (BSI) techniques could improve detection and interpretation of lung nodules. We investigated the effect of a new software product (Clearread BSI 2.4, Riverain Medical Group, Miamisburg, Ohio) that suppresses ribs and clavicles, on the detection of lung nodules. Eight observers, including five radiologists and three residents assessed radiographs of 111 patients with a CT proven solitary nodule and 189 controls. In a fully crossed study design observers assessed first radiographs without and with BSI sequentially. Secondly they scored radiographs independently having BSI available from the beginning. Five months later, the same readers scored the same cases again in an independent reading session, completing the three scorings for CXRs with BSI. Multi reader multi case (MRMC) receiver operating characteristics (ROC) were used for statistical analysis. DBM variance component estimates were calculated. Reading times were digitally recorded. Observer achieved a mean area under the curve (AUC) for unaided reading of 0.855. AUC increased to 0.883(p=0.002) with BSI in the sequential reading mode and to 0.874 (p=0.21) in the independent reading mode. In the second independent reading session after five months the AUC was 0.882 (p=0.20). Median reading times were 19s per case for the unaided CXR with another 10s for reading BSI sequentially. For the independent modes reading times were 19s and 18s. Total observer variance between sequential and independent reading design remained the same. A strong increase of uncorrelated components was found in the independent reading sessions, masking the ability to demonstrate differences in observer performance across modalities. In conclusion, bone suppression imaging improves lung nodule detection in CXR and does not prolong reading time. The independent study design has little power compared to the sequential study design due to a strong increase of uncorrelated variance components.
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