Deployment of a dose-reduction algorithm in Molecular breast Imaging - impact of reader experience on its optimization

Objectives: Molecular Breast Imaging, performed with Tc-99m sestamibi and small CZT-based detectors is a valuable technique for detection of breast cancers occult on mammography. Previous work has shown that a noise reduction algorithm (ClearMBI) allows for a 50% reduction in image acquisition time, while yielding improved image quality relative to a standard acquisition. Optimization of the filter settings for ClearMBI in our lab was accomplished by experienced breast radiologists and nuclear medicine technologists. Deployment of this algorithm in sites with little or no experience with MBI may not achieve these optimal results. Hence, the objective of this study was to determine if this optimization was dependent on user experience with MBI

Methods: Two groups of readers were selection. Group 1 comprised a total of 4 breast imagers / scientists and 4 nuclear medicine technologists with each more than 2 year’s experience with MBI (>2000 patient studies/reader). Group 2 comprised 2 nuclear medicine physicians and 4 nuclear medicine technologists with no experience with MBI. Each reviewer was presented with a test set of 20 MBI exams (each containing a lesion) representing a range of count densities. For each exam, only the original half-dose image was displayed, and the reviewer was allowed to freely adjust the ClearMBI filter setting until their preferred lesion conspicuity was achieved. The average filter setting as a function of counts per pixel in the MBI images was obtained for each group and compared to the previously derived equation that was used to validate the algorithm.

Results: Table 1 below shows the previously reported filter settings, those from experienced reviewers, and those from nuclear medicine physicians and technologists (filter value % = slope * mean cts/pixel in image + intercept). Figure 1 shows an example of an image filtered using the previous published filter values and the corresponding values from Table 1 above. By comparison to experienced reviewers, the nuclear medicine physicians tended to over denoised the MBI images, whereas the technologists tended to under denoise the images. Lack of consistency in use of the algorithm may reduce acceptance by physicians. Implementation of this algorithm into a clinical practice that is initiating an MBI service should provide optimized values of the filter settings to ensure consistent results.

Conclusions: Implementation of the ClearMBI algorithm is strongly dependent on user experience. For new installations with little or no experience in MBI, it is recommended that staff use the previously published filter settings, rather than determining their own.

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