Amide's a Medical Image Data Examiner (AMIDE) has been developed as a user-friendly, open-source software tool for displaying and analyzing multimodality volumetric medical images. Central to the package's abilities to simultaneously display multiple data sets (e.g., PET, CT, MRI) and regions of interest is the on-demand data reslicing implemented within the program. Data sets can be freely shifted, rotated, viewed, and analyzed with the program automatically handling interpolation as needed from the original data. Validation has been performed by comparing the output of AMIDE with that of several existing software packages. AMIDE runs on UNIX, Macintosh OS X, and Microsoft Windows platforms, and it is freely available with source code under the terms of the GNU General Public License.

Luciferases, which have seen expansive employment as reporter genes in biological research, could also be used in applications where the protein itself is conjugated to ligands to create probes that are appropriate for use in small animal imaging. As the bioluminescence activity of commonly used luciferases is too labile in serum to permit this application, specific mutations of Renilla luciferase, selected using a consensus sequence driven strategy, were screened for their ability to confer stability of activity in serum as well as their light output. Using this information, a total of eight favorable mutations were combined to generate a mutant Renilla luciferase (RLuc8) that, compared with the parental enzyme, is 200-fold more resistant to inactivation in murine serum and exhibits a 4-fold improvement in light output. Results of the mutational analysis were also used to generate a double mutant optimized for use as a reporter gene. The double mutant had half the resistance to inactivation in serum of the native enzyme while yielding a 5-fold improvement in light output.These variants of Renilla luciferase, which exhibit significantly improved properties compared with the native enzyme, will allow enhanced sensitivity in existing luciferase-based assays as well as enable the development of novel probes labeled with the luciferase protein.

Multiparametric magnetic resonance imaging (mpMRI) interpreted by experts is a powerful tool for diagnosing prostate cancer. However, the generalizability of published results across radiologists of varying expertise has not been verified. To assess variability in mpMRI reporting and diagnostic accuracy across radiologists of varying experience in routine clinical care. Men who underwent mpMRI and MR-fusion biopsy between 2014-2016. Each MRI scan was read by one of nine radiologists using the Prostate Imaging Reporting and Data System (PIRADS) and was not re-read before biopsy. Biopsy histopathology was the reference standard. Outcomes were the PIRADS score distribution and diagnostic accuracy across nine radiologists. We evaluated the association between age, prostate-specific antigen, PIRADS score, and radiologist in predicting clinically significant cancer (Gleason ≥7) using multivariable logistic regression. We conducted sensitivity analyses for case volume and changes in accuracy over time. We analyzed data for 409 subjects with 503 MRI lesions. While the number of lesions (mean 1.2 lesions/patient) did not differ across radiologists, substantial variation existed in PIRADS distribution and cancer yield. The significant cancer detection rate was 3-27% for PIRADS 3 lesions, 23-65% for PIRADS 4, and 40-80% for PIRADS 5 across radiologists. Some 13-60% of men with a PIRADS score of <3 on MRI harbored clinically significant cancer. The area under the receiver operating characteristic curve varied from 0.69 to 0.81 for detection of clinically significant cancer. PIRADS score (p<0.0001) and radiologist (p=0.042) were independently associated with cancer in multivariable analysis. Neither individual radiologist volume nor study period impacted the results. MRI scans were not retrospectively re-read by all radiologists, precluding measurement of inter-observer agreement. We observed considerable variability in PIRADS score assignment and significant cancer yield across radiologists. We advise internal evaluation of mpMRI accuracy before widespread adoption. We evaluated the interpretation of multiparametric magnetic resonance imaging of the prostate in routine clinical care. Diagnostic accuracy depends on the Prostate Imaging Reporting and Data System score and the radiologist.