Essentials and guidelines for clinical medical physics residency training programs: executive summary of AAPM Report Number 249.

There is a clear need for established standards for medical physics residency training. The complexity of techniques in imaging, nuclear medicine, and radiation oncology continues to increase with each passing year. It is therefore imperative that training requirements and competencies are routinely reviewed and updated to reflect the changing environment in hospitals and clinics across the country. In 2010, the AAPM Work Group on Periodic Review of Medical Physics Residency Training was formed and charged with updating AAPM Report Number 90. This work group includes AAPM members with extensive experience in clinical, professional, and educational aspects of medical physics. The resulting report, AAPM Report Number 249, concentrates on the clinical and professional knowledge needed to function independently as a practicing medical physicist in the areas of radiation oncology, imaging, and nuclear medicine, and constitutes a revision to AAPM Report Number 90. This manuscript presents an executive summary of AAPM Report Number 249.

Reporter gene imaging using radiographic contrast from nonradioactive iodide sequestered by the sodium-iodide symporter.

The hypothesis that the human sodium-iodide symporter, NIS, can be used to detect NIS expression using standard radiological techniques was tested using adenoviral transduced NIS expression in human tumor xenografts grown in mice and in a naive dog prostate. Nonradioactive iodide was administered systemically to animals that 1-3 days previously had received a local injection of a replication-competent adenovirus expressing NIS under the control of the CMV promoter. The distribution of radiopacity was assessed in mouse tumors using micro-CT and a clinical X-ray machine and in the prostate of an anesthetized dog using a clinical spiral CT. Iodide sequestration and NIS expression were measured using X-ray spectrochemical analysis and fluorescence microscopy, respectively. Radiographic contrast due to NIS gene expression that was observed indicates the technique has potential for use in preclinical rodent tumor studies but probably lacks sensitivity for human use.

Magnetically-labeled sensitized splenocytes to identify glioma by MRI: a preliminary study.

This study investigated the feasibility of imaging the migration and incorporation of magnetically-labeled sensitized splenocytes in an experimental 9L glioma brain tumor model. Splenocytes collected from tumor-bearing (sensitized splenocytes) or control (nonsensitized splenocytes) host rats were analyzed to determine the population of different cells, labeled with ferumoxides-protamine sulfate (FePro) and injected intravenously to recipient rats (N=4, for each group) bearing intracranial 9L tumors. Day 3 postinjection of splenocytes multiecho T2*-weighted and three-dimensional (3D) gradient echo MRI were obtained using a 7 Tesla MR system. R2* (1/T2*) maps were created from the T2*-weighted images. Signal intensities (SIs) and R2* values in the tumors and contralateral brain were determined by hand drawn regions of interest (ROIs). Brain sections were stained for the evidence of administered cells. Both 3D and T2*-weighted MRI showed low signal intensity areas in and around the tumors in rats that received labeled sensitized splenocytes. Prussian blue (PB), CD45- and CD8-positive cells were present in areas at the corresponding sites of low signal intensities seen on MRI. Rats that received labeled nonsensitized splenocytes did not show low signal intensity areas or PB positive cells in or around the implanted tumors. In conclusion, the immunogenic reaction can be exploited to delineate recurrent glioma using MRI following systemically delivered magnetically labeled sensitized splenocytes or T-cells.

Model-independent method for fMRI analysis.

This paper presents a fast method for delineation of activated areas of the brain from functional magnetic resonance imaging (fMRI) time series data. The steps of the work accomplished are as follows. 1) It is shown that the detection performance evaluated by the area under the receiver operating characteristic curve is directly related to the signal-to-noise ratio (SNR) of the composite image generated in the detection process. 2) Detection and segmentation of activated areas are formulated in a vector space framework. In this formulation, a linear transformation (image combination method) is shown to be desirable to maximize the SNR of the activated areas subject to the constraint of removing inactive areas. 3) An analytical solution for the problem is found. 4) Image pixel vectors and expected time series pattern (signature) for inactive pixels are used to calculate weighting vector and identify activated regions. 5) Signatures of the activated regions are used to segment different activities. 6) Segmented images by the proposed method are compared with those generated by the conventional methods (correlation, t-statistic, and z statistic). Detection performance and SNRs of the images are compared. The proposed approach outperforms the conventional methods of fMRI analysis. In addition, it is model-independent and does not require a priori knowledge of the fMRI response to the paradigm. Since the method is linear and most of the work is done analytically, numerical implementation and execution of the method are much faster than the conventional methods.