Certification in Medical Physics Imaging, The Workforce and Training Models.

The pathway to becoming a qualified medical physicist (QMP) in the imaging physics disciplines includes several certification organizations. Imaging QMPs play an essential role in the safe practice of the diagnostic disciplines, and their qualifications are necessary for compliance with federal bodies and professional accreditation organizations. The future demand for imaging QMPs is largely unknown, but professional organizations that represent these groups agree that efforts should be made to increase the number of matriculating trainees. The number of imaging residency programs that provide the necessary professional experience to enter the certification pathway has increased substantially in recent years. Most of these programs follow a traditional academic hospital-based training model, but guidance on program construction from the accrediting body permits flexibility. Existing training models for medical physics imaging also include consortiums of affiliate partners and private consulting service groups. In this article, the authors briefly review the certification pathways for imaging QMPs, workforce estimates, and training models.

Repeatability of Quantitative 18F-NaF PET: A Multicenter Study.

18F-NaF, a PET radiotracer of bone turnover, has shown potential as an imaging biomarker for assessing the response of bone metastases to therapy. This study aimed to evaluate the repeatability of 18F-NaF PET-derived SUV imaging metrics in individual bone lesions from patients in a multicenter study. METHODS: Thirty-five castration-resistant prostate cancer patients with multiple metastases underwent 2 whole-body (test-retest) 18F-NaF PET/CT scans 3 ± 2 d apart from 1 of 3 imaging sites. A total of 411 bone lesions larger than 1.5 cm3 were automatically segmented using an SUV threshold of 15 g/mL. Two levels of analysis were performed: lesion-level, in which measures were extracted from individual-lesion regions of interest (ROI), and patient-level, in which all lesions within a patient were grouped into a patient ROI for analysis. Uptake was quantified with SUVmax, SUVmean, and SUVtotal Test-retest repeatability was assessed using Bland-Altman analysis, intraclass correlation coefficient (ICC), coefficient of variation, critical percentage difference, and repeatability coefficient. The 95% limit of agreement (LOA) of the ratio between test and retest measurements was calculated. RESULTS: At the lesion level, the coefficient of variation for SUVmax, SUVmean, and SUVtotal was 14.1%, 6.6%, and 25.5%, respectively. At the patient level, it was slightly smaller: 12.0%, 5.3%, and 18.5%, respectively. ICC was excellent (>0.95) for all SUV metrics. Lesion-level 95% LOA for SUVmax, SUVmean, and SUVtotal was (0.76, 1.32), (0.88, 1.14), and (0.63, 1.71), respectively. Patient-level 95% LOA was slightly narrower, at (0.79, 1.26), (0.89, 1.10), and (0.70, 1.44), respectively. We observed significant differences in the variance and sample mean of lesion-level and patient-level measurements between imaging sites. CONCLUSION: The repeatability of SUVmax, SUVmean, and SUVtotal for 18F-NaF PET/CT was similar between lesion- and patient-level ROIs. We found significant differences in lesion-level and patient-level distributions between sites. These results can be used to establish 18F-NaF PET-based criteria for assessing treatment response at the lesion and patient levels. 18F-NaF PET demonstrates repeatability levels useful for clinically quantifying the response of bone lesions to therapy.

Diagnostic Reference Levels of CT Radiation Dose in Whole-Body PET/CT.

UNLABELLED: The role of CT in PET/CT imaging includes acquisition techniques for diagnostic, anatomic localization, and attenuation correction purposes. Diagnostic reference levels of the volumetric CT dose index (CTDIvol) are available for dedicated CT procedures on selected body regions, but similar reference levels for whole-body CT used in PET/CT examinations are limited. This work reports CTDIvol values from sites that conduct whole-body oncologic PET/CT examinations and participated in the scanner validation program of the Society of Nuclear Medicine and Molecular Imaging Clinical Trials Network. METHODS: From 2010 to 2014, a total of 154 sites submitted CT acquisition parameters used in their clinical (18)F-FDG PET/CT oncology protocols. From these parameters, the CTDIvol was estimated using the ImPACT CTDI dosimetry tables. Histograms of CTDIvol values were created for each year, and descriptive statistics, including mean, median, and 75th percentile, were reported. Repeated-measures ANOVA was performed to determine whether significant differences occurred between reporting years. RESULTS: A wide range of technical parameters was reported, most notably in tube current. Between 2010 and 2014, the median CTDIvol ranged from 4.9 to 6.2 mGy and the 75th percentile from 9.7 to 10.2 mGy. There was no significant change in CTDIvol between reporting years (repeated-measures ANOVA, P = 0.985). CONCLUSION: The 75th percentile CTDIvol reported in this work was 9.8 mGy averaged over all reporting years. These data provide a resource for establishing CTDIvol reference values specific to performing CT in PET/CT whole-body examinations. The wide ranges of CT acquisition parameters reported by sites suggest that CTDIvol reference levels may be beneficial for optimization of CT protocols.

Spatiotemporal stability of Cu-ATSM and FLT positron emission tomography distributions during radiation therapy.

PURPOSE: In dose painting, in which functional imaging is used to define biological targets for radiation therapy dose escalation, changes in spatial distributions of biological properties during treatment can compromise the quality of therapy. The goal of this study was to assess the spatiotemporal stability of 2 potential dose painting targets--hypoxia and proliferation--in canine tumors during radiation therapy. METHODS AND MATERIALS: Twenty-two canine patients with sinonasal tumors (14 carcinoma and 8 sarcoma) were imaged before hypofractionated radiation therapy with copper(II)-diacetyl-bis(N4-methylthiosemicarbazone) (Cu-ATSM) positron emission tomography/computed tomography (PET/CT) for hypoxia and 3'-deoxy-3'-(18)F-fluorothymidine (FLT) PET/CT for proliferation. The FLT scans were repeated after 2 fractions and the Cu-ATSM scans after 3 fractions. Midtreatment PET/CT images were deformably registered to pretreatment PET/CT images. Voxel-based Spearman correlation coefficients quantified the spatial stability of Cu-ATSM and FLT uptake distributions between pretreatment and midtreatment scans. Paired t tests determined significant differences between the patients' respective Cu-ATSM and FLT correlations coefficients. Standardized uptake value measures were also compared between pretreatment and midtreatment scans by use of paired t tests. RESULTS: Spatial distributions of Cu-ATSM and FLT uptake were stable through midtreatment for both sarcomas and carcinomas: the population mean ± standard deviation in Spearman correlation coefficient was 0.88 ± 0.07 for Cu-ATSM and 0.79 ± 0.13 for FLT. The patients' Cu-ATSM correlation coefficients were significantly higher than their respective FLT correlation coefficients (P=.001). Changes in Cu-ATSM SUV measures from pretreatment to midtreatment were histology dependent: carcinomas experienced significant decreases in Cu-ATSM uptake (P<.05), whereas sarcomas did not (P>.20). Both histologies experienced significant decreases in FLT uptake (P<.05). CONCLUSIONS: Spatial distributions of Cu-ATSM were very stable after a few fractions of radiation therapy. FLT spatial distributions were generally stable early in therapy, although they were significantly less stable than Cu-ATSM distributions. Canine tumors had significantly lower proliferative activity at midtreatment than at pretreatment, and they experienced histology-dependent changes in Cu-ATSM uptake.

Heterogeneity in intratumor correlations of 18F-FDG, 18F-FLT, and 61Cu-ATSM PET in canine sinonasal tumors.

UNLABELLED: Intratumor heterogeneity in biologic properties and in relationships between various phenotypes may present a challenge for biologically targeted therapies. Understanding the relationships between different phenotypes in individual tumor types could help inform treatment selection. The goal of this study was to characterize spatial correlations of glucose metabolism, proliferation, and hypoxia in 2 histologic types of tumors. METHODS: Twenty canine veterinary patients with spontaneously occurring sinonasal tumors (13 carcinomas and 7 sarcomas) were imaged with (18)F-FDG, (18)F-labeled 3'-deoxy-3'-fluorothymidine ((18)F-FLT), and (61)Cu-labeled diacetyl-bis(N(4)-methylthiosemicarbazone) ((61)Cu-ATSM) PET/CT on 3 consecutive days. Precise positioning and immobilization techniques coupled with anesthesia enabled motionless scans with repeatable positioning. Standardized uptake values (SUVs) of gross sarcoma and carcinoma volumes were compared by use of Mann-Whitney U tests. Patient images were rigidly registered together, and intratumor tracer uptake distributions were compared. Voxel-based Spearman correlation coefficients were used to quantify intertracer correlations, and the correlation coefficients of sarcomas and carcinomas were compared. The relative overlap of the highest uptake volumes of the 3 tracers was quantified, and the values were compared for sarcomas and carcinomas. RESULTS: Large degrees of heterogeneity in SUV measures and phenotype correlations were observed. Carcinoma and sarcoma tumors differed significantly in SUV measures, with carcinoma tumors having significantly higher (18)F-FDG maximum SUVs than sarcoma tumors (11.1 vs. 5.0; P = 0.01) as well as higher (61)Cu-ATSM mean SUVs (2.6 vs. 1.2; P = 0.02). Carcinomas had significantly higher population-averaged Spearman correlation coefficients than sarcomas in comparisons of (18)F-FDG and (18)F-FLT (0.80 vs. 0.61; P = 0.02), (18)F-FLT and (61)Cu-ATSM (0.83 vs. 0.38; P < 0.0001), and (18)F-FDG and (61)Cu-ATSM (0.82 vs. 0.69; P = 0.04). Additionally, the highest uptake volumes of the 3 tracers had significantly greater overlap in carcinomas than in sarcomas. CONCLUSION: The relationships of glucose metabolism, proliferation, and hypoxia were heterogeneous across different tumors, with carcinomas tending to have high correlations and sarcomas having low correlations. Consequently, canine carcinoma tumors are robust targets for therapies that target a single biologic property, whereas sarcoma tumors may not be well suited for such therapies. Histology-specific PET correlations have far-reaching implications for the robustness of biologic target definition.

Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters.

BACKGROUND: Characterization of textural features (spatial distributions of image intensity levels) has been considered as a tool for automatic tumor segmentation. The purpose of this work is to study the variability of the textural features in PET images due to different acquisition modes and reconstruction parameters. MATERIAL AND METHODS: Twenty patients with solid tumors underwent PET/CT scans on a GE Discovery VCT scanner, 45-60 minutes post-injection of 10 mCi of [(18)F]FDG. Scans were acquired in both 2D and 3D modes. For each acquisition the raw PET data was reconstructed using five different reconstruction parameters. Lesions were segmented on a default image using the threshold of 40% of maximum SUV. Fifty different texture features were calculated inside the tumors. The range of variations of the features were calculated with respect to the average value. RESULTS: Fifty textural features were classified based on the range of variation in three categories: small, intermediate and large variability. Features with small variability (range ≤ 5%) were entropy-first order, energy, maximal correlation coefficient (second order feature) and low-gray level run emphasis (high-order feature). The features with intermediate variability (10% ≤ range ≤ 25%) were entropy-GLCM, sum entropy, high gray level run emphsis, gray level non-uniformity, small number emphasis, and entropy-NGL. Forty remaining features presented large variations (range > 30%). CONCLUSION: Textural features such as entropy-first order, energy, maximal correlation coefficient, and low-gray level run emphasis exhibited small variations due to different acquisition modes and reconstruction parameters. Features with low level of variations are better candidates for reproducible tumor segmentation. Even though features such as contrast-NGTD, coarseness, homogeneity, and busyness have been previously used, our data indicated that these features presented large variations, therefore they could not be considered as a good candidates for tumor segmentation.