MR elastography in nonalcoholic fatty liver disease: inter-center and inter-analysis-method measurement reproducibility and accuracy at 3T.

OBJECTIVES: To assess reproducibility and fibrosis classification accuracy of magnetic resonance elastography (MRE)-determined liver stiffness measured manually at two different centers, and by automated analysis software in adults with nonalcoholic fatty liver disease (NAFLD), using histopathology as a reference standard. METHODS: This retrospective, cross-sectional study included 91 adults with NAFLD who underwent liver MRE and biopsy. MRE-determined liver stiffness was measured independently for this analysis by an image analyst at each of two centers using standardized manual analysis methodology, and separately by an automated analysis. Reproducibility was assessed pairwise by intraclass correlation coefficient (ICC) and Bland-Altman analysis. Diagnostic accuracy was assessed by receiver operating characteristic (ROC) analyses. RESULTS: ICC of liver stiffness measurements was 0.95 (95% CI: 0.93, 0.97) between center 1 and center 2 analysts, 0.96 (95% CI: 0.94, 0.97) between the center 1 analyst and automated analysis, and 0.94 (95% CI: 0.91, 0.96) between the center 2 analyst and automated analysis. Mean bias and 95% limits of agreement were 0.06 ± 0.38 kPa between center 1 and center 2 analysts, 0.05 ± 0.32 kPa between the center 1 analyst and automated analysis, and 0.11 ± 0.41 kPa between the center 2 analyst and automated analysis. The area under the ROC curves for the center 1 analyst, center 2 analyst, and automated analysis were 0.834, 0.833, and 0.847 for distinguishing fibrosis stage 0 vs. ≥ 1, and 0.939, 0.947, and 0.940 for distinguishing fibrosis stage ≤ 2 vs. ≥ 3. CONCLUSION: MRE-determined liver stiffness can be measured with high reproducibility and fibrosis classification accuracy at different centers and by an automated analysis. KEY POINTS: • Reproducibility of MRE liver stiffness measurements in adults with nonalcoholic fatty liver disease is high between two experienced centers and between manual and automated analysis methods. • Analysts at two centers had similar high diagnostic accuracy for distinguishing dichotomized fibrosis stages. • Automated analysis provides similar diagnostic accuracy as manual analysis for advanced fibrosis.

Assessment of agreement between manual and automated processing of liver MR elastography for shear stiffness estimation in children and young adults with autoimmune liver disease.

PURPOSE: To compare automated versus standard of care manual processing of 2D gradient recalled echo (GRE) liver MR Elastography (MRE) in children and young adults. MATERIALS AND METHODS: 2D GRE liver MRE data from research liver MRI examinations performed as part of an autoimmune liver disease registry between March 2017 and March 2020 were analyzed retrospectively. All liver MRE data were acquired at 1.5 T with 60 Hz mechanical vibration frequency. For manual processing, two independent readers (R1, R2) traced regions of interest on scanner generated shear stiffness maps. Automated processing was performed using MREplus+ (Resoundant Inc.) using 90% (A90) and 95% (A95) confidence masks. Agreement was evaluated using intra-class correlation coefficients (ICC) and Bland-Altman analyses. Classification performance was evaluated using receiver operating characteristic curve (ROC) analyses. RESULTS: In 65 patients with mean age of 15.5 ± 3.8 years (range 8-23 years; 35 males) median liver shear stiffness was 2.99 kPa (mean 3.55 ± 1.69 kPa). Inter-reader agreement for manual processing was very strong (ICC = 0.99, mean bias = 0.01 kPa [95% limits of agreement (LoA): - 0.41 to 0.44 kPa]). Correlation between manual and A95 automated processing was very strong (R1: ICC = 0.988, mean bias = 0.13 kPa [95% LoA: - 0.40 to 0.68 kPa]; R2: ICC = 0.987, mean bias = 0.13 kPa [95% LoA: - 0.44 to 0.69 kPa]). Automated measurements were perfectly replicable (ICC = 1.0; mean bias = 0 kPa). CONCLUSION: Liver shear stiffness values obtained using automated processing showed excellent agreement with manual processing. Automated processing of liver MRE was perfectly replicable.

Automated Analysis of Multiparametric Magnetic Resonance Imaging/Magnetic Resonance Elastography Exams for Prediction of Nonalcoholic Steatohepatitis.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) affects 25% of the global population. The standard of diagnosis, biopsy, is invasive and affected by sampling error and inter-reader variability. We hypothesized that widely available rapid MRI techniques could be used to predict nonalcoholic steatohepatitis (NASH) noninvasively by measuring liver stiffness, with magnetic resonance elastography (MRE), and liver fat, with chemical shift-encoded (CSE) MRI. Besides, we validate an automated image analysis technique to maximize the utility of these methods. PURPOSE: To implement and test an automated system for analyzing CSE-MRI and MRE data coupled with model-based prediction of NASH. STUDY TYPE: Prospective. SUBJECTS: Eighty-three patients with suspected NAFLD. FIELD STRENGTH/SEQUENCE: A 1.5 T using a flow-compensated motion-encoded gradient echo MRE sequence and a multiecho CSE-MRI sequence. ASSESSMENTS: The MRE and CSE-MRI data were analyzed by two readers (5+ and 1 years of experience) and an automated algorithm. A logistic regression model to predict pathology-diagnosed NASH was trained based on stiffness and proton density fat fraction, and the area under the receiver operating characteristic curve (AUROC) was calculated using 10-fold cross validation for models based on both automated and manual measurements. A separate model was trained to predict the NASH severity score (NAS). STATISTICAL TESTS: Pearson's correlation, Bland-Altman, AUROC, C-statistic. RESULTS: The agreement between automated measurements and the more experienced reader (R2  = 0.87 for stiffness and R2  = 0.99 for proton density fat fraction [PDFF]) was slightly better than the agreement between readers (R2  = 0.85 and 0.98). The model for predicting biopsy-diagnosed NASH had an AUROC of 0.87. The NAS-prediction model had a C-statistic of 0.85. DATA CONCLUSION: We demonstrated a workflow that used a limited MRI acquisition protocol and fully automated analysis to predict NASH with high accuracy. These methods show promise to provide a reliable noninvasive alternative to biopsy for NASH-screening in populations with NAFLD. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.

Magnetic Resonance Elastography in Primary Sclerosing Cholangitis: Interobserver Agreement for Liver Stiffness Measurement with Manual and Automated Methods.

RATIONALE AND OBJECTIVE: Primary sclerosing cholangitis, a chronic liver disease causes heterogeneous parenchymal changes and fibrosis. Liver stiffness measurement (LSM) with magnetic resonance Elastography (MRE) may be affected by this heterogeneous distribution. We evaluated interobserver agreement of LSM in primary sclerosing cholangitis (PSC) with manual and automated methods to study the influence of heterogeneous changes. MATERIALS AND METHODS: A total of 79 consecutive patients with PSC who had a liver MRI and MRE formed the study group. Three readers with 1-3 years' experience in MRE and a MRE expert (11 years' experience) independently performed LSM. Each reader manually drew free hand (fROI) and average (aROI) on stiffness maps. Automatic liver elasticity calculation (ALEC) was used to generate automated LSM. The expert fROI was the reference standard. Correlation analysis and absolute intra-class correlation coefficient (ICC) analysis was performed. RESULTS: LSM data of 79 livers and 315 sections were evaluated. There was excellent ICC between expert and reader fROIs (0.989, 95% confidence interval, and 0.985-0.993) and aROIs (0.971, 95% confidence interval, and 0.953-0.983) and ALEC (0.972, 0.957-0.982) with fROI performing better. The areas measured with fROIs and ALEC had moderate ICC with Expert fROI (0.64 and 0.56, respectively) whereas aROI area had a poor ICC of 0.12. Comparison of multiple methods showed significant differences in LSM between expert fROI and aROI of two readers and no significant differences for fROIs of all three readers. CONCLUSION: LSM with MRE in PSC patients shows excellent interobserver agreement with both fROI and aROI methods with better performance with fROI. fROI may therefore be preferred for LSM measurements in PSC.

Assessment of advanced hepatic MR elastography methods for susceptibility artifact suppression in clinical patients.

PURPOSE: To assess the success rate, image quality, and the ability to stage liver fibrosis of a standard 2D gradient-recalled echo (GRE) and four different spin-echo (SE) magnetic resonance elastography (MRE) sequences in patients with different liver iron concentrations. MATERIALS AND METHODS: A total of 332 patients who underwent 3T MRE examinations that included liver fat and iron quantification were enrolled, including 136 patients with all five MRE techniques. Thirty-four patients had biopsy results for fibrosis staging. The liver stiffness, region of interest area, image quality, and success rate of the five sequences were compared in 115/136 patients. The area under the receiver operating characteristic curves (AUCs) and the accuracies for diagnosing early-stage fibrosis and advanced fibrosis were compared. The effect of BMI (body mass index), the R2* relaxation time, and fat fraction on the image quality and liver stiffness measurements were analyzed. RESULTS: The success rates were significantly higher in the four SE sequences (99.1-100%) compared with GRE MRE (85.3%) (all P < 0.001). There were significant differences of the mean ROI area between every pair of sequences (all P < 0.0001). There were no significant differences in the AUC of the five MRE sequences for discriminating advanced fibrosis (10 P-values ranging from 0.2410-0.9171). R2* had a significant effect on the success rate and image quality for the noniron 2D echo-planar imaging (EPI), 3D EPI and 2D GRE (all P < 0.001) sequences. BMI had a significant effect on the iron 2D EPI (P = 0.0230) and iron 2D SE (P = 0.0040) sequences. CONCLUSION: All five techniques showed good diagnostic performance in staging liver fibrosis. The SE MRE sequences had higher success rates and better image quality than GRE MRE in 3T clinical hepatic imaging. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018;47:976-987.

Automated Liver Elasticity Calculation for 3D MRE.

Magnetic Resonance Elastography (MRE) is a phase-contrast MRI technique which calculates quantitative stiffness images, called elastograms, by imaging the propagation of acoustic waves in tissues. It is used clinically to diagnose liver fibrosis. Automated analysis of MRE is difficult as the corresponding MRI magnitude images (which contain anatomical information) are affected by intensity inhomogeneity, motion artifact, and poor tissue- and edge-contrast. Additionally, areas with low wave amplitude must be excluded. An automated algorithm has already been successfully developed and validated for clinical 2D MRE. 3D MRE acquires substantially more data and, due to accelerated acquisition, has exacerbated image artifacts. Also, the current 3D MRE processing does not yield a confidence map to indicate MRE wave quality and guide ROI selection, as is the case in 2D. In this study, extension of the 2D automated method, with a simple wave-amplitude metric, was developed and validated against an expert reader in a set of 57 patient exams with both 2D and 3D MRE. The stiffness discrepancy with the expert for 3D MRE was -0.8% ± 9.45% and was better than discrepancy with the same reader for 2D MRE (-3.2% ± 10.43%), and better than the inter-reader discrepancy observed in previous studies. There were no automated processing failures in this dataset. Thus, the automated liver elasticity calculation (ALEC) algorithm is able to calculate stiffness from 3D MRE data with minimal bias and good precision, while enabling stiffness measurements to be fully reproducible and to be easily performed on the large 3D MRE datasets.

Magnetic resonance elastography measured shear stiffness as a biomarker of fibrosis in pediatric nonalcoholic fatty liver disease.

Magnetic resonance elastography (MRE) is a promising technique for noninvasive assessment of fibrosis, a major determinant of outcome in nonalcoholic fatty liver disease (NAFLD). However, data in children are limited. The purpose of this study was to determine the accuracy of MRE for the detection of fibrosis and advanced fibrosis in children with NAFLD and to assess agreement between manual and novel automated reading methods. We performed a prospective, multicenter study of two-dimensional (2D) MRE in children with NAFLD. MR elastograms were analyzed manually at two reading centers, and using a new automated technique. Analysis using each approach was done independently. Correlations were determined between MRE analysis methods and fibrosis stage. Thresholds for classifying the presence of fibrosis and of advanced fibrosis were computed and cross-validated. In 90 children with a mean age of 13.1 ± 2.4 years, median hepatic stiffness was 2.35 kPa. Stiffness values derived by each reading center were strongly correlated with each other (r = 0.83). All three analyses were significantly correlated with fibrosis stage (center 1, ρ = 0.53; center 2, ρ = 0.55; and automated analysis, ρ = 0.52; P < 0.001). Overall cross-validated accuracy for detecting any fibrosis was 72.2% for all methods (95% confidence interval [CI], 61.8%-81.1%). Overall cross-validated accuracy for assessing advanced fibrosis was 88.9% (95% CI, 80.5%-94.5%) for center 1, 90.0% (95% CI, 81.9%-95.3%) for center 2, and 86.7% (95% CI, 77.9%-92.9%) for automated analysis. CONCLUSION: 2D MRE can estimate hepatic stiffness in children with NAFLD. Further refinement and validation of automated analysis techniques will be an important step in standardizing MRE. How to best integrate MRE into clinical protocols for the assessment of NAFLD in children will require prospective evaluation. (Hepatology 2017;66:1474-1485).

Application of Modified Spin-Echo-based Sequences for Hepatic MR Elastography: Evaluation, Comparison with the Conventional Gradient-Echo Sequence, and Preliminary Clinical Experience.

Purpose To (a) evaluate modified spin-echo (SE) magnetic resonance (MR) elastographic sequences for acquiring MR images with improved signal-to-noise ratio (SNR) in patients in whom the standard gradient-echo (GRE) MR elastographic sequence yields low hepatic signal intensity and (b) compare the stiffness values obtained with these sequences with those obtained with the conventional GRE sequence. Materials and Methods This HIPAA-compliant retrospective study was approved by the institutional review board; the requirement to obtain informed consent was waived. Data obtained with modified SE and SE echo-planar imaging (EPI) MR elastographic pulse sequences with short echo times were compared with those obtained with the conventional GRE MR elastographic sequence in two patient cohorts, one that exhibited adequate liver signal intensity and one that exhibited low liver signal intensity. Shear stiffness values obtained with the three sequences in 130 patients with successful GRE-based examinations were retrospectively tested for statistical equivalence by using a 5% margin. In 47 patients in whom GRE examinations were considered to have failed because of low SNR, the SNR and confidence level with the SE-based sequences were compared with those with the GRE sequence. Results The results of this study helped confirm the equivalence of SE MR elastography and SE-EPI MR elastography to GRE MR elastography (P = .0212 and P = .0001, respectively). The SE and SE-EPI MR elastographic sequences provided substantially improved SNR and stiffness inversion confidence level in 47 patients in whom GRE MR elastography had failed. Conclusion Modified SE-based MR elastographic sequences provide higher SNR MR elastographic data and reliable stiffness measurements; thus, they enable quantification of stiffness in patients in whom the conventional GRE MR elastographic sequence failed owing to low signal intensity. The equivalence of the three sequences indicates that the current diagnostic thresholds are applicable to SE MR elastographic sequences for assessing liver fibrosis. © RSNA, 2016.

Automated liver elasticity calculation for MR elastography.

PURPOSE: MR elastography (MRE) is a phase-contrast MRI technique that is used to quantitatively assess liver stiffness for staging hepatic fibrosis. The current approach requires manual selection of a region of interest (ROI) with good wave quality from which to measure stiffness. The purpose of this work was to develop and evaluate a fully automated approach for measuring hepatic stiffness from MRE images to further reduce measurement variability. MATERIALS AND METHODS: An automated liver elasticity calculation (ALEC) algorithm was developed to address reader stiffness measurement variability. ALEC has three stages: initial tissue estimation, segmentation, and ROI cleanup. Stiffnesses measured by the algorithm were compared with technicians and an expert radiologist in a set of 121 clinical cases acquired at 1.5 Tesla. Intra-class correlation (ICC), Bland-Altman analysis, and a noninferiority test were performed to evaluate whether the algorithm can be used in place of manual analysis by technicians. RESULTS: The stiffness measurement difference with the expert was 1.42% ± 11.17% (mean ± standard deviation) for the algorithm and 1.82% ± 13.65% for the technicians. The ICCs were 0.981 and 0.984, respectively. Both the algorithm and technicians were equivalent to the expert within a 5% significance margin (P < 0.01). The algorithm had no failures in the 119 cases that were considered analyzable by the human readers. CONCLUSION: The results of this study show that the newly developed automated algorithm is able to measure stiffness in clinical liver MRE exams with an accuracy that is equivalent to that of an expert radiologist. ALEC may be useful for analysis of archived data and suitable for performing multi-center studies.

Performance of magnetic resonance elastography in primary sclerosing cholangitis.

BACKGROUND AND AIM: Liver stiffness (LS) measured by magnetic resonance elastography (MRE) is emerging as an important biomarker in chronic liver diseases. We examined the diagnostic performance of MRE, factors associated with an increased LS and the prognostic value of LS as measured by MRE among patients with primary sclerosing cholangitis (PSC). METHODS: We performed a retrospective review of 266 patients with PSC to examine whether LS was associated with the primary endpoint of hepatic decompensation (ascites, variceal hemorrhage and hepatic encephalopathy). The ability of MRE to differentiate stages of fibrosis was examined in a subset of patients who underwent a liver biopsy (n = 20). RESULTS: An LS of 4.93 kPa was the optimal point to detected F4 fibrosis (sensitivity, 1.00; 95% confidence interval (CI), 0.40-1.00; specificity, 0.94; 95%CI, 0.68-1.00). While a serum alkaline phosphatase <1.5 times the upper limit of normal excluded the presence of advanced LS, it was not associated with the primary endpoint (hazard ratio, 0.26; 95%CI, 0.01-1.33). However, LS was associated with the development of decompensated liver disease (hazard ratio, 1.55; 95%CI, 1.41-1.70). The optimal LS thresholds that stratified patients at a low, medium and high risk for hepatic decompensation were <4.5, 4.5-6.0 and >6.0 kPa (respectively). CONCLUSION: Magnetic resonance elastography is able to detect cirrhosis with high specificity and an alkaline phosphatase <1.5 times the upper limit of normal makes the presence of advanced LS unlikely. Moreover, LS obtained by MRE is predictive of hepatic decompensation in PSC.

Evaluation of liver stiffness with magnetic resonance elastography in patients with constrictive pericarditis: Preliminary findings.

PURPOSE: To evaluate with magnetic resonance elastography (MRE) whether patients with constrictive pericarditis (CP) have increased hepatic stiffness. CP results in reduced pericardial compliance, ventricular interdependence, and right heart failure. Patients with untreated CP may develop liver fibrosis and ultimately cirrhosis due to chronic venous congestion. Chronic venous congestion ± fibrosis may lead to increased liver stiffness. MATERIALS AND METHODS: Prospectively, patients with suspected CP underwent 2D transthoracic echocardiography, cardiac MRI, and liver MRE. An automated method was used to draw regions of interest (ROIs) on the stiffness maps to calculate the mean liver stiffness in kilopascals (kPa). A t-test with α = 0.05 was performed between stiffness values of patients with positive and negative CP findings based on previously published echocardiography criteria. RESULTS: Nineteen patients met inclusion criteria with a mean ± standard deviation (SD) age of 51 ± 16 years. Nine patients (47%) had CP. Mean liver stiffness trended higher in patients with CP compared to those without CP (4.04 kPa vs. 2.46; P = 0.045). Liver stiffness correlated with MRI septal bounce (P = 0.04), inferior vena cava size (P = 0.003), echo abnormal septal motion (P = 0.04), and echo mitral inflow variation >25% (P = 0.02). Only MRI septal bounce predicted CP by echocardiography (P < 0.001). CONCLUSION: CP was associated with increased liver stiffness. The increased stiffness is most likely secondary to chronic hepatic venous congestion and/or fibrosis. MRE may be useful for noninvasive liver stiffness assessment in CP. J. Magn. Reson. Imaging 2016;44:81-88.

MR elastography for the assessment of hepatic fibrosis in patients with chronic hepatitis B infection: does histologic necroinflammation influence the measurement of hepatic stiffness?

PURPOSE: To determine the diagnostic performance of magnetic resonance (MR) elastography for the staging of hepatic fibrosis and to evaluate the influence of necroinflammation on hepatic stiffness in patients with chronic hepatitis B virus (HBV) infection by using histopathologic findings as the reference standard. MATERIALS AND METHODS: One hundred thirteen consecutive patients with chronic HBV infection were recruited prospectively in this institutional review board-approved study after providing written informed consent between March 2012 and October 2013. The stiffness measurements were obtained by using two-dimensional gradient-echo MR elastography with a 3.0-T MR system. The METAVIR scoring system was used for the assessment of fibrosis ("F" stage) and necroinflammation ("A" grade). The predictive ability of MR elastography was evaluated by using the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC). Multiple linear regression analyses were conducted to determine the relationship between hepatic stiffness and the variables that showed a significant association in the univariate analysis or those that were of interest for comparison with earlier work (histologic scores, sex, age, aspartate aminotransferase level, and aspartate aminotransferase/alanine aminotransferase ratio). RESULTS: MR elastography showed excellent performance for characterization of ≥ F1, ≥ F2, ≥ F3, and F4 findings, with AUC values of 0.961, 0.986, 1.000, and 0.998, respectively. It showed a moderate capability for evaluation of necroinflammatory activity of ≥ A1, ≥ A2, and A3 (AUC = 0.806, 0.834, and 0.906, respectively). Multiple linear regression analysis showed that fibrosis, necroinflammation, and sex were independently associated with hepatic stiffness (ß = 0.799, 0.277, and 0.070, respectively; P < .05). For pairwise comparisons, log-transformed hepatic stiffness showed no difference between (a) groups F0/A2-3 and F1/A0-1 and (b) groups F1/A2-3 and F2/A0-1 (P > .99 and P = .486, respectively). CONCLUSION: MR elastography demonstrated excellent performance for distinguishing the stages of hepatic fibrosis in patients with chronic HBV infection. For hepatic tissue with ≤ F2 fibrosis, necroinflammation can account for a substantial fraction of the increase in hepatic stiffness.

Automated liver stiffness measurements with magnetic resonance elastography.

PURPOSE: To provide a fully automated algorithm for obtaining stiffness measurements from hepatic magnetic resonance elastography (MRE) images that are consistent with measurements performed by expert readers. MATERIALS AND METHODS: An initial liver contour was found using an adaptive threshold and expanded using an active contour to select a homogeneous area of the liver. The confidence map generated during the stiffness calculation was used to select a region of reliable wave propagation. The average stiffness within the automatically generated region of interest (ROI) was compared to measurements by two trained readers in a set of 88 clinical test cases ranging from healthy to severely fibrotic. RESULTS: The stiffness measurements reported by the readers differed by -6.76% ± 22.8% (95% confidence) and had an intraclass correlation coefficient (ICC) of 0.972 (P < 0.05). The algorithm and the more experienced reader differed by 4.32% ± 14.9 with an ICC of 0.987. CONCLUSION: The automated algorithm performed reliably, even though MRE acquisitions often have motion artifacts present. The correlation between the automated measurements and those from the trained readers was superior to the correlation between the readers.

Stable Automated Segmentation of Liver MR Elastography Images for Clinical Stiffness Measurement.

Magnetic Resonance Elastography (MRE) is an MRI-based technique that is used for the clinical diagnosis and staging of liver fibrosis by quantitatively measuring the stiffness of the liver. Due to the complexity of the signal characteristics and the presence of artifacts both in the acquired images and in the resulting stiffness images, the selection of the ROI for the stiffness measurement is currently performed manually, which may lead to significant inter- and intrareader variability. An algorithm has been developed to fully automate this analysis for liver MRE images. Automated segmentation of liver MRE images is challenging due to signal inhomogeneity, low contrast, and variability in patient anatomy. An initial liver contour is found by fitting Gaussian peaks to the image histogram and selecting the peak that comprises intensities in the expected range and produces a mask near the expected location of the liver. After correction to reduce intensity inhomogeneity, an active contour based on intensity, with morphology used to implicitly enforce smoothness, is used to segment liver tissue while avoiding blood vessels. The resulting mask is used to initialize another segmentation which splits the region of the elastogram belonging to the liver into homogeneous liver tissue and areas with inclusions, partial volume effects, and artifacts. In a set of 88 cases the algorithm had a -6.0 ± 14.2% stiffness difference from an experienced reader, which was superior to the 6.8 ± 22.8% difference between two readers. The segmentation was run on an additional 200 cases and the final ROIs were subjectively rated by a radiologist. The ROIs in 98% of cases received an average rating of "good" or "acceptable."

A CCD based approach to collimated photon counting imaging for micro-SPECT/CT.

Analog summation methods of x-ray imaging have nonlinearity in signal readout and dynamic range limitations. To minimize these limitations, a photon counting CCD-based gamma camera imaging system has been developed and evaluated.