ACR-ACNM Practice Parameter for the Performance of Dopamine Transporter (DaT) Single Photon Emission Computed Tomography (SPECT) Imaging for Movement Disorders

Practical use of DAT SPECT imaging in diagnosing dementia with Lewy bodies: a US perspective of current guidelines and future directions

Background

Diagnosing Dementia with Lewy Bodies (DLB) remains a challenge in clinical practice. The use of 123I-ioflupane (DaTscan™) SPECT imaging, which detects reduced dopamine transporter (DAT) uptake-a key biomarker in DLB diagnosis-could improve diagnostic accuracy. However, DAT imaging is underutilized despite its potential, contributing to delays and suboptimal patient management.

Methods

This review evaluates DLB diagnostic practices and challenges faced within the U.S. by synthesizing information from current literature, consensus guidelines, expert opinions, and recent updates on DaTscan FDA filings. It contrasts DAT SPECT with alternative biomarkers, provides recommendations for when DAT SPECT imaging may be indicated and discusses the potential of emerging biomarkers in enhancing diagnostic approaches.

Results

The radiopharmaceutical 123I-ioflupane for SPECT imaging was initially approved in Europe (2000) and later in the US (2011) for Parkinsonism/Essential Tremor. Its application was extended in 2022 to include the diagnosis of DLB. DaTscan's diagnostic efficacy for DLB, with its sensitivity, specificity, and predictive values, confirms its clinical utility. However, US implementation faces challenges such as insurance barriers, costs, access issues, and regional availability disparities.

Conclusion

123I-ioflupane SPECT Imaging is indicated for DLB diagnosis and differential diagnosis of Alzheimer's Disease, particularly in uncertain cases. Addressing diagnostic obstacles and enhancing physician-patient education could improve and expedite DLB diagnosis. Collaborative efforts among neurologists, geriatric psychiatrists, psychologists, and memory clinic staff are key to increasing diagnostic accuracy and care in DLB management.

Practical Overview of 123I-Ioflupane Imaging in Parkinsonian Syndromes

Parkinsonian syndromes are a heterogeneous group of progressive neurodegenerative disorders involving the nigrostriatal dopaminergic pathway and are characterized by a wide spectrum of motor and nonmotor symptoms. These syndromes are quite common and can profoundly impact the lives of patients and their families. In addition to classic Parkinson disease, parkinsonian syndromes include multiple additional disorders known collectively as Parkinson-plus syndromes or atypical parkinsonism. These are characterized by the classic parkinsonian motor symptoms with additional distinguishing clinical features. Dopamine transporter SPECT has been developed as a diagnostic tool to assess the levels of dopamine transporters in the striatum. This imaging assessment, which uses iodine 123 (123I) ioflupane, can be useful to differentiate parkinsonian syndromes caused by nigrostriatal degeneration from other clinical mimics such as essential tremor or psychogenic tremor. Dopamine transporter imaging plays a crucial role in diagnosing parkinsonian syndromes, particularly in patients who do not clearly fulfill the clinical criteria for diagnosis. Diagnostic clarification can allow early treatment in appropriate patients and avoid misdiagnosis. At present, only the qualitative interpretation of dopamine transporter SPECT is approved by the U.S. Food and Drug Administration, but quantitative interpretation is often used to supplement qualitative interpretation. The authors provide an overview of patient preparation, common imaging findings, and potential pitfalls that radiologists and nuclear medicine physicians should know when performing and interpreting dopamine transporter examinations. Alternatives to 123I-ioflupane imaging for the evaluation of nigrostriatal degeneration are also briefly discussed. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Intenzo and Colarossi in this issue.

No impact of attenuation and scatter correction on the interpretation of dopamine transporter SPECT in patients with clinically uncertain parkinsonian syndrome

PURPOSE

The benefit from attenuation and scatter correction (ASC) of dopamine transporter (DAT)-SPECT for the detection of nigrostriatal degeneration in clinical routine is still a matter of debate. The current study evaluated the impact of ASC on visual interpretation and semi-quantitative analysis of DAT-SPECT in a large patient sample.

METHODS

One thousand seven hundred forty consecutive DAT-SPECT with 123I-FP-CIT from clinical routine were included retrospectively. SPECT images were reconstructed iteratively without and with ASC. Attenuation correction was based on uniform attenuation maps, scatter correction on simulation. All SPECT images were categorized with respect to the presence versus the absence of Parkinson-typical reduction of striatal 123I-FP-CIT uptake by three independent readers. Image reading was performed twice to assess intra-reader variability. The specific 123I-FP-CIT binding ratio (SBR) was used for automatic categorization, separately with and without ASC.

RESULTS

The mean proportion of cases with discrepant categorization by the same reader between the two reading sessions was practically the same without and with ASC, about 2.2%. The proportion of DAT-SPECT with discrepant categorization without versus with ASC by the same reader was 1.66% ± 0.50% (1.09-1.95%), not exceeding the benchmark of 2.2% from intra-reader variability. This also applied to automatic categorization of the DAT-SPECT images based on the putamen SBR (1.78% discrepant cases between without versus with ASC).

CONCLUSION

Given the large sample size, the current findings provide strong evidence against a relevant impact of ASC with uniform attenuation and simulation-based scatter correction on the clinical utility of DAT-SPECT to detect nigrostriatal degeneration in patients with clinically uncertain parkinsonian syndrome.

Novel nested patch-based feature extraction model for automated Parkinson's Disease symptom classification using MRI images

OBJECTIVE

Parkinson's disease (PD) is a common neurological disorder with variable clinical manifestations and magnetic resonance imaging (MRI) findings. We propose a handcrafted image classification model that can accurately (i) classify different PD stages, (ii) detect comorbid dementia, and (iii) discriminate PD-related motor symptoms.

METHODS

Selected image datasets from three PD studies were used to develop the classification model. Our proposed novel automated system was developed in four phases: (i) texture features are extracted from the non-fixed size patches. In the feature extraction phase, a pyramid histogram-oriented gradient (PHOG) image descriptor is used. (ii) In the feature selection phase, four feature selectors: neighborhood component analysis (NCA), Chi2, minimum redundancy maximum relevancy (mRMR), and ReliefF are used to generate four feature vectors. (iii) Two classifiers: k-nearest neighbor (kNN) and support vector machine (SVM) are used in the classification step. A ten-fold cross-validation technique is used to validate the results. (iv) Eight predicted vectors are generated using four selected feature vectors and two classifiers. Finally, iterative majority voting (IMV) is used to attain general classification results. Therefore, this model is named nested patch-PHOG-multiple feature selectors and multiple classifiers-IMV (NP-PHOG-MFSMCIMV).

RESULTS

Our presented NP-PHOG-MFSMCIMV model achieved 99.22, 98.70, and 99.53% accuracies for the collected PD stages, PD dementia, and PD symptoms classification datasets, respectively.

SIGNIFICANCE

The obtained accuracies (over 98% for all states) demonstrated the performance of developed NP-PHOG-MFSMCIMV model in automated PD state classification.

Practical Application of DaTQUANT with Optimal Threshold for Diagnostic Accuracy of Dopamine Transporter SPECT

Evaluation of Parkinsonian Syndromes (PS) with Ioflupane iodine-123 dopamine transporter single photon emission computed tomography (DaT-SPECT), in conjunction with history and clinical examination, aids in diagnosis. FDA-approved, semi-quantitative software, DaTQUANT^TM (GE Healthcare, Chicago, IL, USA) is available to assist in interpretation. This study aims to evaluate the optimal variables and thresholds of DaTQUANT to yield the optimal diagnostic accuracy. It is a retrospective review with three different patient populations. DaT-SPECT images from all three study groups were evaluated using DaTQUANT^TM software, and both single and multi-variable logistic regression were used to model PS status. The optimal models were chosen via accuracy, sensitivity, and specificity, then evaluated on the other study groups. Among single variable models, the posterior putamen yielded the highest accuracy (84% to 95%), while balancing sensitivity and specificity. Multi-variable models did not substantially improve the accuracy. When the optimal single variable models for each group were used to evaluate the remaining two groups, comparable results were achieved. In typical utilization of DaT-SPECT for differentiation between nigrostriatal degenerative disease (NSDD) and non-NSDD, the posterior putamen was the single variable that yielded the highest accuracy across three different patient populations. The posterior putamen’s recommended thresholds for DaTQUANT are SBR ≤ 1.0, z-score of ≤−1.8 and percent deviation ≤ −0.34.

Dopamine transporter SPECT imaging in Parkinson’s disease and parkinsonian disorders

The dopamine transporter (DAT) imaging provides an objective tool for the assessment of dopaminergic function of presynaptic terminals which is valuable for the differential diagnosis of parkinsonian disorders related to a striatal dopaminergic deficiency from movement disorders not related a striatal dopaminergic deficiency. DAT imaging with single-photon emission computed tomography (SPECT) can be used to confirm or exclude a diagnosis of dopamine deficient parkinsonism in cases where the diagnosis is unclear. It can also detect the dopaminergic dysfunction in presymptomatic subjects at risk for Parkinson’s disease (PD) since the reduced radiotracer binding to DATs in striatum is already present in the prodromal stage of PD. This review covers the rationale of using DAT SPECT imaging in the diagnosis of PD and other parkinsonian disorders, specifically focusing on the practical aspects of imaging and routine clinical indications.

Evaluation of a variable-aperture full-ring SPECT system using large-area pixelated CZT modules: A simulation study for brain SPECT applications

PURPOSE

Single photon emission computed tomography (SPECT) scanners using cadmium zinc telluride (CZT) offer compact, lightweight, and improved imaging capability over conventional NaI(Tl)-based SPECT scanners. The main purpose in this study is to propose a full-ring SPECT system design with eight large-area CZT detectors that can be used for a broad spectrum of SPECT radiopharmaceuticals and demonstrate the performance of our system in comparison to the reference conventional NaI(Tl)-based two-head Anger cameras.

METHODS

A newly designed full-ring SPECT system is composed of eight large-area CZT cameras (128 mm × 179.2 mm effective area) that can be independently swiveled around their own axes of rotation independently and can have radial motion for varying aperture sizes that can be adapted to different sizes of imaging volume. Extended projection data were generated by conjoining projections of two adjacent detectors to overcome the limited field-of-view (FOV) by each CZT camera. Using Monte Carlo simulations, we evaluated this new system design with digital phantoms including a Derenzo hot rod phantom and a Zubal brain phantom. Comparison of performance metrics such as spatial resolution, sensitivity, contrast-to-noise ratio (CNR), and contrast-recovery ratio was made between our design and conventional SPECT scanners having different pixel sizes and radii of rotation (one clinically well-known type and two arbitrary types matched to our proposed CZT-SPECT geometries).

RESULTS

The proposed scanner could result in up to about three times faster in acquisition time over conventional scan time at same acquisition time per step. The spatial resolution improvement, or deterioration, of our proposed scanner compared to the clinical-type scanner was dependent upon the location of the point source. However, there were overall performance improvements over the three different setups of the conventional scanner particularly in volume sensitivity (approximately up to 1.7 times). Overall, we successfully reconstructed the phantom image for both ^99m Tc-based perfusion and ¹²³ I-based dopamine transporter (DaT) brain studies simulated for our new design. In particular, the striatal/background contrast-recovery ratio in 3-to-1 reference ratio was over 0.8 for the ¹²³ I-based DaT study.

CONCLUSIONS

We proposed a variable-aperture full-ring SPECT system using combined pixelated CZT and energy-optimized parallel-hole collimator modules and evaluated the performance of this scanner using relevant digital phantoms and MC simulations. Our studies demonstrated the potential of our new full-ring CZT-SPECT design, showing reduced acquisition time and improved sensitivity with acceptable CNR and spatial resolution.

Going against the norm: validation of a novel alternative to brain SPECT normative datasets

Aim: Quantitative analysis of brain single photon emission computed tomography (SPECT) perfusion imaging is dependent on normative datasets that are challenging to produce. This study investigated the combination of SPECT neuroimaging from a large clinical population rather than small numbers of controls. The authors hypothesized this “population template” would demonstrate noninferiority to a control dataset, providing a viable alternative for quantifying perfusion abnormalities in SPECT neuroimaging. Methods: A total of 2, 068 clinical SPECT scans were averaged to form the “population template”. Validation was three-fold. First, the template was imported into SPECT brain analysis software, MIMneuro®, and compared against its control dataset of 90 individuals through its region and cluster analysis tools. Second, a cohort of 100 cognitively impaired subjects was evaluated against both the population template and MIMneuro®’s normative dataset to compute region-based metrics. Concordance and intraclass correlation coefficients, mean square deviations, total deviation indices, and limits of agreement were derived from these data to measure agreement and test for noninferiority. Finally, the same patients were clinically read in CereMetrix® to confirm that expected perfusion patterns appeared after comparison to the template. Results: MIMneuro®’s default threshold for normality is ± 1.65 z-score and this served as our noninferiority margin. Direct comparison of the template to controls produced no regions that exceeded this threshold and all clusters identified were far from statistically significant. Agreement measures revealed consistency between the softwares and that CereMetrix® results were noninferior to MIMneuro®, albeit with proportional bias. Visual analysis also confirmed that expected perfusion patterns appeared when individual scans were compared to the population template within CereMetrix®. Conclusions: The authors demonstrated a population template was noninferior to a smaller control dataset despite inclusion of abnormal scans. This suggests that our patient-based population template can serve as an alternative for identifying and quantifying perfusion abnormalities in brain SPECT.

[Verification of Image Reconstruction Method and Collimator Suitable for Quantitative Analysis of Striatum in Dopamine Transporter Scintigraphy]

Specific binding ratio (SBR) is mainly used as a quantitative index of dopamine transporter scintigraphy, although it was reported that standardized uptake value (SUV) is useful for clinical diagnosis in recent years. The aim of this study is to evaluate whether xSPECT is useful for SUV in dopamine transporter scintigraphy. xSPECT is a recently developed, high-resolution image reconstruction technique that transforms single photon emission computed tomography (SPECT) to a computed tomography (CT) coordinate system. Furthermore, low-penetration high-resolution (LPHR), which there has been no previous physical evaluation report was also evaluated. The radioactive concentration of the image with xSPECT is automatically calculated by the periodic sensitivity calibration and one volume sensitivity calibration. In the case of images with conventional reconstruction methods as filtered back projection (FBP) and ordered subset expectation maximization (OSEM), the calibration factor related to the photon count and radioactive concentration was calculated from measuring a cylinder phantom filled with Iodine-123. Radioactive concentrations of the SUV factor were measured by SPECT data acquisition with the striatal phantom in various conditions. Radioactive concentrations with conventional reconstruction methods had a lower value (for example, with FBP it was 7.53 kBq/ml, with OSEM it was 7.22 kBq/ml) compared to the actual measurement value, although that with xSPECT (12.45 kBq/ml) got close to the actual measurement value (14.68 kBq/ml). LPHR showed an approximation to low-energy high-resolution (LEHR) in terms of spatial resolution and scatter fraction estimated from energy windows. The quantitative accuracy of radioactive concentration was the highest under xSPECT.

[Basic Evaluation of Standardized Uptake Value Using SPECT Single Unit to Compare with Specific Binding Ratio in Dopamine Transporter Scintigraphy]

Specific binding ratio (SBR) is mainly used as a quantitative index of dopamine transporter scintigraphy, nevertheless, the striatal volume which is influenced by individual differences and aging is calculated as a fixed value. Therefore, standardized uptake value (SUV) calculated with single photon emission computed tomography (SPECT) single unit was compared with SBR. A cylinder phantom filled with Iodine-123 was measured and the calibration factor (CF) was calculated from the count rate per volume. The conditions that SBR calculated using the striatal phantom and the radioactivity concentration calibrated and calculated by CF approximate the actual measured value were determined. There was a strong positive correlation between SBR and SUV with 16 clinical cases in Pearson's correlation coefficient (r>0.7). Moreover, a statistical analysis between the normal and diseased groups for SBR and SUV showed a significant difference (p<0.05). The area under the receiver operating characteristic curve (AUC) of SUV was 0.875, which was useful for clinical diagnosis; however, SBR had a higher diagnostic accuracy. SBR is considered to be suitable for quantitative analysis with SPECT single unit.