Search Results (9)

Parkinsonian syndromes comprise overlapping neurodegenerative and non-degenerative disorders, making aetiological diagnosis difficult, while existing procedural guidance does not fully integrate tracer-specific biology with clinical decision-making, multimodal strategies, and emerging quantitative and pathology-directed biomarkers. This review synthesises evidence on the molecular targets, radiopharmaceutical characteristics, biological interpretation, and clinical applications of dopaminergic single-photon emission computed tomography (SPECT) and positron emission tomography (PET), focusing on the dopamine transporter (DAT), aromatic L-amino acid decarboxylase (AADC), vesicular monoamine transporter type 2 (VMAT2), dopamine D₂/D₃ receptors, differential diagnosis, semiquantification, kinetic modelling, and artificial intelligence-assisted interpretation. The evidence confirms that DAT SPECT with [¹²³I]ioflupane ([¹²³I]FP-CIT) remains the most established method for demonstrating or arguing against presynaptic nigrostriatal dysfunction, but an abnormal result cannot establish aetiology, and a normal result can redirect evaluation towards non-degenerative mimics; target-specific PET provides complementary biological information, although availability, standardisation, and prospective validation remain limiting. By additionally integrating genetic and prodromal applications, question-driven multimodal imaging, emerging acquisition approaches, α-synuclein imaging and seed amplification assays, and contemporary biological staging frameworks, this review extends procedural guidance and positions dopaminergic imaging as a targeted functional biomarker selected according to the unresolved clinical question rather than as a stand-alone disease label. Full article

Background/Objectives: Dementia with Lewy bodies (DLB) is a clinically heterogeneous neurodegenerative disorder characterized by cognitive, neuropsychiatric, motor, and autonomic manifestations. Reduced striatal dopamine transporter availability on ¹²³I-ioflupane single-photon emission computed tomography (SPECT) is an established indicative biomarker of DLB. However, the associations among expert visual interpretation, regional semiquantitative dopamine transporter measurements, autonomic manifestations, and dementia severity remain incompletely characterized. This study aimed to evaluate the relationship between visual ¹²³I-ioflupane SPECT classification and regional DaTQUANT z-scores in patients with clinically probable DLB and to explore their associations with autonomic manifestations and dementia severity. Methods: This retrospective, cross-sectional study included 30 patients who received a clinical diagnosis of probable DLB according to the 2017 DLB Consortium criteria before the ¹²³I-ioflupane SPECT results became available. SPECT images were assessed visually by experienced nuclear medicine physicians and semiquantitatively using DaTQUANT software. Bilateral striatal, putaminal, caudate, and putamen-to-caudate ratio z-scores were analyzed in relation to visual scan classification, Clinical Dementia Rating (CDR) scores, and retrospectively ascertained autonomic manifestations, including orthostatic hypotension, delayed orthostatic hypotension, supine hypertension, postprandial hypotension, constipation, and urinary incontinence. Results: Scans were visually classified as supportive of nigrostriatal dopaminergic degeneration in 23 of 30 patients (76.7%) and as non-supportive in seven (23.3%). Bilateral striatal, putaminal, and caudate z-scores were significantly lower in visually supportive scans than in non-supportive scans (all p < 0.001), whereas putamen-to-caudate ratio z-scores did not differ significantly between the groups. None of the evaluated autonomic manifestations was significantly associated with either visual scan classification or regional DaTQUANT measurements. No regional DaTQUANT measurement was significantly associated with dementia severity. A modest positive correlation was observed between the left putamen-to-caudate ratio z-score and CDR (Spearman’s ρ = 0.373, nominal p = 0.050); however, given the small sample size and multiple regional comparisons, this borderline finding was considered exploratory. Conclusions: Regional DaTQUANT measurements were consistent with expert visual interpretation of ¹²³I-ioflupane SPECT in patients with clinically probable DLB. Associations of dopaminergic imaging measurements with autonomic manifestations and dementia severity were limited. Semiquantitative analysis may complement visual interpretation, but its findings should be interpreted within the broader clinical and biomarker context. Larger prospective studies incorporating standardized autonomic testing, appropriate control groups, longitudinal follow-up, and complementary biomarkers are warranted. Full article

Background: Differentiating Parkinson’s disease (PD) from essential tremor (ET) is often challenging, especially in early or atypical cases. Dopamine transporter (DAT) single-photon emission computed tomography (SPECT) with ¹²³I-Ioflupane supports diagnosis, and semi-quantitative tools such as DaTQUANT^® and BasGanV2™ provide objective measures. This study compared their diagnostic performance when integrated with supervised machine learning. Methods: We retrospectively analysed ¹²³I-Ioflupane SPECT scans from 169 patients (133 PD, 36 ET). Semi-quantitative analysis was performed using DaTQUANT^® v2.0 and BasGanV2™ v.2. Classification tree (ClT), k-nearest neighbour (k-NN), and support vector machine (SVM) models were trained and validated with stratified shuffle split (250 iterations). Diagnostic accuracy was compared between the two software packages. Results: All classifiers reliably distinguished PD from ET. DaTQUANT^® consistently achieved higher accuracy than BasGanV2™: 93.8%, 93.2%, and 94.5% for ClT, k-NN, and SVM, respectively, versus 90.9%, 91.7%, and 91.9% for BasGanV2™ (p < 0.001). Sensitivity and specificity were also consistently higher for DaTQUANT^® than BasGanV2. Class imbalance (PD > ET) was addressed using Synthetic Minority Over-sampling Technique (SMOTE). Conclusions: Machine learning analysis of ¹²³I-Ioflupane SPECT enhances differentiation between PD and ET. DaTQUANT^® outperformed BasGanV2™, suggesting greater suitability for AI-driven decision support. These findings support the integration of semi-quantitative and AI-based approaches into clinical workflows and highlight the need for harmonised methodologies in movement disorder imaging. Full article

Background: Quantitative thresholds are helpful to define an abnormal DaT SPECT in patients with suspected nigrostriatal degenerative diseases (NSDD). The optimal DaTQUANT threshold for diagnostic accuracy of DaT SPECT across combined movement and cognitive disorder populations has been previously described. Methods: We established optimal DaTQUANT thresholds that enhance the discrimination between dementia with Lewy bodies (DLB) and non-DLB dementia types, as well as between Parkinsonian syndromes (PS) and conditions not characterized by nigrostriatal degeneration (non-PS). Results: Data from a total of 303 patients were used in this retrospective analysis. Posterior putamen of the more affected hemisphere (MAH) was shown to be an accurate single-variable predictor for both DLB and PS and was comparable to the most accurate multi-variable models. Conclusions: Automated quantification with DaTQUANT can accurately aid in the differentiation of DLB from non-DLB dementias and PS from non-PS. Optimal thresholds for assisting a diagnosis of DLB are striatal binding ratio (SBR) ≤ 0.65, z-score ≤ −2.36, and a percent deviation ≤ −0.54 for the posterior putamen of the MAH. Optimal posterior putamen thresholds for assisting a diagnosis of PS are SBR ≤ 0.92, z-score ≤ −1.53, and a percent deviation ≤ −0.33, which are similar to our previously reported posterior putamen threshold values using a blended patient pool from multiple study populations. Full article

Background: Multiple system atrophy (MSA) is a neurodegenerative disease. It has a fast progression, so early diagnosis is decisive. Two functional imaging tests can be involved in its diagnosis: [¹²³I]Ioflupane SPECT and [¹²³I]MIBG scintigraphy. Our aim is to comparatively analyze the diagnostic performance of both techniques. Methods: 46 patients (24 males and 22 females) with MSA underwent [¹²³I]Ioflupane SPECT and [¹²³I]MIBG scintigraphy. In each of these techniques, qualitative assessment was compared with quantitative assessment. Results: SPECT visual assessment was positive in 93.5% of subjects (S = 95.24%; PPV = 93.02%). A cut-off of 1.363 was established for overall S/O index (S = 85.7%, E = 100%). Visual assessment of scintigraphy was positive in 73.1% (S = 78.57%, PPV = 94.29%). For the delayed heart/medistinum ratio (HMR) a cut-off of 1.43 (S = 85.3, E = 100%) was obtained. For each unit increase in delayed HMR, the suspicion of MSA increased by 1.58 (OR = 1.58, p < 0.05). The quantitative assessment showed an association with the visual assessment for each technique (p < 0.05). Conclusions: Both tests are useful in MSA diagnosis. Comparatively, we did not observe a clear superiority of either. Striatal and myocardial deterioration do not evolve in parallel. Qualitative assessment is crucial in both techniques, together with the support of quantitative analysis. Delayed HMR shows a direct relationship with the risk of MSA. Full article

Background: Multiple system atrophy (MSA) is subdivided into two types: MSA-P (parkinsonian) and MSA-C (cerebellar). Brain SPECT allows for the detection of nigrostriatal involvement, even in the early stages. To date, the scientific literature does not show a consensus on how to follow-up MSA, especially MSA-C. Our aim was to analyze the diagnostic effectiveness of repeat [¹²³I]Ioflupane SPECT for the follow-up of MSA. Methods: A longitudinal observational study on 22 MSA patients (11 males and 11 females). Results: Significant changes were obtained in the quantitative SPECT assessments in the three Striatum/Occipital indices. The qualitative SPECT diagnosis did not show differences between the initial and evolving SPECT, but the neurologist’s clinical suspicion did. Our results showed a brain deterioration of around 31% at 12 months, this being the optimal cut-off for differentiating a diseased subject (capable of solving diagnostic error rate). Previous imaging tests were inconclusive, as they showed less deterioration in the SPECT and quantitative assessments with respect to the group of confirmed patients. Repeated SPECT increased the diagnostic sensitivity (50% vs. 75%) and positive predictive value (72.73% vs. 77%). In addition, repeated SPECT proved decisive in the diagnosis of initial inconclusive cases. Conclusion: Repeat SPECT at 12 months proves useful in the diagnosis and follow-up of MSA. Full article

Background: Multiple system atrophy (MSA) is a rapidly progressive neurodegenerative disorder that has no curative treatment. Diagnosis is based on a set of criteria established by Gilman (1998 and 2008) and recently updated by Wenning (2022). We aim to determine the effectiveness of [¹²³I]Ioflupane SPECT in MSA, especially at the initial clinical suspicion. Methods: A cross-sectional study of patients at the initial clinical suspicion of MSA, referred for [¹²³I]Ioflupane SPECT. Results: Overall, 139 patients (68 men, 71 women) were included, 104 being MSA-probable and 35 MSA-possible. MRI was normal in 89.2%, while SPECT was positive in 78.45%. SPECT showed high sensitivity (82.46%) and positive predictive value (86.24), reaching maximum sensitivity in MSA-P (97.26%). Significant differences were found when relating both SPECT assessments in the healthy–sick and inconclusive–sick groups. We also found an association when relating SPECT to the subtype (MSA-C or MSA-P), as well as to the presence of parkinsonian symptoms. Lateralization of striatal involvement was detected (left side). Conclusions: [¹²³I]Ioflupane SPECT is a useful and reliable tool for diagnosing MSA, with good effectiveness and accuracy. Qualitative assessment shows a clear superiority when distinguishing between the healthy–sick categories, as well as between the parkinsonian (MSA-P) and cerebellar (MSA-C) subtypes at initial clinical suspicion. Full article

This study aimed to develop a new convolutional neural network (CNN) method for estimating the specific binding ratio (SBR) from only frontal projection images in single-photon emission-computed tomography using [¹²³I]ioflupane. We created five datasets to train two CNNs, LeNet and AlexNet: (1) 128FOV used a 0° projection image without preprocessing, (2) 40FOV used 0° projection images cropped to 40 × 40 pixels centered on the striatum, (3) 40FOV training data doubled by data augmentation (40FOV_DA, left-right reversal only), (4) 40FOVhalf, and (5) 40FOV_DAhalf, split into left and right (20 × 40) images of 40FOV and 40FOV_DA to separately evaluate the left and right SBR. The accuracy of the SBR estimation was assessed using the mean absolute error, root mean squared error, correlation coefficient, and slope. The 128FOV dataset had significantly larger absolute errors compared to all other datasets (p < 0. 05). The best correlation coefficient between the SBRs using SPECT images and those estimated from frontal projection images alone was 0.87. Clinical use of the new CNN method in this study was feasible for estimating the SBR with a small error rate using only the frontal projection images collected in a short time. Full article

A fully automatic method for specific binding ratio (SBR) calculation in [¹²³I]ioflupane single-photon emission computed tomography (SPECT) studies was proposed by creating volumes of interest of the striatum (VOI_st) and reference region (VOI_ref) without manual handling to avoid operator-induced variability. The study involved 105 patients (72 ± 10 years) suspected of parkinsonian syndrome (PS) who underwent [¹²³I]ioflupane SPECT. The 200 images from our previous study were used for evaluation and validation of the new program. All patients were classified into PS and non-PS groups according to the results of clinical follow-up. A trapezoidal volume of interest (VOI_t) containing all striatal intensive counts was created automatically, followed by VOI_st setting using the previous method. SBR values were calculated from the mean values of VOI_st and VOI_ref determined by the whole brain outside of VOI_t. The low count voxels in the VOI_ref were excluded using an appropriate threshold. The SBR values from the new method were compared with the previous semi-automatic method and the Tossici–Bolt (TB) method. The SBRs from the semi- and fully automatic methods showed a good linear correlation (r > 0.98). The areas under the curves (AUCs) of receiver operating characteristic analysis showed no significant difference between the two methods for both our previous (AUC > 0.99) and new (AUC > 0.95) data. The diagnostic accuracy of the two methods showed similar results (>92%), and both were better than the TB method. The proposed method successfully created the automatic VOIs and calculated SBR rapidly (9 ± 1 s/patient), avoiding operator-induced variability and providing objective SBR results. Full article