No difference in striatal dopamine transporter availability between active smokers, ex-smokers and non-smokers using [123I]FP-CIT (DaTSCAN) and SPECT

Background: Mesolimbic and nigrostriatal dopaminergic pathways play important roles in both the rewarding and conditioning effects of drugs. The dopamine transporter (DAT) is of central importance in regulating dopaminergic neurotransmission and in particular in activating the striatal D2-like receptors. Molecular imaging studies of the relationship between DAT availability/dopamine synthesis capacity and active cigarette smoking have shown conflicting results. Through the collaboration between 13 SPECT centres located in 10 different European countries, a database of FP-CIT-binding in healthy controls was established. We used the database to test the hypothesis that striatal DAT availability is changed in active smokers compared to non-smokers and ex-smokers. Methods: A total of 129 healthy volunteers were included. Subjects were divided into three categories according to past and present tobacco smoking: (1) non-smokers (n = 64), (2) ex-smokers (n = 39) and (3) active smokers (n = 26). For imaging of the DAT availability, we used [123I]FP-CIT (DaTSCAN) and single photon emission computed tomography (SPECT). Data were collected in collaboration between 13 SPECT centres located in 10 different European countries. The striatal measure of DAT availability was analyzed in a multiple regression model with age, SPECT centre and smoking as predictor. Results: There was no statistically significant difference in DAT availability between the groups of active smokers, ex-smokers and non-smokers (p = 0.34). Further, we could not demonstrate a significant association between striatal DAT and the number of cigarettes per day or total lifetime cigarette packages in smokers and ex-smokers. Conclusion: Our results do not support the hypothesis that large differences in striatal DAT availability are present in smokers compared to ex-smokers and healthy volunteers with no history of smoking

Reduction in camera-specific variability in [123I]FP-CIT SPECT outcome measures by image reconstruction optimized for multisite settings: impact on age-dependence of the specific binding ratio in the ENC-DAT database of healthy controls

Purpose Quantitative estimates of dopamine transporter availability, determined with [123I]FP-CIT SPECT, depend on the SPECT equipment, including both hardware and (reconstruction) software, which limits their use in multicentre research and clinical routine. This study tested a dedicated reconstruction algorithm for its ability to reduce camera-specific intersubject variability in [123I]FP-CIT SPECT. The secondary aim was to evaluate binding in whole brain (excluding striatum) as a reference for quantitative analysis. Methods Of 73 healthy subjects from the European Normal Control Database of [123I]FP-CIT recruited at six centres, 70 aged between 20 and 82 years were included. SPECT images were reconstructed using the QSPECT software package which provides fully automated detection of the outer contour of the head, camera-specific correction for scatter and septal penetration by transmission-dependent convolution subtraction, iterative OSEMreconstruction including attenuation correction, and camera-specific Bto kBq/ml^ calibration. LINK and HERMES reconstruction were used for head-to-head comparison. The specific striatal [123I]FP-CIT binding ratio (SBR) was computed using the Southampton method with binding in the whole brain, occipital cortex or cerebellum as the reference. The correlation between SBR and age was used as the primary quality measure. Results The fraction of SBR variability explained by age was highest (1) with QSPECT, independently of the reference region, and (2) with whole brain as the reference, independently of the reconstruction algorithm. Conclusion QSPECT reconstruction appears to be useful for reduction of camera-specific intersubject variability of [123I]FP-CIT SPECT in multisite and single-site multicamera settings. Whole brain excluding striatal binding as the reference provides more stable quantitative estimates than occipital or cerebellar binding

Comparison of machine learning and semi-quantification algorithms for (I123)FP-CIT classification: the beginning of the end for semi-quantification?

Background Semi-quantification methods are well established in the clinic for assisted reporting of (I123) Ioflupane images. Arguably, these are limited diagnostic tools. Recent research has demonstrated the potential for improved classification performance offered by machine learning algorithms. A direct comparison between methods is required to establish whether a move towards widespread clinical adoption of machine learning algorithms is justified. This study compared three machine learning algorithms with that of a range of semi-quantification methods, using the Parkinson’s Progression Markers Initiative (PPMI) research database and a locally derived clinical database for validation. Machine learning algorithms were based on support vector machine classifiers with three different sets of features: Voxel intensities Principal components of image voxel intensities Striatal binding radios from the putamen and caudate. Semi-quantification methods were based on striatal binding ratios (SBRs) from both putamina, with and without consideration of the caudates. Normal limits for the SBRs were defined through four different methods: Minimum of age-matched controls Mean minus 1/1.5/2 standard deviations from age-matched controls Linear regression of normal patient data against age (minus 1/1.5/2 standard errors) Selection of the optimum operating point on the receiver operator characteristic curve from normal and abnormal training data Each machine learning and semi-quantification technique was evaluated with stratified, nested 10-fold cross-validation, repeated 10 times. Results The mean accuracy of the semi-quantitative methods for classification of local data into Parkinsonian and non-Parkinsonian groups varied from 0.78 to 0.87, contrasting with 0.89 to 0.95 for classifying PPMI data into healthy controls and Parkinson’s disease groups. The machine learning algorithms gave mean accuracies between 0.88 to 0.92 and 0.95 to 0.97 for local and PPMI data respectively. Conclusions Classification performance was lower for the local database than the research database for both semi-quantitative and machine learning algorithms. However, for both databases, the machine learning methods generated equal or higher mean accuracies (with lower variance) than any of the semi-quantification approaches. The gain in performance from using machine learning algorithms as compared to semi-quantification was relatively small and may be insufficient, when considered in isolation, to offer significant advantages in the clinical context

The impact of regional 99mTc-HMPAO single-photon-emission computed tomography (SPECT) imaging on clinician diagnostic confidence in a mixed cognitive impairment sample

AIM:To assess the clinical impact of regional cerebral blood flow (rCBF) single-photon-emission computed tomography (SPECT) imaging on diagnosis and clinician diagnostic confidence in a cohort of individuals with cognitive impairment. MATERIALS AND METHODS:Forty-one clinicians who referred 79 patients for a [99mTc]-hexamethylpropyleneamine oxime (HMPAO) SPECT for cognitive complaints completed a two-part questionnaire to determine the diagnosis and diagnostic confidence (using a 0-100 visual analogue scale [VAS]) before and after imaging. SPECT images were analysed using statistical parametric mapping and interpreted semi-quantitatively. Clinicians were also asked directly for their opinion on whether the imaging contributed to their diagnostic process. RESULTS:Diagnosis changed after imaging in 44% of cases, and confidence was significantly improved (VAS score change= +26.3±22.2) after imaging in cases where the pre-imaging confidence was low (p<0.001). Clinician confidence was not significantly different (VAS score change=-6.6±25.5) after imaging when pre-imaging confidence was moderate to high. Interestingly, a proportion of clinicians with the highest confidence levels became less certain about their diagnosis following imaging results. When asked directly, 96% of clinicians stated that the imaging contributed to the diagnostic process. CONCLUSIONS:In a mixed clinical cognitive impairment cohort, perfusion SPECT is valued by referring clinicians and contributes to diagnostic decision making. Imaging is of particular value when diagnostic confidence is low prior to imagin

Analytical technique to recover the third dimension in planar imaging of inhaled aerosols: (1) impact on spatial quantification

An analytical algorithm is described for converting planar scintigraphic images of aerosol distributions in the lungs to an equivalent three-dimensional (3D) representation. The recovery of volumetric information should benefit regional quantification. The technique has been validated using simulated planar images of eleven known aerosol distributions in ten realistic lungs. Global and regional 3D parameters, such as the total activity deposition (A), the penetration index (PI) and the relative penetration index (rPI), were quantified on the planar images and on their 3D representation. Random and systematic errors of the estimation were measured. Finally, the performance of planar imaging was compared with that of single-photon emission computed tomography (SPECT). SPECT images were simulated for the same aerosol distributions in the same subjects and quantified for A, PI, and rPI. The systematic errors in A, PI and rPI obtained from planar imaging were 8.9%, 64.8%, and 54.1%, respectively, using the two-dimensional (2D) analysis; they improved significantly to 4.4%, 19.0%, and 25.5% with the 3D analysis (p < 0.01). The corresponding values for SPECT were 5.2%, 9.8%, and 15.7%, significantly better for PI and rPI (p < 0.01). The random errors of A were similar for all techniques being about 5%; those of PI and rPI measurements were significantly higher for planar imaging (?14%) than SPECT (?8%). In conclusion, 3D spatial parameters can be derived from planar imaging that are significantly more accurate in characterizing different aerosol depositions than their 2D counterpart. However, the errors remain significantly higher than with SPECT

Supplementary Material for: Imaging Care Requirements: Use of Functional Neuroimaging to Predict Dementia Caregiver Burden

Background: Dementia caregivers frequently report high stress, with increased burden associated with worse outcomes for both patients and caregivers. Although many studies relate clinical phenotypes to burden, the relationship between imaging pathology and burden, irrespective of diagnosis, is unknown. This study investigated the relationship between caregiver burden and patient regional cerebral blood flow in dementia. Methods: Seventy-sev en patients with cognitive impairment undergoing brain perfusion single-photon emission computed tomography imaging in normal clinical care and their caregivers were recruited. Caregiver burden was ranked from &ldquo;little&rdquo; to &ldquo;severe&rdquo; using the Zarit Burden Interview and perfusion values extracted from the patient images for predefined regions of interest. The associations between burden score and regional function on imaging were tested. Results: Burden score was significantly higher for caregivers of patients with abnormal perfusion compared to those with normal perfusion in the left and right frontal, right parietal, and right temporal lobes. No difference in burden was found in the left parietal or temporal groups. Correlations showed that a higher caregiver burden was associated with lower patient perfusion scores in the same regions. Conclusion: Caregiver burden is strongly related to the extent of frontal or right-predominant parietal or temporal lobe dysfunction. Regional abnormality on perfusion imaging can be used to facilitate identification of individuals who are likely to create a high burden on caregivers.</span

Limitations of the HMPAO SPECT appearances of occipital lobe perfusion in the differential diagnosis of dementia with Lewy bodies

Objective To assess the utility of the appearances of occipital lobe perfusion on HMPAO SPECT in the diagnosis of dementia with Lewy bodies (DLB) using the I-123-FP-CIT findings as the diagnostic 'gold standard'. Methods Eighty-four consecutive patients underwent both HMPAO SPECT and I-123-FP-CIT as part of their routine investigations for suspected DLB. Results Thirty-nine of the 84 FP-CIT scans were abnormal indicating a prevalence of 44% of patients with DLB in this series. In those patients classified as DLB, 28% of HMPAO SPECT scans demonstrated occipital hypoperfusion. In those patients with a dementia other than DLB 31% of patients demonstrated occipital hypoperfusion (P=0.8). Conclusion Occipital lobe hypoperfusion as demonstrated by HMPAO SPECT in patients with suspected Lewy body dementia does not appear to be able to either rule in, or rule out, the diagnosis of DL