Single Proton Emission Computed Tomography Research Articles

Artificial intelligence and imaging: Opportunities in cardio-oncology

Cardiovascular disease is a leading cause of death in cancer survivors. It is critical to apply new predictive and early diagnostic methods in this population, as this can potentially inform cardiovascular treatment and surveillance decision-making. We discuss the application of artificial intelligence (AI) technologies to cardiovascular imaging in cardio-oncology, with a particular emphasis on prevention and targeted treatment of a variety of cardiovascular conditions in cancer patients. Recently, the use of AI-augmented cardiac imaging in cardio-oncology is gaining traction. A large proportion of cardio-oncology patients are screened and followed using left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS), currently obtained using echocardiography. This use will continue to increase with new cardiotoxic cancer treatments. AI is being tested to increase precision, throughput, and accuracy of LVEF and GLS, guide point-of-care image acquisition, and integrate imaging and clinical data to optimize the prediction and detection of cardiac dysfunction. The application of AI to cardiovascular magnetic resonance imaging (CMR), computed tomography (CT; especially coronary artery calcium or CAC scans), single proton emission computed tomography (SPECT) and positron emission tomography (PET) imaging acquisition is also in early stages of analysis for prediction and assessment of cardiac tumors and cardiovascular adverse events in patients treated for childhood or adult cancer. The opportunities for application of AI in cardio-oncology imaging are promising, and if availed, will improve clinical practice and benefit patient care.

Characteristic Neuroimaging Findings in a Patient with Acute Metabolic Encephalopathy, Lactic Acidosis and Stroke-Like Episodes Syndrome Distinguishable from that of Acute Ischemic Stroke

Metabolic encephalopathy, lactic acidosis and stroke-like episodes (MELAS) syndrome is characterized by encephalopathy mimicking acute stroke, which is rarely observed in adulthood. We present a case of a female who presented with several neurologic deficits and diagnosed with MELAS syndrome. Brain magnetic resonance imaging (MRI) showed acute lesions mimicking stroke, which were not compatible with specific vascular territories. Magnetic resonance spectroscopy showed lactate peaks in both symptomatic and asymptomatic area. Single proton emission computed tomography (SPECT) shows hyperperfusion in the same area. On follow-up image, MRI lesion nearly disappeared and hyperperfusion on SPECT changed into hypoperfusion. We discuss the clinical characteristics and image findings of our patient.

Acute anxiety disorder, major depressive disorder, bipolar disorder and schizophrenia are related to different patterns of nigrostriatal and mesolimbic dopamine dysfunction.

Dopamine (DA) receptor and transporter dysfunctions play a major role in the pathophysiology of neuropsychiatric diseases including anxiety disorder (AD), major depressive disorder (MDD), bipolar disorder (BD) in the manic (BDman) or depressive (BDdep) state and schizophrenia (SZ). We performed a PUBMED search, which provided a total of 239 in vivo imaging studies with either positron emission tomography (PET) or single-proton emission computed tomography (SPECT). In these studies, DA transporter binding, D1 receptor (R) binding, D2R binding, DA synthesis and/or DA release in patients with the primary diagnosis of acute AD (n=310), MDD (n=754), BDman (n=15), BDdep (n=49) or SZ (n=1532) were compared to healthy individuals. A retrospective analysis revealed that AD, MDD, BDman, BDdep and SZ differed as to affected brain region(s), affected synaptic constituent(s) and extent as well as direction of dysfunction in terms of either sensitization or desensitization of transporter and/or receptor binding sites. In contrast to AD and SZ, in MDD, BDman and BDdep, neostriatal DA function was normal, whereas MDD, BDman, and BDdep were characterized by the increased availability of prefrontal and frontal DA. In contrast to AD, MDD, BDman and BDdep, DA function in SZ was impaired throughout the nigrostriatal and mesolimbocortical system with an increased availability of DA in the striatothalamocortical and a decreased availability in the mesolimbocortical pathway.

Similarity-based attribute weighting methods via clustering algorithms in the classification of imbalanced medical datasets

In the fields of pattern recognition and machine learning, the use of data preprocessing algorithms has been increasing in recent years to achieve high classification performance. In particular, it has become inevitable to use the data preprocessing method prior to classification algorithms in classifying medical datasets with the nonlinear and imbalanced data distribution. In this study, a new data preprocessing method has been proposed for the classification of Parkinson, hepatitis, Pima Indians, single proton emission computed tomography (SPECT) heart, and thoracic surgery medical datasets with the nonlinear and imbalanced data distribution. These datasets were taken from UCI machine learning repository. The proposed data preprocessing method consists of three steps. In the first step, the cluster centers of each attribute were calculated using k-means, fuzzy c-means, and mean shift clustering algorithms in medical datasets including Parkinson, hepatitis, Pima Indians, SPECT heart, and thoracic surgery medical datasets. In the second step, the absolute differences between the data in each attribute and the cluster centers are calculated, and then, the average of these differences is calculated for each attribute. In the final step, the weighting coefficients are calculated by dividing the mean value of the difference to the cluster centers, and then, weighting is performed by multiplying the obtained weight coefficients by the attribute values in the dataset. Three different attribute weighting methods have been proposed: (1) similarity-based attribute weighting in k-means clustering, (2) similarity-based attribute weighting in fuzzy c-means clustering, and (3) similarity-based attribute weighting in mean shift clustering. In this paper, we aimed to aggregate the data in each class together with the proposed attribute weighting methods and to reduce the variance value within the class. Thus, by reducing the value of variance in each class, we have put together the data in each class and at the same time, we have further increased the discrimination between the classes. To compare with other methods in the literature, the random subsampling has been used to handle the imbalanced dataset classification. After attribute weighting process, four classification algorithms including linear discriminant analysis, k-nearest neighbor classifier, support vector machine, and random forest classifier have been used to classify imbalanced medical datasets. To evaluate the performance of the proposed models, the classification accuracy, precision, recall, area under the ROC curve, κ value, and F-measure have been used. In the training and testing of the classifier models, three different methods including the 50–50% train–test holdout, the 60–40% train–test holdout, and tenfold cross-validation have been used. The experimental results have shown that the proposed attribute weighting methods have obtained higher classification performance than random subsampling method in the handling of classifying of the imbalanced medical datasets.

Cardiological functional diagnostics

Cardiovascular diseases are common; therefore, adequate and guideline-based diagnostics and treatment are essential. In addition to an electrocardiogram (ECG) and (treadmill) exercise tests, echocardiography plays the pivotal role in functional cardiac testing. It is permanently available at the bedside and has a high diagnostic accuracy; however, examinations such as cardiac magnetic resonance imaging (MRI) and computed tomography (CT) as well as nuclear medical imaging, e.g. single proton emission CT (SPECT) and positron emission tomography (PET) are becoming more and more common in clinical practice. This is due to the wide range of additional information and the high diagnostic accuracy. In the following article, the individual possibilities of non-invasive cardiac functional testing are presented and their meaningful application will be discussed; however, studies on the meaningful application of non-invasive diagnostics are scarce.

Random sliced inverse regression

ABSTRACTSliced Inverse Regression (SIR; 1991) is a dimension reduction method for reducing the dimension of the predictors without losing regression information. The implementation of SIR requires inverting the covariance matrix of the predictors—which has hindered its use to analyze high-dimensional data where the number of predictors exceed the sample size. We propose random sliced inverse regression (rSIR) by applying SIR to many bootstrap samples, each using a subset of randomly selected candidate predictors. The final rSIR estimate is obtained by aggregating these estimates. A simple variable selection procedure is also proposed using these bootstrap estimates. The performance of the proposed estimates is studied via extensive simulation. Application to a dataset concerning myocardial perfusion diagnosis from cardiac Single Proton Emission Computed Tomography (SPECT) images is presented.

A Hybrid Approach for Cases Classification of Medical Data

Classification of cases has been widely applied in medicine, and it is helpful to disease diagnosis to a great extent. At present, the classification of medical cases is performed by physicians subjectively based on clinical theory and knowledge, which may hinder the diagnosis and treatment in some extent. In this paper, a hybrid classification approach (HCA) is proposed for medical data, it consists of two parts, including feature selection and classification. In feature selection, critical features are selected from the original features through linear correlation. Based on the selected features, cases are classified by C5.0 decision tree. And the proposed approach is evaluated through four medical datasets of diabetes, cardiac Single Proton Emission Computed Tomography (SPECT) images, lung cancer, and hepatitis survival for demonstration. On the four datasets, HCA shows a better construction for obviously higher classification accuracies, and it also outperforms some typical integrated classification methods.

DETECTING CRITICAL LEAST ASSOCIATION RULES IN MEDICAL DATABASES

Least association rules are corresponded to the rarity or irregularity relationship among itemset in database. Mining these rules is very difficult and rarely focused since it always involves with infrequent and exceptional cases. In certain medical data, detecting these rules is very critical and most valuable. However, mathematical formulation and evaluation of the new proposed measurement are not really impressive. Therefore, in this paper we applied our novel measurement called Critical Relative Support (CRS) to mine the critical least association rules from medical dataset. We also employed our scalable algorithm called Significant Least Pattern Growth algorithm (SLP-Growth) to mine the respective association rules. Experiment with two benchmarked medical datasets, Breast Cancer and Cardiac Single Proton Emission Computed Tomography (SPECT) Images proves that CRS can be used to detect to the pertinent rules and thus verify its scalability.

An uncommon presentation of Progressive Supranuclear Palsy diagnosed on DaT scan

Diagnosis of Parkinson's disease can be difficult in presence of atypical symptoms and signs. While the commonest reason of parkinsonism is idiopathic Parkinson's disease (PD), other disease entities that can mimic PD should be considered in the light of clinical history and examination findings. However, still some diagnostic dilemmas may exist which may need special investigative modalities. In recent years, advancements have been made to use single proton emission computed tomography (SPECT) scan to determine the cause of parkinsonian features. However, clinical use of this specialized tool is still not well-recognized. We have presented here a case of supranuclear palsy that was difficult to diagnose clinically and had appropriate final diagnosis with the help of dopamine transporters (DaT) scan.

Myocardial perfusion scintigraphy in Germany in 2009: utilization and state of the practice

Since 2006, the working group Cardiovascular Nuclear Medicine of the German Society of Nuclear Medicine, in cooperation with the working group Nuclear Cardiology of the German Cardiac Society, has been surveying the utilization and technical realization of myocardial perfusion scintigraphy (MPS) in Germany. This paper presents the results of the reporting year 2009. A total of 291 centres participated in the inquiry, including 179 private practices (PP), 86 hospitals (HO) and 26 university hospitals (UH). MPS of 98,103 patients were reported. The MPS numbers per million population (pmp) were estimated at 2,360; 76% of the MPS were performed in PP, 17% in HO and 7% in UH. The ratio of MPS to coronary angiography to revascularization was 0.5 to 2.3 to 1. Data from 134 centres which participated in the surveys from 2005 to 2009 showed a decrease in MPS utilization of 2.2%. Nearly half of the MPS were requested by ambulatory care cardiologists. Of all MPS studies, 89% were conducted with (99m)Tc perfusion tracers. Ergometry was the preferred stress test (69%). Adenosine was used in 16%, adenosine + exercise in 7%, dipyridamole in 3%, dipyridamole + exercise in 5% and dobutamine in <1%. Gated single proton emission computed tomography (SPECT) acquisition was performed in 56% of all rest MPS and in 56% of all stress MPS. Both rest and stress MPS were ECG gated in 41%. Only 33% of the centres always performed a quantification of the perfusion studies, whereas 51% did not apply any quantification; 4% of the MPS studies were corrected for attenuation, and 17 centres used transmission sources of 12 CT-based systems. A scan activity of 2,380 MPS pmp is in the upper third of the European range. The ratios to coronary angiography and to revascularization suggest that angiography dominates diagnosis and management of coronary artery disease (CAD). The clinical and technical realizations reveal that the predominant goals of further trainings to optimize MPS are in the field of gated SPECT and quantitative perfusion SPECT.

Cerebral Blood Flow Measurement in the Assessment of Post-Traumatic Cerebral Contusions

Brain trauma (BT) is extremely common in the Western society, and has been identified as the main cause of death and disability in the under-40 age group. Many aspects of the pathophysiological mechanisms involved and the effect of changes in cerebral metabolism are unclear. The aim of this study was to establish the rela- tionship between anatomical changes and deranged cerebral perfusion in patients with cerebral contusions, using Computed Tomography (CT) and Single Proton Emission Computed Tomography (SPECT). Twenty- two (22) patients who had suffered BT were recruited. All patients underwent SPECT and CT head scans on the same day. 18 were men. Patient average age was 45.6. Patients were assessed using the Glasgow scale (average 10.6). Cause of trauma included traffic accidents (9 patients) and falls (13 patients). A 4-slice spiral CT scan was performed. For each contusion, areas of bleeding, edema, and healthy perilesional tissue were distinguished. SPECT was performed with 20 mCi of 99 mTcECD using a dual-head gamma camera (128 × 128 matrix). CT scan revealed a single lesion in 12 patients, and more than one lesion in 10. The biggest le- sions found on CT were located in the frontal region in 13 patients; temporal region in 4; and parietal region in 1; four patients had poorly defined lesions. A total absence of perfusion was visible in 18 patients in the hemorrhagic area and in 14 patients in the edema, In 7 cases SPECT showed hypoperfusion that did not cor- respond to any morphological changes on the CT scan. Quantitative of fused lesions appearing on both CT scan and SPECT revealed severe perfusion defects in the hemorrhagic area (17.8%) and in the edema (29.4%). In our study, regional cerebral blood flow add relevant information on encephalic damage in pa- tients with BT.

Bio-effect model applied to 131I radioimmunotherapy of refractory non-Hodgkin’s lymphoma

Improved data collection methods have improved absorbed dose estimation by tracking activity distributions and tumor extent at multiple time points, allowing individualized absorbed dose estimation. Treatment with tositumomab and (131)I-tositumomab anti-CD20 radioimmunotherapy (BEXXAR) yields a cold antibody antitumor response (cold protein effect) and a radiation response. Biologically effective contributions, including the cold protein effect, are included in an equivalent biological effect model that was fit to patient data. Fifty-seven tumors in 19 patients were followed using 6 single proton emission computed tomography (SPECT)/CT studies, 3 each post tracer (5 mCi) and therapy (∼100 mCi) injections with tositumomab and (131)I-tositumomab. Both injections used identical antibody mass, a flood dose of 450 mg plus 35 mg of (131)I tagged antibody. The SPECT/CT data were used to calculate absorbed dose rate distributions and tumor and whole-body time-activity curves, yielding a space-time dependent absorbed dose rate description for each tumor. Tumor volume outlines on CT were used to derive the time dependence of tumor size for tracer and therapy time points. A combination of an equivalent biological effect model and an inactivated cell clearance model was used to fit absorbed dose sensitivity and cold effect sensitivity parameters to tumor shrinkage data, from which equivalent therapy values were calculated. Patient responses were categorized into three groups: standard radiation sensitivity with no cold effect (7 patients), standard radiation sensitivity with cold effect (11 patients), and high radiation sensitivity with cold effect (1 patient). Fit parameters can be used to categorize patient response, implying a potential predictive capability.

Continuing Education Course #1

The continuing education course "Non-Invasive Imaging as a Problem-Solving Tool and Translational Biomarker Strategy in Toxicologic Pathology" provided a thorough overview of commonly used imaging modalities and the logistics required for integration of small animal imaging into toxicologic pathology. Non-invasive imaging (NIN) is gaining acceptance as an important modality in toxicologic pathology. This technology allows nonterminal, time-course evaluation of functional and morphologic endpoints and can be used to translate biomarkers between preclinical animal models and human patients. NIN can support drug development as well as basic research in academic or industrial environments. An initial overview of theoretical principles was followed by focused presentations on magnetic resonance imaging (MRI)/magnetic resonance microscopy (MRM), positron emission tomography (PET)/single proton emission computed tomography (SPECT), ultrasonography (US, primarily focused on echocardiography), optical (bioluminescent) imaging, and computed tomography (CT). The choice of imaging modality will depend on the research question and the needed resolution.

Intractable occipital lobe epilepsy: Clinical characteristics and surgical treatment

Intractable occipital lobe epilepsy remains a surgical challenge. Clinical characteristics of 14 patients were analyzed. Twelve patients had surgery, seven patients had visual auras (50%) and only eight patients (57%) had posterior scalp EEG changes. Ictal single-proton emission computed tomography (SPECT) incorrectly localized in 7 of 10 patients. Six patients (50%) had Engel's class I outcome. Patients with inferior occipital seizure onset appeared to fare better (three of four class I) than patients with lateral or medial occipital seizure onset (three of eight class I). Patients who had all three occipital surfaces covered with electrodes had a better outcome (four of five class I) than patients who had limited electroencephalography (EEG) coverage (two of seven class I). Magnetic resonance imaging (MRI) lesions did not guarantee a seizure free outcome. In conclusion, visual auras, scalp EEG, and imaging findings are not reliable for correct identification of occipital onset. Occipital seizure onset can be easily missed in nonlesional epilepsy. Comprehensive intracranial EEG coverage of all three occipital surfaces leads to better outcomes.

Contralateral hyperperfusion and ipsilateral hypoperfusion by ictal SPECT in patients with mesial temporal lobe epilepsy

Ictal Single Proton Emission Computed Tomography (SPECT) has demonstrated high levels of sensitivity in localizing seizures among patients with epilepsy of the mesial temporal lobe (mTLE). However, incorrect information on the lateralization of mTLE has also been reported. In order to investigate the causes of these incorrect localizations, the authors assessed clinical symptoms, as well as the electroencephalography (EEG) and brain SPECT scan data of five patients with mTLE experiencing ictal hyperperfusion of the contralateral temporal lobe. All patients underwent presurgical evaluations, including an interictal and ictal brain SPECT scan. A subtraction ictal SPECT co-registered with Magnetic Resonance Imaging (MRI) procedure or SISCOM was performed. Hyperperfusion (ictal perfusion greater than interictal perfusion) and hypoperfusion (ictal perfusion lower than interictal perfusion), results of SISCOM were analyzed and compared with seizure and ictal EEG pattern patterns. All the five patients had unilateral hippocampal sclerosis, and the radiotracer for the ictal SPECT was injected after the ictal EEG pattern had propagated to the contralateral side. The average delay between the ictal EEG onset and the radiotracer injection was 29.7+/-9.6s. All hyperperfusion SISCOM results revealed hyperperfusion in the contralateral temporal region with a more intense ictal EEG build-up. However, hypoperfusion SISCOM results demonstrated significant hypoperfusion in the epileptogenic temporal lobe of three of the five patients, but no hypoperfusion finding in the other two patients. This study demonstrates that early ictal EEG pattern propagation to the contralateral side in mTLE may be associated with contralateral ictal hyperperfusion with or without ipsilateral temporal hypoperfusion. The authors recommend simultaneous interpretations of ictal SPECT and ictal EEG propagation patterns at the time of the injection of radiotracers.

Reliability of Composite Dichotomous Measurements

Reliability of measurement is a measure of its reproducibility under replicate conditions. The classical concept of reliability assumes that measurement Y is composed out of true value T and error term e, two independent random variables, Y = T + e . Reliability of measurement is defined as the ratio of the variance of the true scores to the variance of the observed scores. However, this concept is not applicable in models for dichotomous measurements which do not consider error terms and are instead defined via conditional probabilities. In this paper we examine a more general definition of reliability proposed in [1], which is based on decomposition of variance in mixed effects model. Proposed definition covers the classical definition of reliability and it is, moreover, appropriate for dichotomous measurements, too. Newly, for the proposed definition assumptions are derived, under which the reliability of composite measurement can be predicted by reliability of single measurement ( Spearman- Brown f ormula) and approximate validity of Spearman-Brown formula is shown for the Rasch model. Finally, as a modification of the classical estimate of reliability based on Cronbach’s alpha, we examine its counterpart logistic alpha introduced in [2], which appears to be more appropriate for composite dichotomous measurements in some cases. Simulations show that the new estimate does not tend to underestimate reliability as often as the Cronbach’s alpha does. The new estimate is used in binary data of computerized process of myocardial perfusion diagnosis from cardiac single proton emission computed tomography (SPECT).

Acceleration of Monte Carlo-based scatter compensation for cardiac SPECT

Single proton emission computed tomography (SPECT) images are degraded by photon scatter making scatter compensation essential for accurate reconstruction. Reconstruction-based scatter compensation with Monte Carlo (MC) modelling of scatter shows promise for accurate scatter correction, but it is normally hampered by long computation times. The aim of this work was to accelerate the MC-based scatter compensation using coarse grid and intermittent scatter modelling. The acceleration methods were compared to un-accelerated implementation using MC-simulated projection data of the mathematical cardiac torso (MCAT) phantom modelling 99mTc uptake and clinical myocardial perfusion studies. The results showed that when combined the acceleration methods reduced the reconstruction time for 10 ordered subset expectation maximization (OS-EM) iterations from 56 to 11 min without a significant reduction in image quality indicating that the coarse grid and intermittent scatter modelling are suitable for MC-based scatter compensation in cardiac SPECT.

Clinical characteristics of corticobasal syndrome amongst Chinese in Taiwan

This study reviewed the clinical characteristics of nine patients, the female-to-male ratio being 2 (6/3), with corticobasal syndrome (CBS) from 2001 to 2006. The mean age of onset was 60.33±5.20 years. The most popular symptom was rigidity (100%), followed by bradykinesia (88.89%), apraxia (88.89%) and dystonia (66.67%). The common presentations in neuropsychological assessment included frontal dysfunction (88.89%), disorientation (66.67%), memory impairments (66.67%) and visuospecial defects (66.67%). Single proton emission-computed tomography (CT) showed hypoperfusion at contralateral basal ganglia, thalamic, parietal or temporal region in eight of nine patients. This investigation suggests that functional neuroimages and neuropsychological tests are useful tools for the diagnosis of CBS.

Knowledge discovery approach to automated cardiac SPECT diagnosis

The paper describes a computerized process of myocardial perfusion diagnosis from cardiac single proton emission computed tomography (SPECT) images using data mining and knowledge discovery approach. We use a six-step knowledge discovery process. A database consisting of 267 cleaned patient SPECT images (about 3000 2D images), accompanied by clinical information and physician interpretation was created first. Then, a new user-friendly algorithm for computerizing the diagnostic process was designed and implemented. SPECT images were processed to extract a set of features, and then explicit rules were generated, using inductive machine learning and heuristic approaches to mimic cardiologist’s diagnosis. The system is able to provide a set of computer diagnoses for cardiac SPECT studies, and can be used as a diagnostic tool by a cardiologist. The achieved results are encouraging because of the high correctness of diagnoses.

Long-term additive prognostic value of thallium-201 myocardial perfusion imaging over clinical and exercise stress test in low to intermediate risk patients : study in 1137 patients with 6-year follow-up.

The exercise treadmill test (ETT) and Tl201 single proton emission computed tomography (SPECT) are of short- to medium-term prognostic value in coronary heart disease. We assessed the long-term prognostic value of these tests in a large population of patients with low- to intermediate risk of cardiac events. One thousand one hundred thirty-seven patients (857 men, age 55+/-9 years) referred for typical (62.1%) or atypical (22.4%) chest pain, or suspected silent ischemia (15.5%), were followed up for 72+/-18 months. Overall mortality was higher after strongly positive (ST depression >2 mm, or >1 mm for a workload </=75 W) (2. 36%/y) or nondiagnostic ETT (1.63%/y) than after normal (0.85%/y) or positive ETT (1.37%/y) (P=0.002), and after abnormal SPECT than after normal SPECT (1.60%/y versus 0.68%/y, P=0.001). The major cardiac event rate (cardiac death or myocardial infarction [MI]) was 0.88%, 1.59%, 2.10%, and 2.13%/y after negative, positive, strongly positive, and nondiagnostic ETT, respectively (P=0.003), and 0.56%, 1.43%, and 2.05%/y in patients with 0, 1 to 2, and >/=3 abnormal segments on SPECT, respectively (P<0.002). An abnormal SPECT was predictive of MI (P<0.001), whereas ETT was not. In multivariate analysis, SPECT was of incremental prognostic value over clinical and ETT data for predicting overall mortality and major cardiac events. The incremental predictive value of SPECT is maintained over 6 years and is particularly relevant after positive, strongly positive, and nondiagnostic ETT.