Radioiodination and Purification of [131I]β-CIT and [131I]FP-CIT with an Automated Radiosynthesizer

Dopaminergic transporter (DAT) imaging with single photon emission computed tomography (SPECT) is used to diagnose Parkinson’s disease and to differentiate it from other neurodegenerative disorders without presynaptic dopaminergic dysfunction. The radioiodinated tropane alkaloids [123I]FP-CIT and [123I]β-CIT enable the evaluation of the integrity of DATs. Commonly, the labeling of these compounds is performed by electrophilic substitution of the alkylstannylated precursors with radioactive iodine and following purification by HPLC or solid phase extraction (SPE). This work presents the first radioiodination of β-CIT and FP-CIT with no carrier added [131I]NaI on a Scintomics GRP synthesis module. Free iodine-131 and impurities were removed by SPE over a C-18 Sep-Pak cartridge. We achieved a radiochemical yield of >75% and a radiochemical purity of >98% with both compounds. Our development of an automated synthesis on a commercially available synthesizer ensures robust and efficient labeling of [131I]FP-CIT and [131I]β-CIT starting with low concentrated radioiodine.

Correlations Between Single-Photon Emission Computed Tomography Parameters of Salivary Glands and Dry Eye Tests in Patients With Sjögren's Syndrome

ObjectiveTo evaluate the correlations between Single-Photon Emission Computed Tomography (SPECT) parameters of salivary glands and dry eye parameters in patients with Sjögren's syndrome (SS).MethodsA total of 28 patients with SS participated in this prospective study. Dry eye assessments include tear film break-up time (TBUT), corneal fluorescein staining scoring (CFS), Schirmer's I test (SIT) examination and SPECT of salivary gland. The following quantitative parameters were derived from SPECT imaging for salivary glands: Uptake index (UI), the time needed to achieve the minimum counts after Vit C stimulation (Ts), and excretion fraction (EF). The relation between the aforementioned parameters and TBUT, CFS and SIT were analyzed with SPSS 22.0 software.ResultsAll the 28 eyes of the 28 subjects were examined. The mean SIT was 6.04 ± 4.64 mm/5 min (0–18 mm/5 min); the mean CFS was 3.07 ± 2.65 (0–10) and the mean BUT was 2.11 ± 1.97 s (0–9 s). The mean EF value was 0.52 ± 0.12 (0.26–0.75) in parotid glands and 0.45 ± 0.10 (0.30–0.67) in submandibular glands, respectively. The mean UI value was 9.33 ± 1.68 (6.03–13.20) in parotid glands and 9.92 ± 1.48 (7.08–12.60) in submandibular glands, respectively. The mean Ts (min) was 5.32 ± 3.01 (2.00–12.00) in parotid glands and 11.09 ± 7.40 (2.00- 29.00 min) in submandibular glands, respectively. It was found that EF positively correlates with SIT in patients with SS (r = 0.499 and 0.426 in parotid glands and submandibular glands, with P < 0.05), while no significant correlation was found between the UI, Ts and CFS, TBUT (P > 0.05).ConclusionsThe EF was positively correlated with SIT in patients with SS, it could reflex the dysfunction of salivary glands in SS patients. So, EF may be a valuable parameter for the diagnosis of SS patients with lacrimal gland secretion dysfunction.

Influence of brain atrophy using semiquantitative analysis in [123I]FP-CIT single-photon emission computed tomography by a Monte Carlo simulation study

The specific binding ratio (SBR) is an objective indicator of N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-[123I] iodophenyl) nortropane ([123I]FP-CIT) single-photon emission computed tomography (SPECT) that could be used for the diagnosis of Parkinson’s disease and Lewy body dementia. One of the issues of the SBR analysis is that the setting position of the volume of interest (VOI) may contain cerebral ventricles and cerebral grooves. These areas may become prominent during the brain atrophy analysis; however, this phenomenon has not been evaluated enough. This study thus used Monte Carlo simulations to examine the effect of brain atrophy on the SBR analysis. The brain atrophy model (BAM) used to simulate the three stages of brain atrophy was made using a morphological operation. Brain atrophy levels were defined in the descending order from 1 to 3, with Level 3 indicating to the most severe damage. Projection data were created based on BAM, and the SPECT reconstruction was performed. The ratio of the striatal to background region accumulation was set to a rate of 8:1, 6:1, and 4:1. The striatal and the reference VOI mean value were decreased as brain atrophy progressed. Additionally, the Bolt’s analysis methods revealed that the reference VOI value was more affected by brain atrophy than the striatal VOI value. Finally, the calculated SBR value was overestimated as brain atrophy progressed, and a similar trend was observed when the ratios of the striatal to background region accumulation were changed. This study thus suggests that the SBR can be overestimated in cases of advanced brain atrophy.

Single-Photon Emission Computed Tomography/Computed Tomography Image-Based Radiomics for Discriminating Vertebral Bone Metastases From Benign Bone Lesions in Patients With Tumors

Purpose: The purpose of this study was to investigate the feasibility of Single-Photon Emission Computed Tomography/Computed Tomography (SPECT/CT) image-based radiomics in differentiating bone metastases from benign bone lesions in patients with tumors.Methods: A total of 192 lesions from 132 patients (134 in the training group, 58 in the validation group) diagnosed with vertebral bone metastases or benign bone lesions were enrolled. All images were evaluated and diagnosed independently by two physicians with more than 20 years of diagnostic experience for qualitative classification, the images were imported into MaZda software in Bitmap (BMP) format for feature extraction. All radiomics features were selected by least absolute shrinkage and selection operator (LASSO) regression and 10-fold cross-validation algorithms after the process of normalization and correlation analysis. Based on these selected features, two models were established: The CT model and SPECT model (radiomics features were derived from CT and SPECT images, respectively). In addition, a combination model (ComModel) combined CT and SPECT features was developed in order to better evaluate the predictive performance of radiomics models. Subsequently, the diagnostic performance between each model was separately evaluated by a confusion matrix.Results: There were 12, 13, and 18 features contained within the CT, SPECT, and ComModel, respectively. The constructed radiomics models based on SPECT/CT images to discriminate between bone metastases and benign bone lesions not only had high diagnostic efficacy in the training group (AUC of 0.894, 0.914, 0.951 for CT model, SPECT model, and ComModel, respectively), but also performed well in the validation group (AUC; 0.844, 0.871, 0.926). The AUC value of the human experts was 0.849 and 0.839 in the training and validation groups, respectively. Furthermore, both SPECT model and ComModel show higher classification performance than human experts in the training group (P = 0.021 and P = 0.001, respectively) and the validation group (P = 0.037 and P = 0.007, respectively). All models showed better diagnostic accuracy than human experts in the training group and the validation group.Conclusion: Radiomics derived from SPECT/CT images could effectively discriminate between bone metastases and benign bone lesions. This technique may be a new non-invasive way to help prevent unnecessary delays in diagnosis and a potential contribution in disease staging and treatment planning.

Severity Evaluation of Regional Cerebrovascular Reactivity in Acute Stroke Patients using SPECT

Background: Cerebrovascular reactivity (CVR), as measured using perfusion single photon emission computed tomography (SPECT), is an important indicator for the treatment and prognosis of cerebrovascular disease, but there are few studies of acute stroke or small vascular disease using SPECT. Objective: This study was to evaluate the regional severity with quantitatively determined CVR in patients with acute stroke. Method: Fifty-eight patients who took brain SPECT images were selected to localize quantitative CVR values. The severity of the disease (Grade 1 to 4) was determined through image-based clinical assessment in the absence and presence of a CVR map and their results were compared. Results: In 1st diagnosis without the map, the mean CVR values of Grades 2 and 3 were -6.07% and -9.12%, respectively (P=0.034), while they were -4.78% and -12.34% in 2nd diagnosis with the map, respectively (P<0.001), suggesting that the CVR difference with the map was much more pronounced than without the map. Furthermore, in the ROC analysis, the diagnostic sensitivity between Grades 2 and 3 in 2nd diagnosis (AUC=0.899, P<0.001) was substantially greater than 1st diagnosis (AUC=0.646, P=0.048). Conclusion: This study demonstrated the quantitative CVR maps could reinforce the clinical evaluation of cerebral severity by showing that they can provide statistically significant results between severity and CVR. Furthermore, this study was the first to evaluate the effectiveness of quantitative CVR by examining the difference in the presence or absence of CVR in patients with acute stroke.

Characterization of time-of-flight double-photon Compton imaging system by simulation

Double-photon emission computed tomography (DPECT) has been proposed to overcome the disadvantage of a low signal-to-background ratio for conventional Compton imaging. This method has shown significant image reconstruction capability in the 2D plane. However, its performance is unsatisfactory when the field of view is 3-dimensional (3D). To solve this problem, we propose application of the time-of-flight (TOF) technique to DPECT as an enhancement. In this research, we used a Geant4 simulation to demonstrate the effectiveness of TOF in large 3D volume image reconstruction.

Pencitraan Kedokteran Nuklir Pada Pasien Metastasis Tulang dengan Kanker Payudara

Bone is the most common site to which breast cancer metastasizes and sometimes is the first affected site in a substantial proportion of women with advanced breast cancer. A lot of study has highlighted that imaging modalities visualize different aspects of osseous tissues (cortex or marrow). Imaging bone metastases is problematic because the lesions can be osteolytic, osteoblastic, or mixed, and imaging modalities are based on either direct anatomic visualization of the bone or tumor or indirect measurements of bone or tumor metabolism. Bone imaging by skeletal scintigraphy can be an essential part, and positron emission tomography or single-photon emission computed tomography have a potential of evaluating bone metastases, but no consensus exists as to the best modality for diagnosing the lesion and for assessing its response to treatment. In this review, we discuss the use of each nuclear imaging for bone modality for diagnosing bone metastases from breast cancer