Annals of Nuclear Medicine最新文献

Objective

Amino acid positron emission tomography (PET) examinations using anti-1-amino-3-[¹⁸F]-fluorocyclobutane-1-carboxylic acid ([¹⁸F]FACBC) were allowed for routine clinical use in July 2024. However, phantom test procedures for [¹⁸F]FACBC reconstruction parameters have not yet been established. The present study aimed to establish new phantom test procedures for [¹⁸F]FACBC brain PET imaging to determine optimal reconstruction parameters.

Methods

Background (BG) activity as well as hot sphere and target-to-background ratios (TBRs) of [¹⁸F]FACBC were estimated based on brain activity and tumor-to-normal tissue ratios (TNR) in a Japanese clinical trial of [¹⁸F]FACBC. Phantom experiments proceeded under [¹⁸F]FACBC or L-[methyl-¹¹C]-methionine ([¹¹C]MET) conditions. The number of iterations and the Gaussian filter parameters were determined from the reconstruction parameters %contrast_mean and coefficients of variation (CVs) in ordered subset expectation maximization (OSEM) and time-of-flight (TOF) with or without point-spread-function (PSF) correction.

Results

The amounts of activity in the hot spheres and BG were 1.1 and 5.5 kBq/mL, respectively, and the TBR was 5.0 at the start of acquisition. The %contrast_mean of all hot spheres was higher with [¹⁸F]FACBC than [¹¹C]MET, and %contrast_mean converged between 4 and 6 iterations in hot spheres with diameters < 10 mm. We used four iterations for OSEM + TOF and five for OSEM + TOF + PSF correction for [¹⁸F]FACBC and [¹¹C]MET images. The CV was higher for [¹⁸F]FACBC than [¹¹C]MET. The optimal sizes of Gaussian filters for OSEM + TOF and OSEM + TOF + PSF correction of image reconstruction were 5 mm for [¹⁸F]FACBC, and 4 and 3 mm, respectively, for [¹¹C]MET images.

Conclusions

We estimated phantom activity and TBR based on brain activity in a Japanese clinical trial and established new phantom test procedures for [¹⁸F]FACBC. We recommend that the optimal reconstruction parameters for [¹⁸F]FACBC should be set to the same number of iterations as [¹¹C]MET and that the FWHM of Gaussian filter should have a few mm higher than [¹¹C]MET to reduce image noise from brain normal tissue.

Background

Stress myocardial perfusion single-photon emission computed tomography (SPECT) imaging (MPI) has been used to diagnose and predict the prognoses of patients with coronary artery disease (CAD). An ongoing multicenter collaboration established a Japanese database (J-ACCESS) in 2001 that includes a risk model and expert interpretations. The present study aimed to develop a novel algorithm using machine learning (ML) and resources from the J-ACCESS database to aid SPECT image interpretation.

Methods

We analyzed data from 1288 patients in J-ACCESS 3 and 4 databases. Three-dimensional (3D) stereoscopic images of left ventricular myocardial perfusion were reconstructed with linear transformation from the original short-axis data. Segments were extracted from U-Net, then features were extracted from each segment during the ML process. We estimated segmental scores based on weighted features obtained from fully connected layers. Correlations between segment scores interpreted by nuclear cardiology experts and estimated by ML were evaluated using a 17-segment model, summed stress (SSS), summed rest (SRS), and summed difference (SDS) scores, and ratios (%) of summed different scores (%SDS).

Results

The complete concordance rate of scores assessed by the experts and estimated by ML was 79.6%. The underestimated and overestimated rates were 10.3% and 10.0%, respectively. Associations between defect scores assessed by experts and ML were close, with correlation coefficients (r) of 0.923, 0.917, 0.842 and 0.853 for SSS, SRS, SDS, %SDS, respectively (p < 0.0001 for all).

Conclusions

We created a new algorithm to estimate MPI scores using ML and the J-ACCESS database. This algorithm should provide accurate MPI interpretation even in facilities without specialist nuclear cardiologists, and might facilitate therapeutic decision-making and predict prognoses.

Purpose

In this study, we aimed to evaluate the response of the primary and metastatic liver tumors to radioembolization with ⁹⁰Y glass microspheres and investigate its correlations with dosimetric variables calculated with ⁹⁰Y PET/MRI.

Methods

In this ambispective study, 44 patients treated with ⁹⁰Y glass microspheres and imaged with ⁹⁰Y PET/MRI were included for analysis. Dosimetric analysis was performed for every perfused lesion using dose–volume histograms. Response was assessed by comparing pre-treatment and follow-up total lesion glycolysis (TLG) values derived from ¹⁸F-FDG PET imaging. The relationship between ΔTLG and log-transformed dosimetric variables was analyzed with linear mixed effects regression models. ROC analyses were performed to compare discriminatory power of the variables in predicting response and complete response.

Results

Regression and ROC analyses demonstrated that mean tumor dose and almost all D values were statistically significant predictors of treatment response and complete treatment response. Specifically, D60, D70 and D80 values exhibited significantly higher discriminatory power for predicting treatment response compared to the mean dose (D_mean) delivered to tumor. High specificity cut-off values to predict response were determined as 160.75 Gy for D_mean, 95.50 Gy for D60, 89 Gy for D70, and 59.50 Gy for D80. Similarly, high-specificity cut-off values to predict complete response were 262.75 Gy for D_mean, 173 Gy for D70, 140.5 Gy for D80, and 100 Gy for D90.

Conclusion

In this study, we demonstrated that voxel-based dosimetry with post-treatment ⁹⁰Y PET/MRI can predict response to treatment. D60, D70 and D80 variables also did have greater discriminatory power compared to D_mean in prediction of response. In addition, we present high-specificity cut-offs to predict response (CR + PR) and complete response (CR) for both D_mean and several D variables derived from dose–volume histograms.

Objectives

We aimed to evaluate correlations between striatal dopamine transporter (DAT) uptake and clinical assessments in both patients with Parkinson’s disease (PD) and healthy controls.

Methods

This study enrolled 193 healthy controls, and 581 patients with PD. They underwent various clinical assessments and ¹²³I-FP-CIT SPECT scans. After reconstruction, attenuation correction, and normalization of SPECT images, counts were measured from the bilateral caudate and putamen, and the occipital cortex for reference. Count densities for each region were extracted and used to calculate striatal binding ratios (SBRs) for each striatal region. SBR is calculated as (target region/reference region)—1. After logarithmic transformation of striatal SBRs, we analyzed the effects of clinical assessments on striatal SBRs using Bayesian hierarchical modeling.

Results

MDS-UPDRS total score, part I, part II, part III, Epworth Sleepiness Scale, REM sleep behavior disorder screening questionnaire, SCOPA-AUT total score were negatively associated with striatal SBR in patients with PD. Also, HVLT recognition discrimination was positively associated with striatal SBR in both healthy controls and patients with PD. In healthy control, MDS-UPDRS part II, MOCA, SCOPA-AUT total score were positively associated with striatal SBR.

Conclusion

We demonstrated that motor symptom, sleep disturbance, autonomic symptom, and cognition of patients with PD were associated with striatal dopaminergic activity. In healthy controls, motor symptoms, autonomic symptom, and cognition were associated with striatal dopaminergic activity, some of which showing the opposite direction with patients with PD. This result might provide new insight to underlying mechanism of dopamine system with motor and non-motor assessments.

Purpose

To assess myocardial injury using rest single photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) in patients with COVID-19 and to evaluate whether myocardial injury detected by rest MPI predict the prognosis of symptoms after 6 months follow-up.

Methods

Patients suspected of myocarditis between December 2022 and March 2023, after the lifting of COVID-19 pandemic restrictions, and between December 2018 and March 2019, prior to the pandemic, were referred to our study. All patients underwent rest MPI. One hundred and sixty four patients with COVID-19 infection after the lifting of pandemic restrictions and 101 patients before the pandemic were included as the study and control groups, respectively. One hundred and fifty three patients of the study group and 83 of the control group presented symptoms when they initially visit to our department. Compare the parameters of myocardial injury detected by rest SPECT MPI between the two groups and then investigate the association between myocardial injury and symptom prognosis in symptomatic patients of both groups.

Results

Total perfusion defect (TPD) (4.2% ± 3.3% vs. 2.3% ± 2.2%, P < 0.001), summed rest score (SRS) (5.3 ± 5.4 vs. 2.7 ± 2.0, P < 0.001), the proportion of patients with TPD > 4% (43.3% vs. 17.8%, P < 0.001), TPD > 10% (6.71% vs 0, P < 0.001), SRS > 4 (40.2% vs 15.8%, P < 0.001), SRS > 10 (12.8% vs 0, P < 0.001), the number of abnormal perfusion segments (3.9 ± 3.1 vs. 2.4 ± 1.7, P < 0.001) were all significantly higher in the study group. All the parameters of rest MPI were not associated with the prognosis of symptoms in symptomatic patients of both groups after 6 months follow-up.

Conclusion

Myocardial injury in COVID-19 patients could be assessed by rest SPECT MPI. The COVID-19 patients could exhibited a higher frequency and greater severity of myocardial injury than uninfected control patients. Myocardial injury assessed by rest MPI did not predict for the prognosis of symptoms in symptomatic patients of both COVID-19 patients and uninfected patients.

Aim

CT images can identify structural and opacity alterations of the lungs while nuclear medicine’s lung perfusion studies show the homogeneity (or lack of) of blood perfusion on the organ. Therefore, the use of SPECT/CT in lung perfusion scintigraphies can help physicians to assess anatomical and functional alterations of the lungs and to differentiate between acute and chronic disease.

Objective

To develop a computer-aided methodology to quantify the total global perfusion of the lungs via SPECT/CT images and to compare these results with parenchymal alterations obtained in CT images.

Methods

39 perfusion SPECT/CT images collected retrospectively from the Nuclear Medicine Facility of Botucatu Medical School’s Clinics Hospital in São Paulo, Brazil, were analyzed. Anatomical lung impairments (emphysema, collapsed and infiltrated tissue) and the functional percentage of the lungs (blood perfusion) were quantified from CT and SPECT images, with the aid of the free, open-source software 3D Slicer. The results obtained with 3D Slicer (3D-TGP) were also compared to the total global perfusion of each patient’s found on their medical report, obtained from visual inspection of planar images (2D-TGP).

Results

This research developed a novel and practical methodology for obtaining lungs’ total global perfusion from SPECT/CT images in a semiautomatic manner. 3D-TGP versus 2D-TGP showed a bias of 7% with a variation up to 67% between the two methods. Perfusion percentage showed a weak positive correlation with infiltration (p = 0.0070 and ρ = 0.43) and collapsed parenchyma (p = 0.040 and ρ = 0.33).

Conclusions

This research brings meaningful contributions to the scientific community because it used a free open-source software to quantify the lungs blood perfusion via SPECT/CT images and pointed that the relationship between parenchyma alterations and the organ’s perfusion capability might not be so direct, given compensatory mechanisms.

Introduction

¹²³I-FP-CIT (¹²³I-Ioflupane) SPECT shows strong accumulation in the striatum, but morphological standardization is challenging due to low accumulation outside the striatum, particularly in subjects with marked striatal decline. In this study, morphological standardization without MRI was achieved using the adaptive template registration (ATR) method to create a subject-specific optimized template with weighted images of normal-type and egg-shape-type templates. The accuracy of a quantitative method for calculating the ratio with nonspecific accumulation in the occipital lobe was evaluated by placing voxels-of-interest (VOI) on standardized images, particularly targeting the striatum.

Methods

The average images of eight subjects, demonstrating normal-type and egg-shape-type tracer accumulation in ¹²³I-Ioflupane SPECT, were utilized as normal and disease templates, respectively. The study included 300 subjects that underwent both ¹²³I-Ioflupane SPECT and MRI for the diagnosis of suspected Parkinson's disease or for exclusion diagnosis. Morphological standardization of SPECT images using structural MRI (MRI-based method) was considered the standard of truth (SOT). Three morphological standardizations without MRI were conducted. The first involved conventional morphological standardization using a normal template (fixed template method), the second employed the ATR method, with a weighted template, and the third used the split-ATR method, processing the left and right striatum separately to address asymmetrical accumulation. VOIs were set on the striatum, caudate, putamen as regions of specific accumulation, and on the occipital lobe as a reference region for nonspecific accumulation.

Results

Results showed significant and robust linearity in the striatal accumulation ratios for all templates when compared with the occipital lobe accumulation ratio when using the MRI-based method. Comparing intra-class correlations for different linearities, the ATR method and split-ATR method demonstrated higher linearity in the striatum, caudate, and putamen. The split-ATR method showed similar improvements, although more linearity than some of the ATR methods; the effectiveness of the Split-ATR method may vary by image quality, and further validation of its effectiveness in diverse asymmetric accumulation cases seemed warranted.

Conclusion

The use of optimized templates, such as the ATR and split-ATR methods, improved reproducibility in fully automated processing and demonstrated superior linearity compared to that of MRI-based method, in the ratio to the occipital lobe. The ATR method, which enables morphological standardization when using SPECT images only, proved highly reproducible for clinical quantitative analysis of striatal accumulation, facilitating its clinical use.

Objective

This study aimed to identify a relatively robust SUV for guiding clinical practice through quantitative measurement and comparison of various normalization methods based on the SUV of ^99mTc-MDP in the normal spine and pelvis using an integrated SPECT/CT scanner.

Methods

Between June 2017 and September 2019, a total of 500 oncology patients (mean age, 60.9; men, 66.0%) who underwent bone SPECT/CT scans with ^99mTc-MDP were enrolled in this retrospective study. The mean SUV (SUV_mean) of 4962 spinal and pelvic bones was calculated based on the patients’ body weight (BW), lean body mass (LBM), bone mineral content (BMC), body surface area (BSA), and body mass index (BMI), defined as SUV_bw, SUV_lbm, SUV_bmc, SUV_bsa, and SUV_bmi, respectively. The coefficients of variation (CoVs) of the aforementioned parameters were compared, and the correlation and multiple linear regression analyses were used to compare the extent to which these parameters were affected by sex, age, height, weight, BMI, and CT values.

Results

The average SUVs in the normal spine and pelvis displayed a relatively wide variability: 4.573 ± 1.972 for SUV_bw, 3.555 ± 1.517 for SUV_lbm, 0.163 ± 0.071 for SUV_bmc, 0.124 ± 0.052 for SUV_bsa, and 1.668 ± 0.732 for SUV_bmi. In general, SUV_bsa had relatively lowest CoV (42.1%) in all vertebrae and pelvis compared with other SUVs. For correlation analyses, all SUVs displayed weak but significant correlations with age and CT values. For regression analyses, SUV_bsa was influenced only by age, BMI, and CT values independently. The effects of these variables on SUV_bsa were all smaller than those on conventional SUV_bw.

Conclusions

The SUVs of ^99mTc-MDP in normal bone derived from quantitative bone SPECT/CT could serve as a reference for evaluating tumor bone metastasis, but it should be assessed on a site-specific basis. SUV_bsa exhibited superior robustness among all the SUV normalization variations, indicating potential clinical applications.

Objectives

This study aims to evaluate the value of the dynamic and static quantitative metabolic parameters derived from ¹⁸F-fluorodeoxyglucose (FDG)–positron emission tomography/CT (PET/CT) in the differential diagnosis of metastatic from non-metastatic lymph nodes (LNs) in lung cancer and to validate them based on the results of a previous study.

Methods

One hundred and twenty-one patients with lung nodules or masses detected on chest CT scan underwent ¹⁸F-FDG PET/CT dynamic + static imaging with informed consent. A retrospective collection of 126 LNs in 37 patients with lung cancer was pathologically confirmed. Static image analysis parameters include LN-SUV_max and LN-SUV_max/primary tumor SUV_max (LN-SUV_max/PT-SUV_max). Dynamic metabolic parameters including the net influx rate (K_i) and the surrogate of perfusion (K₁) and of each LN were obtained by applying the irreversible two-tissue compartment model using in-house Matlab software. K_i/K₁ was then calculated as a separate marker. Based on the pathological findings, we divided into a metastatic group and a non-metastatic group. The χ² test was used to evaluate the agreement of the individual and combined diagnosis of each metabolic parameter with the gold standard. The receiver-operating characteristic (ROC) analysis was performed for each parameter to determine the diagnostic efficacy in differentiating non-metastatic from metastatic LNs with high FDG-avid. P < 0.05 was considered statistically significant.

Results

Among the 126 FDG-avid LNs confirmed by pathology, 70 LNs were metastatic, and 56 LNs were non-metastatic. For ROC analysis, in separate assays, the dynamic metabolic parameter K_i [sensitivity (SEN) of 84.30%, specificity (SPE) of 94.60%, accuracy of 88.89%, and AUC of 0.895] had a better diagnostic value than the static metabolic parameter SUV_max (SEN of 82.90%, SPE of 62.50%, accuracy of 74.60%, and AUC of 0.727) in differentiating between metastatic from non-metastatic LNs groups, respectively. In the combined diagnosis group, the combined SUV_max + K_i diagnosis had a better diagnostic value in the differential diagnosis of metastatic from non-metastatic LNs, with SEN, SPE, accuracy, and AUC of 84.3%, 94.6%, 88.89%, and 0.907, respectively.

Conclusions

When the cutoff value of K_i was 0.022 ml/g/min, it had a high diagnostic value in the differential diagnosis between metastasis and non-metastasis in FDG-avid LNs of lung cancer, especially in improving the specificity. The combination of SUV_max and K_i is expected to be a reliable metabolic parameter for N-staging of lung cancer.

Objective

When patients administered ¹⁷⁷Lu-DOTATATE are released or discharged from rooms where radiopharmaceuticals are used, the time required for release or discharge varies across patients. This study investigated whether the amount of radioactivity accumulated on ¹¹¹In-somatostatine receptor scintigraphy (¹¹¹In-SRS) performed prior to treatment can predict the 1 cm dose-equivalent rate at a distance of 1 m from the patient on the day after ¹⁷⁷Lu-DOTATATE administration.

Methods

Whole-body planar ¹¹¹In-SRS images were acquired for 21 patients. Pixel values within whole-body and abdominal (35 × 25 cm) regions of interest (ROIs) were converted to radioactivity dose (MBq). The 1 cm dose-equivalent rate (µSv/h) at a distance of 1 m from the patient 18.3 ± 0.5 h after administration of ¹⁷⁷Lu-DOTATATE was measured using an ionization survey meter.

Results

The following relationships were observed between the radioactivity on ¹¹¹In-SRS and the 1 cm dose-equivalent rate on the day after administration of ¹⁷⁷Lu-DOTATATE: whole-body ROI: y = 0.16x + 5.01 (r = 0.56, p = 0.009), abdominal ROI: y = 0.27x + 5.13 (r = 0.63, p = 0.002). The regression equations indicate that patients cannot be released or discharged from the radiopharmaceutical room the day after ¹⁷⁷Lu-DOTATATE administration if the whole-body and abdominal ROI doses are greater than 81 and 48 MBq, respectively, on ¹¹¹In-SRS.

Conclusions

The amount of radioactivity accumulated on ¹¹¹In-SRS may be a predictor of release criteria for patients receiving ¹⁷⁷Lu-DOTATATE.