Frontiers in nuclear medicine (Lausanne, Switzerland)最新文献

Background: ¹⁸F-FDG-PET/CT may reveal widespread inflammation of musculoskeletal structures in polymyalgia rheumatica (PMR). Currently, scans are subjectively analysed based on the overall gestalt of the scan. Standardized PET scores may potentially aid the interpretation of the scans for suspected PMR. Here, we compared the agreement and diagnostic accuracy of routine PET scan reports vs. the most validated PET scores for PMR.

Methods: 68 consecutive patients with suspected PMR (treatment-naïve, n = 29; already treated, n = 39) undergoing ¹⁸F-FDG-PET/CT were included. In glucocorticoid-treated patients, complete tapering was pursued prior to the scan. Conclusions of routine PET scan reports were interpretated by three independent readers as "PMR", "not PMR" or "unclear". The Leuven and Leuven/Groningen scores were determined. Agreement of scan report interpretation, and agreement of routine scan reports and PET scores were determined. Sensitivity and specificity were determined for the routine scan report and the two scores, with the clinical diagnosis established after 6 months follow-up as the reference standard.

Results: A diagnosis of PMR was made in 45/68 patients. Routine scan reports were uniformly rated by all three readers in 54 (78%) cases. Following a consensus meeting, scans were rated as "PMR" in 43 cases, "unclear" in 10 cases and "not PMR" in 15 cases. The routine scan report showed a sensitivity of 82% and specificity of 74%, if "unclear" cases were considered negative for PMR. The Leuven and Leuven/Groningen Scores showed similar diagnostic accuracy. Agreement between the routine scan report and PET scores was good (Cohen's kappa 0.60-0.64), if "unclear" cases were excluded from the analysis. Among 8/10 "unclear" cases, the PMR PET Scores accurately distinguished between PMR/PMR-mimicking inflammatory conditions and non-inflammatory conditions. Agreement and diagnostic accuracy of routine scan reports and PET scores were better among treatment-naïve patients than those that had been treated previously.

Conclusion: Our study reveals that routine PET scan reports for suspected PMR can be interpreted differently between readers. Although the routine PET scan reports and PMR PET scores did not always agree, they demonstrated similar diagnostic accuracy, with the highest accuracy observed in treatment-naive patients. The Leuven and Leuven/Groningen score could especially be helpful for cases in which the nuclear medicine physician is uncertain.

Medical images are hampered by noise and relatively low resolution, which create a bottleneck in obtaining accurate and precise measurements of living organisms. Noise suppression and resolution enhancement are two examples of inverse problems. The aim of this study is to develop novel and robust estimation approaches rooted in fundamental statistical concepts that could be utilized in solving several inverse problems in image processing and potentially in image reconstruction. In this study, we have implemented Bayesian methods that have been identified to be particularly useful when there is only limited data but a large number of unknowns. Specifically, we implemented a locally adaptive Markov chain Monte Carlo algorithm and analyzed its robustness by varying its parameters and exposing it to different experimental setups. As an application area, we selected radionuclide imaging using a prototype gamma camera. The results using simulated data compare estimates using the proposed method over the current non-locally adaptive approach in terms of edge recovery, uncertainty, and bias. The locally adaptive Markov chain Monte Carlo algorithm is more flexible, which allows better edge recovery while reducing estimation uncertainty and bias. This results in more robust and reliable outputs for medical imaging applications, leading to improved interpretation and quantification. We have shown that the use of locally adaptive smoothing improves estimation accuracy compared to the homogeneous Bayesian model.

Aim/background: Dynamic PET imaging requires an input function typically obtained through blood sampling. Image-derived input functions (IDIFs) of the ascending aorta (AA), aortic arch, descending aorta (DA), or left ventricle (LV) offer non-invasive alternatives, especially with long-axial field-of-view (LAFOV) PET/CT systems enabling whole-body dynamic ¹⁸F-FDG imaging. This study aimed to validate uncorrected IDIFs derived from the AA, DA, aortic arch, and LV by comparing them to (late) venous whole-blood in patients undergoing LAFOV PET/CT.

Methods: Eleven oncology patients who underwent 70-min dynamic ¹⁸F-FDG PET/CT scans on a LAFOV PET/CT system after receiving an intravenous bolus injection of 3.0 MBq/kg were included. Seven venous blood samples were collected manually at approximately 5, 10, 15, 25, 35, 45, and 60 min post-injection (pi) and compared to IDIFs derived from the AA, aortic arch, DA, and LV. Bias between IDIFs and venous blood samples was assessed at each time point.

Results: IDIF accuracy relative to venous blood samples improved over time, with a median percentage bias <10% after 25 min pi. At 60 min pi, the aortic arch showed the smallest bias (median -1.1%, IQR 5.9%), followed by the AA (2.5%, IQR 7.0%), DA (5.1%, IQR 8.6%), and LV (7.4%, IQR 7.6%).

Conclusion: The high precision of aorta-derived IDIFs suggests that IDIFs are a reliable alternative to manual blood sampling for dynamic ¹⁸F-FDG PET imaging on a LAFOV PET/CT system. Using IDIFs reduces variability, simplifies protocols, minimizes radiation exposure, and enhances patient safety with a non-invasive approach.

Background and objective: This study aimed to assess the impact of upsampling and downsampling techniques on the noise characteristics and similarity metrics of scintigraphic images in nuclear medical imaging.

Methods: A physical phantom study using dynamic imaging was used to generate reproducible static images of varying count statistics. Naïve upsampling and downsampling with linear interpolation were compared against alternative methods based on the preservation of Poisson count statistics and principles of nuclear scintigraphic imaging; namely, linear interpolation with a Poisson resampling correction (upsampling) and a sliding window summation method (downsampling). For each resizing method, we computed the similarity of resized images to count-matched images acquired at the target grid size with the structural similarity index measure and the logarithm of the mean squared error. These image quality metrics were subsequently compared to those of two independent count-matched images at the target grid size (representing variance due to natural noise permutations) as a reference to establish an optimal resizing method.

Results: Only upsampled images with the Poisson resampling correction after linear interpolation produced images that were similar to those acquired at the target grid size. For downsampling, both linear interpolation and sliding window summation yielded similar outcomes for a reduction factor of 2. However, for a reduction factor of 4, only sliding window summation resulted in image similarity metrics in agreement with those at the target grid size.

Conclusions: The study underlines the importance of applying appropriate resizing techniques in nuclear medical imaging to produce realistic images at the target grid size.

Sydenham's chorea is an autoimmune reaction against cerebral basal ganglia associated with rheumatic fever, caused by group A beta-hemolytic streptococcus infection. Diagnosis of this condition is difficult because of significant delay between infection onset and symptoms presentation, resulting in few positive biological tests or imaging exams. We report the case of a nine-year-old boy exhibiting hemicorporal abnormal movements with tics for whom [¹⁸F]FDG PET/CT exam allowed to make the diagnosis, associated with anti-DNase B elevation. Other biology, spinal tap, EEG and imaging modality like MRI or scanner, were non-contributory.

Purpose: The aims of this study were to evaluate and compare fibroblast activation protein (FAP) expression and localization in surgically resected cholangiocarcinoma (CCA), primary and metastatic hepatocellular carcinoma (HCC), hepatocellular adenoma (HCA), and focal nodular hyperplasia (FNH), and to identify any association between CCA clinical or pathologic features and FAP expression.

Materials and methods: FAP immunostaining from surgically resected CCA (N = 58), primary intrahepatic and extrahepatic metastatic HCC (N = 148), HCA (N26), and FNH (N = 19) was scored (negative, weak positive, moderate positive or strong positive) from tissue microarrays. FAP expression was compared between groups. CCA FAP expression was compared to clinical and tumor pathology features.

Results: Moderate-strong FAP expression in the tumor stroma was present in 93.1% of CCA, 60.7% of extrahepatic metastatic HCC, 29.6% of primary HCC, 21.1% of FNH, and 11.6% of HCA. Moderate-strong FAP expression in tumor stroma was significantly more prevalent in CCA than HCC (p < 0.001), metastatic HCC (p = 0.005), HCA (p < 0.001) and FNH (p < 0.001). FAP was expressed in the stroma of all but one CCA (1.7%), and FAP expression in CCA tumor stroma was not associated with any clinical or tumor pathology features (p > 0.05, all).

Conclusion: FAP is expressed in the stroma of a high proportion (93%) of primary CCA independent of patient clinical or tumor pathology features. As such, these data provide the tissue basis for systematically evaluating FAP as a theranostic target across a broad range of CCA subtypes.

Introduction: In Positron Emission Tomography (PET) imaging, the use of tracers increases radioactive exposure for longitudinal evaluations and in radiosensitive populations such as pediatrics. However, reducing injected PET activity potentially leads to an unfavorable compromise between radiation exposure and image quality, causing lower signal-to-noise ratios and degraded images. Deep learning-based denoising approaches can be employed to recover low count PET image signals: nonetheless, most of these methods rely on structural or anatomic guidance from magnetic resonance imaging (MRI) and fails to effectively preserve global spatial features in denoised PET images, without impacting signal-to-noise ratios.

Methods: In this study, we developed a novel PET only deep learning framework, the Self-SiMilARiTy-Aware Generative Adversarial Framework (SMART), which leverages Generative Adversarial Networks (GANs) and a self-similarity-aware attention mechanism for denoising [18F]-fluorodeoxyglucose (18F-FDG) PET images. This study employs a combination of prospective and retrospective datasets in its design. In total, 114 subjects were included in the study, comprising 34 patients who underwent 18F-Fluorodeoxyglucose PET (FDG) PET imaging for drug-resistant epilepsy, 10 patients for frontotemporal dementia indications, and 70 healthy volunteers. To effectively denoise PET images without anatomical details from MRI, a self-similarity attention mechanism (SSAB) was devised. which learned the distinctive structural and pathological features. These SSAB-enhanced features were subsequently applied to the SMART GAN algorithm and trained to denoise the low-count PET images using the standard dose PET image acquired from each individual participant as reference. The trained GAN algorithm was evaluated using image quality measures including structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), normalized root mean square (NRMSE), Fréchet inception distance (FID), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR).

Results: In comparison to the standard-dose, SMART-PET had on average a SSIM of 0.984 ± 0.007, PSNR of 38.126 ± 2.631 dB, NRMSE of 0.091 ± 0.028, FID of 0.455 ± 0.065, SNR of 0.002 ± 0.001, and CNR of 0.011 ± 0.011. Regions of interest measurements obtained with datasets decimated down to 10% of the original counts, showed a deviation of less than 1.4% when compared to the ground-truth values.

Discussion: In general, SMART-PET shows promise in reducing noise in PET images and can synthesize diagnostic quality images with a 90% reduction in standard of care injected activity. These results make it a potential candidate for clinical applications in radiosensitive populations and for longitudinal neurological studies.

Purpose: ⁶⁸Ga-Trivehexin is a PET tracer targeting αvβ6-integrin, a transmembrane receptor that is frequently expressed by pancreatic cancer cells. This study aimed to determine the biokinetics, image contrast, and acquisition parameters for ⁶⁸Ga-Trivehexin PET imaging in pancreatic cancers.

Methods: 44 patients with pancreatic cancer underwent Trivehexin PET/CT between June 2021 and November 2022 (EK-242052023). Biokinetics and -distribution were extracted. Previous imaging follow-up imaging, and histological findings were used as reference standards. A one-way ANOVA test, followed by Tukey HSD post-hoc test was conducted. T-tests for subgroups ± chemotherapy prior to PET were performed. Based on dynamic PET data (n = 11) recorded over 45 min, time-activity curves were generated.

Results: ⁶⁸Ga-Trivehexin PET/CT detected 40 pancreatic cancers, SUVmax 12.6; range [5.1-30.8]; 39 liver metastases, SUVmax 7.9 [2.7-16.3]; 21 lymph node metastases, SUVmax 8.6 [2.5-15.0]; 17 peritoneal metastases, SUVmax 9.5 [4.0-16.9] and 14 other metastases, SUVmax 7.2 [2.9-13.1]. Tukey post-hoc analysis revealed significant differences for SUVmax in pancreatic cancer compared to SUVmax in liver metastases [4.74, 95%-CI (1.74, 7.75)], for SUVmax in pancreatic cancer to SUVmax in lymph node metastasis [4.07, 95%-CI (0.47, 7. 67)], for tumor-to-liver ratio (TLR) of liver metastasis to TLR of pancreatic cancer [1.82, 95%-CI (0.83, 2.80)], for TLR of pancreatic cancer to TLR of peritoneal carcinomatoses [-1.88, 95%-CI (-3.15, -0.61)], and TLR of pancreatic cancer to TLR of pleural carcinomatosis [-2.79, 95%-CI (-5.42, -0.18)]. When comparing subgroups ± chemotherapy prior to PET, TLR of pancreatic cancers and TLR of peritoneal carcinomatoses were significantly different. At 45 min p.i., the highest tumor-to-backround (TBR) was observed.

Conclusion: ⁶⁸Ga-Trivehexin is suitable for imaging of αvβ6-integrin expression in pancreatic cancer due to its ability to distinguish primary carcinoma and metastases from background tissue.