Annals of Nuclear Medicine最新文献

Background: This study aimed the role of volumetric and dissemination features of staging [18F]PSMA-1007 PET/CT in predicting progression-free survival (PFS) in patients with prostate cancer (PCa) and their relationship with the main clinical data (ISUP grade groups, number of lesions, PSA).

Methods: We included 164 patients with high-risk PCa who underwent baseline [18F]PSMA-1007 PET/CT. With the help of LIFEx version 7.7, the main volumetric and dissemination PET parameters were semi-automatically extracted: PSMA-prostate tumor volume (PSMA-TV), PSMA-prostate total lesion (PSMA-TL), PSMA total TV (PSMA-TTV), PSMA total TL (PSMA-TTL) and Dmax corrected for body-surface-area (Dmax_bsa). Spearman rank correlations between semiquantitative PET features and the clinical variables were analyzed. PFS estimates were plotted with the Kaplan-Meier method.

Results: A high correlation was seen between the number of lesions and both PSMA-TTL (r 0.725), and Dmaxbsa (r 0.935). A moderate correlation was registered between PSA and PSMA-TTV (r 0.333), PSMA-TTL (r 0.441), Dmax_bsa (r 0.333), as well as between number of lesions and PSMA-TTV (r 0.342). After a median follow-up of 17 months (range 2-45), relapse/progression happened in 17 patients (10%). PSA level, presence of distant metastases at staging, PSMA-TV, PSMA-TL, PSMA-TTL and Dmax_bsa were significantly associated with PFS at univariate analysis, but only the presence of distant metastases, PSMA-TTL and Dmax_bsa were confirmed to be independent prognostic factors.

Conclusion: Volumetric and dissemination features derived by staging [18F]PSMA-1007 PET/CT were significantly correlated with PSA and number of lesions. The combination of PSMA-TTL and Dmax_bsa was the best predictor of PFS and may help to better stratify PCa patients.

Objective: Bone scintigraphy is widely employed for detecting bone metastases, with the bone scan index (BSI) gaining traction as a quantitative tool in this domain. VSBONE BSI, an automated image analysis software, identifies abnormal hyperaccumulation areas in bone scintigraphy and computes BSI scores. The software, originally developed using data from conventional gamma cameras (C-Camera), has undergone two upgrades. This study hypothesized that the upgrades enhance the diagnostic accuracy for bone metastases and assessed the software's applicability to images obtained using a cadmium-zinc-telluride detector gamma camera (CZT-Camera). The aim was to compare the diagnostic accuracy of VSBONE BSI across software versions using both conventional and CZT detectors and to evaluate its utility.

Methods: A total of 287 patients with breast or prostate carcinoma who underwent whole-body bone scintigraphy were included. VSBONE BSI automatically analyzed and calculated the BSI. The analysis results were compared with the presence or absence of metastases for each software version by using detector type of camera. The diagnostic agreement was evaluated.

Results: Receiver operating characteristic analysis showed an area under the curve (AUC) exceeding 0.7 across all groups, indicating good diagnostic performance. AUC values significantly increased with version upgrades for all patients and for breast carcinoma patients. In metastasis-negative cases, BSI values decreased with each software version upgrade, with the reduction being more pronounced in breast carcinoma patients scanned with the CZT-Camera.

Conclusions: Using the VSBONE BSI, version 2 or 3 had a higher rate of diagnostic concordance with the clinical prognosis than version 1. In metastasis-negative patients, newer software versions yielded lower BSI values, especially for breast carcinoma patients scanned using the CZT-Camera, highlighting the improved diagnostic accuracy of the updated software.

Aim: This study aimed to analyze the clinicopathologic and metabolic parameters derived from staging ¹⁸F-FDG PET/CT that can predict recurrence patterns in non-small-cell lung cancer (NSCLC) after curative surgery.

Material and methods: Retrospective study included stage I-III NSCLC patients with a baseline ¹⁸F-FDG PET/CT scan. Relapse patterns were analyzed based on location, lesion, and organ-specific recurrence. Clinicopathologic variables were recorded. Three distinct categories of variables were obtained: standardized uptake value (SUV)-based metrics, heterogeneity parameters, and morphological features. The relation of relapse patterns with clinicopathologic and metabolic parameters was analyzed using the uni-multivariate logistic regression.

Results: Out of 173 patients, 104 experienced recurrences, with 66% presenting distant involvement and 56.7% exhibiting polymetastatic disease at initial recurrence. Patient age, pathologic lymphovascular invasion, and normalized SUVmax perimeter distance (nSPD) were considered as risk factors for early recurrence. Adenocarcinoma histology was identified as an independent variable for distant recurrence. Patient age, number of metastatic mediastinal lymph nodes at staging (nN), sphericity, normalized SUVpeak to centroid distance (nSCD), entropy, low gray-level run emphasis, and high gray-level run emphasis were independent variables for polymetastatic disease. Certain variables were correlated with organ-specific recurrence. Bone recurrence was related to nN and SUVmean. Brain recurrence was related to adenocarcinoma histology. Lung recurrence was associated with coefficient of variation and nSPD.

Conclusion: The metabolic profile of lung primary tumors obtained from ¹⁸F-FDG PET/CT seems to be predictive of recurrence patterns that are closely linked to the overall survival of NSCLC patients. These findings could help in the development of personalized follow-up strategies based on an individual's recurrence pattern.

Objective: At present, most of the targeted imaging based on insulin-like growth factor 1 receptor (IGF-1R) is for tumor research, and there is no IGF-1R-targeted imaging for Graves' ophthalmopathy(GO). This study aims to develop a peptide probe, ^99mTc-Z_IGF1R:4551-GGGC, targeting the IGF-1R, and to achieve specific imaging in Graves' disease (GD) animal models exhibiting GO.

Methods: 99mTc-ZIGF1R:4551-GGGC probe was synthesized using a direct labeling method and its labeling efficiency assessed via instant thin-layer chromatography (ITLC). Western blot analysis confirmed the overexpression of IGF-1R in malignant melanoma B16F10 cells. Subsequent SPECT/CT whole-body imaging of B16F10 tumor-bearing mice evaluated the probe's targeting accuracy. In addition, a GO model was established using an electroporation immunoassay, followed by serological and histopathological examinations. The GO models then underwent 99mTc-ZIGF1R:4551-GGGC SPECT/CT imaging to assess eye-targeted imaging capabilities.

Results: The peptide probe exhibited a labeling efficiency exceeding 90%. Both GD and GO models were effectively created via electroporation immunoassay. Imaging results indicated significant accumulation and retention of the peptide probes in the tumors of B16F10 tumor-bearing mice. In the GO models, probe uptake was predominantly observed in retrobulbar tissues, contrasting with primary accumulation in the lungs and gastrointestinal tract in normal mice, where only minimal tracer was observed in retrobulbar tissues. Notably, GO mice demonstrated higher probe uptake and prolonged retention.

Conclusion: This study successfully established GD and GO models, reducing the duration of the immune cycle. Moreover, a peptide probe targeting IGF-1R was synthesized, enabling specific imaging of retrobulbar tissues in GO models.

Objective: This study aims to accurately classify ATN profiles using highly specific amyloid and tau PET ligands and MRI in patients with cognitive impairment and suspected Alzheimer's disease (AD). It also aims to explore the relationship between quantified amyloid and tau deposition and cognitive function.

Methods: Twenty-seven patients (15 women and 12 men; age range: 64-81 years) were included in this study. Amyloid and tau PET scans were performed using ¹⁸F-NAV4694 and ¹⁸F-MK6240, respectively. For each patient, amyloid and tau PET images were visually assessed and classified as either amyloid-positive or amyloid-negative, and as ¹⁸F-MK6240 Braak stage 0 (tau-negative) or Braak stages I-VI (tau-positive). Voxel-based morphometry of three-dimensional T1-weighted MRI was used to evaluate neurodegeneration. Amyloid and tau depositions were quantified using the Centiloid scale and standardized uptake value ratio (SUVR), respectively. Global cognitive function was assessed with the Mini-Mental State Examination (MMSE).

Results: Patients were categorized into seven ATN profiles. Six patients (22%) exhibited a normal AD biomarker profile, 15 patients (56%) fell within the Alzheimer's continuum, and 14 patients (52%) were diagnosed with AD. Additionally, six patients (22%) displayed non-AD pathological changes. Positive and negative findings of amyloid and tau PET were concordant in 24 patients (89%). Among the 14 patients diagnosed with AD, the Centiloid scale for amyloid deposition did not show a significant negative correlation with MMSE scores (r = 0.269, p = 0.451). In contrast, the SUVR for tau deposition in the neocortex exhibited a significant negative correlation (r = -0.689, p = 0.014), while tau deposition in the mesial temporal region did not show a significant correlation (r = 0.158, p = 0.763).

Conclusion: Highly specific amyloid and tau PET scans, along with MRI, can be utilized to accurately classify ATN profiles in patients with cognitive impairment and suspected AD. The discordance in amyloid and tau PET findings in three patients allowed for a more precise AD diagnosis. Furthermore, tau PET imaging provided insight into the propagation of tau deposition in the neocortex beyond the mesial temporal region, which is associated with cognitive decline.

Objective: Data-driven respiratory gating (DDG) has recently been introduced to improve image quality in the PET portion of PET/CT examinations. The latest DDG system does not require any external equipment or extended examination time. In this study, we investigated the effects of the new DDG system on the visualization and quantification of breast and upper abdominal cancers, comparing the results with those obtained using the standard free-breathing (STD) PET protocol.

Methods: A total of 223 cancer lesions (138 breast and 85 upper abdominal) evaluated with FDG PET/CT were included in this study. PET images were reconstructed using the STD and DDG algorithms. Lesion blurring and conspicuity were each visually graded on a three-point scale. The longest diameter (LD), SUVmax, and metabolic tumor volume (MTV) of the lesions were used for quantitative analysis. % change in SUVmax or MTV was calculated from the metrics in STD and DDG images. Fifty-six texture features (TFs) were also evaluated. Visual scores and quantitative metrics were compared between STD and DDG images. % change in SUVmax or MTV was compared in the lesion location groups or in the high and low groups based on LD, SUVmax, or MTV in STD images.

Results: Visual scores for lesion blurring and conspicuity were both significantly higher in DDG than in STD PET images. SUVmax and MTV were significantly higher and lower, respectively, in DDG than in STD images. An increase in SUVmax and a decrease in MTV were observed in 96% and 86% of all lesions, respectively. Group analysis revealed that % change in SUVmax was greater in the upper abdominal than the breast lesions and % change in MTV was greater in the high LD and high MTV groups than in the low LD and low MTV groups, respectively. Quantitative changes in TFs were observed between STD and DDG images for most of the features.

Conclusion: This study demonstrated that DDG improved visualization and quantification of breast and upper abdominal cancers in FDG PET/CT examinations. DDG PET images exhibited an increase in SUVmax, a decrease in MTV, and changes in TFs.