Annals of Nuclear Medicine最新文献

Backgrounds

Automated PROMISE (aPROMISE), which is an artificial intelligence-supported software for prostate-specific membrane antigen (PSMA) PET/CT based on PROMISE V2, has demonstrated diagnostic utility with better correspondence rates compared to manual diagnosis. However, previous studies have consistently utilized ¹⁸F-PSMA PET/CT. Therefore, we investigated the diagnostic utility of aPROMISE using both ¹⁸F- and ⁶⁸ Ga-PSMA PET/CT of Japanese patients with metastatic prostate cancer (mPCa).

Materials and methods

We retrospectively evaluated 21 PSMA PET/CT images (⁶⁸ Ga-PSMA PET/CT: n = 12, ¹⁸F-PSMA PET/CT: n = 9) from 21 patients with mPCa. A single, well-experienced nuclear radiologist performed manual diagnosis following PROMISE V2 and subsequently performed aPROMISE-assisted diagnosis to assess miTNM and details of metastatic sites. We compared the diagnostic time and correspondence rates of miTNM diagnosis between manual and aPROMISE-assisted diagnoses. Additionally, we investigated the differences in diagnostic performance between the two radioisotopes.

Results

aPROMISE-assisted diagnosis was significantly associated with shorter median diagnostic time compared to manual diagnosis (427 s [IQR: 370–834] vs. 1,114 s [IQR: 922–1291], p < 0.001). The time reduction with aPROMISE-assisted diagnosis was particularly notable when using ⁶⁸ Ga-PSMA PET/CT. aPROMISE had high diagnostic accuracy with 100% sensitivity for miT, M1a, and M1b stages. Notably, for M1b stages, aPROMISE achieved 100% sensitivity and specificity, regardless of the type of radioisotope used. However, aPROMISE was misinterpreted in lymph node detection in some cases and missed five visceral metastases (2 adrenal and 3 liver), resulting in lower sensitivity for miM1c stage (63%). In addition to detecting metastatic sites, aPROMISE successfully provided detailed metrics, including the number of metastatic lesions, total metastatic volume, and SUV mean.

Conclusions

Despite the preliminary nature of the study, aPROMISE-assisted diagnosis significantly reduces diagnostic time and achieves satisfactory accuracy compared to manual diagnosis. While aPROMISE is effective in detecting bone metastases, its limitations in identifying lymph node and visceral metastases must be carefully addressed. This study supports the utility of aPROMISE in Japanese patients with mPCa and underscores the need for further validation in larger cohorts.

Purpose

Accurate differentiation of Parkinsonism subtypes—including Parkinson’s disease (PD), multiple system atrophy (MSA), and progressive supranuclear palsy (PSP)—is essential for clinical prognosis and treatment planning. However, this remains a major challenge due to overlapping symptomatology and high inter-individual variability in cerebral glucose metabolism patterns observed on fluorodeoxyglucose positron emission tomography (FDG-PET).

Methods

To address these challenges, we propose PETFormer-SCL, a clinically informed deep learning framework that integrates convolutional neural networks (CNNs) with a channel-wise Transformer module, guided by supervised contrastive learning (SCL). This architecture is designed to enhance disease-specific feature learning while mitigating individual variability.

Results

Trained on 945 patients and evaluated on an independent test cohort of 330 patients (1275 in total), PETFormer-SCL achieved AUCs of 0.9830, 0.9702, and 0.9565 for MSA, PD, and PSP, respectively. In addition, class activation maps (CAMs) highlighted key disease-related brain regions—including the cerebellum, midbrain, and basal ganglia—demonstrating strong alignment with known pathophysiological findings.

Conclusions

PETFormer-SCL not only achieves high diagnostic accuracy, particularly for subtypes with overlapping phenotypes, but also enhances interpretability. These results support its potential as a reliable clinical decision-support tool for the early and differential diagnosis of Parkinsonism.

Objective

This systematic review aims to assess the diagnostic performance of FDG PET/CT and FAPi PET/CT in patients with gastric carcinoma, specifically for the evaluation of primary tumors, metastatic lymph nodes, and metastatic lesions.

Methods

Following PRISMA guidelines, relevant databases were searched until January 20, 2023. Studies reporting histopathology or surgical outcomes as the reference standard were included. Pooled estimates of diagnostic accuracy were generated using meta-analysis.

Results

Six studies with 167 patients who underwent FDG PET/CT and 169 patients who underwent FAPi PET/CT were included. For the detection of primary gastric carcinoma, FDG PET/CT demonstrated a pooled sensitivity of 0.86 (95% CI 0.47–0.98) and specificity of 0.70 (95% CI 0.39–0.90). The pooled positive likelihood ratio was 2.9 (95% CI 1.0–8.4), and the negative likelihood ratio was 0.21 (95% CI 0.03–1.30). The diagnostic odds ratio was 14 (95% CI 1–224), and the area under the SROC curve was 0.82. For FAPi PET/CT, pooled sensitivity and specificity for detecting primary gastric carcinoma were 0.90 (95% CI 0.90–0.90) and 0.50 (95% CI 0.50–0.50), respectively. The pooled positive and negative likelihood ratios were 1.8 (95% CI 1.8–1.8) and 0.20 (95% CI 0.20–0.20), respectively. The diagnostic odds ratio was 9 (95% CI 9–9), and the area under the SROC curve was 0.54.

Conclusion

FAPi PET/CT demonstrated comparable diagnostic performance to FDG PET/CT in the diagnosis of primary gastric carcinoma, lymph nodal metastases, and metastatic lesions. When compared to histopathology or surgical findings, FAPi PET/CT showed good sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio.

Objective

Gallium-68-labelled fibroblast activation protein inhibitor ([⁶⁸ Ga]Ga-FAPI) is a tumour-stromal imaging agent showing complementary value alongside fluorine-18 fluorodeoxyglucose ([¹⁸F]FDG) in cancer imaging. This study investigated the feasibility of a same-day dual-tracer positron emission tomography/computed tomography (PET/CT) protocol with [⁶⁸ Ga]Ga-FAPI-04 following [¹⁸F]FDG in patients presenting with negative or equivocal [¹⁸F]FDG.

Methods

Patients with negative or equivocal [¹⁸F]FDG findings underwent dual-tracer PET/CT (named FDG-mixed FAPI PET/CT, abbreviated to mFAPI PET/CT) on the same day, with [⁶⁸ Ga]Ga-FAPI-04 administered 4.0–7.75 h following [¹⁸F]FDG injection. Lesion detection rates and lesion-to-background uptake ratios (LBRs) were compared between [¹⁸F]FDG and mFAPI PET/CT.

Results

Forty-four patients were included in the analysis. The mFAPI PET was superior to [¹⁸F]FDG PET for primary tumour detection (86.2% [25/29] vs. 37.9% [11/29], P < 0.001), and showed higher LBRs (P < 0.001) in various types of cancer. For metastatic lesions detection, mFAPI PET yielded a greater number of positive lesions (90.3% [317/351] vs. 44.7% [157/351], P < 0.001) and higher LBRs than [¹⁸F]FDG in most lesions, especially in lymph node, peritoneal, and liver metastases (all P < 0.05). The mFAPI PET/CT scans had a prominent impact on patients with negative or equivocal [¹⁸F]FDG in different clinical situations, including characterizing suspicious lesions in 88.9% (8/9), locating the primary site in 46.2% (6/13), upgrading of tumour staging in 81.8% (9/11), and identification of recurrence in 81.8% (9/11).

Conclusions

A same-day dual-tracer PET/CT protocol with [⁶⁸ Ga]Ga-FAPI-04 following [¹⁸F]FDG is feasible for enhancing the ability to identify indeterminate lesions, localize unknown malignant primary tumour sites, and accurately provide staging and restaging in patients presenting with negative or equivocal [¹⁸F]FDG.

Trial registration

NCT05034146. Registered February 23, 2021.

Objective

Medication-related osteonecrosis of the jaw (MRONJ) is a severe complication of bone-modifying agent (BMA) therapy in patients with prostate cancer and bone metastasis. This study aimed to assess the effectiveness of the temporal changes in jaw-specific bone scan index (ΔBSIJ) as quantitative markers for early prediction of MRONJ in patients with prostate cancer receiving BMA therapy.

Methods

This retrospective study included 33 patients with prostate cancer with bone metastases who underwent bone scintigraphy before and after BMA initiation. BSIJ was measured using BONENAVI software, and the difference between pre- and post-BMA BSIJ values was considered ΔBSIJ. Statistical analyses, including paired t-test, receiver operating characteristic (ROC) curve analysis, and Kaplan–Meier survival estimate, were employed to assess the predictive value of ΔBSIJ for MRONJ.

Results

Of the 33 patients, 10 developed MRONJ during a median follow-up period of 29 months. ΔBSIJ was significantly higher in the MRONJ group than in the non-MRONJ group (0.05 vs. – 0.04, p = 0.002). ROC analysis revealed the highest area under the curve (AUC = 0.823) for ΔBSIJ compared with the pre- and post-BMA BSIJ values. A ΔBSIJ cutoff of 0.039 predicted MRONJ with 60% sensitivity and 91% specificity. Patients with ΔBSIJ ≥ 0.039 exhibited significantly shorter MRONJ-free survival than those with ΔBSIJ < 0.039 (median: 18.4 months vs. not reached, p < 0.001).

Conclusion

ΔBSIJ is a novel and clinically useful quantitative marker for the early detection of MRONJ in patients with prostate cancer receiving BMA therapy. This study highlights the potential of leveraging functional imaging and temporal changes in BSIJ to improve MRONJ management.

Purpose

This study aimed to evaluate the prognostic predictive ability of MET PET/CT-derived imaging biomarkers in patients with localized non-small cell lung cancer (NSCLC) undergoing single-fraction carbon-ion radiotherapy (CIRT) and to clarify the additional prognostic information these biomarkers can provide beyond the standard UICC staging protocol.

Methods

With institutional review board approval, 67 localized NSCLC patients eligible for CIRT between 2007 and 2012 were included. Single-fraction doses of 40–50 Gy were irradiated. MET PET imaging using the Toshiba Aquiduo or Siemens Biograph 16 commenced 20 min post 740 MBq MET injection before CIRT. Experienced radiologists analyzed the images, defining metabolic tumor volume (MTV) as areas with SUV > 1.5. Statistical analysis was performed using SPSS 29, including Cox proportional hazard models for disease-free and overall survival.

Results

Seven cases with Tis of T stage were excluded because of low MET radiotracer uptake. A total of 60 patients were analyzed: 36 males and 24 females with a mean age of 73 years; 35 cases of T1, 24 cases of T2, and one T3 case. The average follow-up period was 74.3 months. The univariate Cox proportional hazard analyses showed that SUVmax, MTV, and total lesion retention (TLR) correlated with disease-free survival (DFS), while no significant difference was noted in treatment dose. For overall survival (OS), solid tumor diameter, SUVmax, MTV, TLR, and sex showed significant correlations in the univariate analysis. The multivariate analysis identified MTV as the only significant prognostic factor for both DFS and OS. Kaplan–Meier survival curves further supported these findings, with log-rank tests indicating a significant difference in survival duration related to MTV in both DFS and OS.

Conclusion

MTV in pre-treatment MET PET/CT would be a valuable predictor of DFS and OS of localized NSCLC treated with single-fraction CIRT.

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) present a diagnostic challenge due to their heterogeneous nature and varying somatostatin receptor (SSTR) expressions. Although rare, their incidence has increased with earlier detection, which can improve overall survival. Functional SSTR imaging, especially with radiolabeled somatostatin analogs like DOTATATE, DOTANOC, and DOTATOC, offers greater sensitivity and specificity than anatomic imaging. However, differences in pharmacokinetics and binding affinities among these radiotracers lead to variability in diagnostic performance and clinical utility. As theranostics becomes central to GEP-NEN management, standardizing radiotracer selection is essential for diagnostic consistency and personalized therapy. This review summarizes current literature on the comparative performance of the three most commonly used radiotracers in GEP-NEN imaging, covering their SSTR subtype affinities, diagnostic accuracy, biodistribution, dosimetry, and clinical impact. Among the radiotracers, DOTATOC is considered the most superior for functional imaging due to its broad affinity for SSTR2 and SSTR5, yielding the highest tumor-to-background ratio (TBR). In comparison, DOTANOC is less effective because its lower tumor uptake and slower clearance result in a reduced TBR. Although it binds to SSTR2, SSTR3, and SSTR5, the low expression of SSTR3 in GEP-NENs limits the advantage of DOTANOC broader receptor affinity. DOTATATE exhibits the highest tumor uptake but also shows higher normal tissue uptake, potentially reducing diagnostic performance. However, its better tumor-to-bone uptake ratio makes it effective for detecting bone lesions, and it is also suitable for peptide receptor radionuclide therapy (PRRT) due to its prolonged intracellular retention. The sensitivity and specificity of these radiotracers vary across studies, with comparable clinical impact and dosimetry, suggesting they may be used interchangeably. However, DOTATATE combines high SSTR2 affinity, strong cellular retention, and rapid clearance, making it effective for both imaging and therapy. Its widespread use simplifies tracer inventory and supports harmonization in radiotheranostics, particularly in light of recent FDA approvals and the evolving landscape of theranostic practices. PET/CT scans are recommended over SPECT/CT for GEP-NEN diagnosis due to their higher accuracy. Enhancements in diagnostic performance may be achieved by combining SSTR tracers with radionuclides like ⁶⁴Cu and ¹⁸F, using somatostatin antagonists as tracers, or employing dual-tracer protocols with ¹⁸F-FDG.

Purpose

The purpose of the current study was to evaluate the diagnostic accuracy of FDG PET/CT radiomics in predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC), and to compare it with conventional metabolic parameters of FDG PET/CT through a systematic review and meta-analysis.

Methods

The PubMed, EMBASE, and Cochrane databases were searched for studies evaluating the diagnostic performance of FDG PET/CT in predicting MVI in HCC patients. We calculated the pooled area under the curve (AUC) for predicting MVI using FDG PET/CT analyzed with radiomics methods and compared the results with those predicted through visual or semi-quantitative analysis. The study was conducted and registered in PROSPERO (International Prospective Register of Systematic Reviews) with the registration number CRD42023466842.

Results

The pooled AUC for predicting MVI from three studies (274 patients) analyzed using radiomics methods was 0.79 (95% CI; 0.75–0.84), with various model algorithms and selected features. The pooled AUC for six studies (368 patients) using visual analysis was 0.76 (95% CI; 0.73–0.80), and the pooled AUC for nine studies (661 patients) using semi-quantitative analysis was 0.80 (95% CI; 0.76–0.83). The diagnostic performance of the three analysis methods did not show a statistically significant difference.

Conclusion

FDG PET/CT radiomics for predicting MVI in HCC showed diagnostic performance similar to that of conventional visual or semi-quantitative analysis methods. Further large-scale multicenter studies are necessary to substantiate the diagnostic accuracy of FDG PET/CT radiomics for predicting MVI in HCC patients.

Purpose

The study aimed to assess the prognostic value of non-perfusion parameters for gated myocardial perfusion imaging (MPI) performed using Cadmium-Zinc-Telluride (CZT) single-photon emission computed tomography (SPECT) for individuals with normal myocardial perfusion.

Methods

We analyzed data from consecutive patients who underwent thallium-201 MPI SPECT with normal perfusion. Major adverse cardiovascular events (MACEs) were recorded during a 2-year follow-up. Non-perfusion parameters were evaluated as predictors of MACEs.

Results

Among 1570 patients with normal SPECT perfusion, 80 (5.1%) experienced MACEs over a mean follow-up of 22.5 ± 10.8 months: 12 (0.8%) had cardiac death, and 68 (4.3%) underwent coronary revascularization due to significant coronary artery disease. Independent predictors of MACEs included worsening post-stress ejection fraction (HR: 1.971; p = 0.008), and increased lung-to-heart ratio (HR: 2.207; p = 0.001). Kaplan–Meier analysis showed the highest MACEs’ incidence in patients with two of these factors (p < 0.001). Among patients with normal resting ejection fraction, EF worsening (OR: 2.16; p = 0.004) and increased lung-to-heart ratio (OR: 1.91; p = 0.0013) both remained strong predictors.

Conclusions

Although normal myocardial perfusion typically indicates low risk for obstructive coronary artery disease, worsening post-stress ejection fraction and increased lung-to-heart ratio are crucial prognostic indicators. Importantly, these non-perfusion parameters retain their prognostic value even in patients without clinical heart failure, highlighting their relevance in comprehensive risk stratification beyond perfusion assessment alone.