OBJECTIVE: This retrospective study was undertaken to assess the predictive efficacy of 18F-FDG PET/CT -derived radiomic features concerning the co-mutation status of epidermal growth factor receptor (EGFR) and TP53 in LUAD.
METHODS: A cohort of 150 LUAD patients underwent pretreatment 18F-FDG PET/CT scans with known mutation status of EGFR and TP53 were collected. The feature extraction based on their PET/CT images utilized the Pyradiomics package based on the 3D Slicer. The optimal radiomic features were selected through correlation analysis and the Gradient Boosting Decision Tree (GBDT) algorithm, followed by the construction of the radiomic model. The clinical model incorporated meaningful clinical variables, whereas the complex model integrated both the radiomic and clinical models. The area under the receiver operating characteristic curve (AUC) facilitated the comparison of prediction performance across the three models. The DCA gauged the clinical utility of these models.
RESULTS: The patient cohort was randomly allocated into a training set (n = 105) and a validation set (n = 45) in a 7:3 ratio. Eleven PET and eleven CT optimal radiomic features were selected to construct the radiomic model. The model showed a good ability to discriminate the co-occurrence of EGFR and TP53, with AUC equal to 0.850 in the training set, and 0.748 in the validation set, compared with 0.750 and 0.626 for the clinical model. The complex model exhibited the highest AUC values, with 0.880 and 0.794 in both sets, but there were no significant differences compared to the radiomic model. The DCA revealed favorable clinical value.
CONCLUSIONS:

OBJECTIVE: Our goal was to compare the lateralization of 68Ga-pentixafor PET/CT with adrenal vein sampling (AVS) in primary aldosteronism (PA) patients with unilateral lesions.
METHODS: We retrospectively enrolled 61 patients with PA and all patients showed unilateral nodular lesions on CT and underwent 68Ga-Pentixafor PET/CT. The general clinical data, imaging and AVS results were collected. The diagnostic efficiency of 68Ga-Pentixafor PET/CT imaging in PA patients was calculated by visual and semi-quantitative analysis to compare the consistency with AVS, and the correlation between CXCR4 express and 68Ga-Pentixafor uptake was performed.
RESULTS: The study included 42 unilateral PA (UPA) and 19 bilateral PA (BPA). The area under curve (AUC) of 68Ga-Pentixafor PET/CT to diagnosis UPA with 10 min maximum standardized uptake value (SUVmax) > 8.17 was 0.82 ([0.70-0.90], P < 0.001), and the sensitivity and specificity were 0.64 and 0.90, respectively. The maximal AUC of 68Ga-pentixafor PET/CT for the diagnosis UPA in patients with nodules with a diameter ≥1 cm was 0.87 ([0.73-0.95],P both <0.001,[10 min SUVmax=8.17 and 10 min mean standardized uptake value (SUVmean)=5.57]), and the sensitivity and specificity were 0.73 and 0.93, respectively. Unilateral adrenalectomy and significant CXCR4 expression were present in 32 UPA, including 27 aldosterone-producing adenoma and 5 idiopathic adrenal hyperplasia. Additionally, 68Ga-pentixafor uptake in adrenal lesions was significantly correlated with CXCR4 expression, and statistical differences in 68Ga-pentixafor uptake among IRS subgroups.
CONCLUSIONS: 68Ga-Pentixafor PET/CT can be helpful for subtyping diagnosis of PA patients with unilateral adrenal nodular, showing significant potential in non-invasive PA classification.

OBJECTIVE: This updated systematic review and bivariate meta-analysis aimed to investigate the diagnostic performance of 2-[18F]FDG PET/CT for the detection of recurrent disease in patients with differentiated thyroid cancer (DTC) who have negative 131I whole body scintigraphy and increased antithyroglobulin antibodies (TgAb) levels.
METHODS: The current systematic review was carried out following a preset protocol, and the \"Preferred Reporting Items for a Systematic Review and Meta-Analysis\" served as a guideline for its development and reporting. A comprehensive research of the PubMed/MEDLINE, Embase and Cochrane library databases was conducted until June 2024.
RESULTS: Between 2002 and 2023, 13 studies (608 patients) published on this topic were selected. The pooled sensitivity, specificity, positive predictive value, negative predictive value and accuracy of 2-[18F]FDG PET or PET/CT were 84% (95%CI: 78-87%), 82% (95%CI: 78-86%), 72% (95%CI: 67-76%), 90% (95%CI: 87-93%) and 83% (95%CI: 79%-86%) respectively. The pooled positive and negative likelihood ratios (LR+ and LR - ) and the diagnostic odds ratio (DOR) were 0.180 (95%CI: 0.128-0.253), 3.214 (95%CI: 2.357-4.383), and 17.863 (95%CI: 10.475-30.462), respectively. No statistically significant heterogeneity among the studies was found for all the metrics evaluated (I2 < 50%).
CONCLUSIONS: 2-[18F]FDG PET/CT demonstrated a good diagnostic performance in patients with DTC and increased TgAb. Although more studies are warranted, the provided evidence-based data should support the integration of 2-[18F]FDG PET/CT in clinical and diagnostic guidelines on DTC patients with increased TgAb.

Lung cancer is a predominant cause of cancer-related mortality worldwide, necessitating precise tumor segmentation of medical images for accurate diagnosis and treatment. However, the intrinsic complexity and variability of tumor morphology pose substantial challenges to segmentation tasks. To address this issue, we propose a multitask connected U-Net model with a teacher-student framework to enhance the effectiveness of lung tumor segmentation. The proposed model and framework integrate PET knowledge into the segmentation process, leveraging complementary information from both CT and PET modalities to improve segmentation performance. Additionally, we implemented a tumor area detection method to enhance tumor segmentation performance. In extensive experiments on four datasets, the average Dice coefficient of 0.56, obtained using our model, surpassed those of existing methods such as Segformer (0.51), Transformer (0.50), and UctransNet (0.43). These findings validate the efficacy of the proposed method in lung tumor segmentation tasks.

UNASSIGNED: Infective endocarditis (IE) is a serious and fatal condition, with prosthetic valve endocarditis representing the worst prognosis. The recommended nuclear imaging modality 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography ([18F]FDG PET/CT) has limitations. In this case series, we present two patients with IE scanned with a novel PET tracer [64Cu]Cu-DOTATATE ([64Cu]Cu-[1,4,7,10-tetraazacyclododecane-N,N\',N″,N‴-tetra acetic acid]-d-Phe1, Tyr3-octreotate).
UNASSIGNED: An 84-year-old female patient (Patient 1) with a biological mitral valve prosthesis (MVP) was admitted acutely from the outpatient clinic. Transoesophageal echocardiography showed vegetations on the MVP. The patient underwent [64Cu]Cu-DOTATATE PET/CT, which showed uptake at the site of infection. The patient underwent surgical valve replacement. The post-operative period was without significant complications, and the patient was discharged home. In another case, a 72-year-old male patient (Patient 2) with a medical history of mild mitral valve stenosis, aortic valve stenosis, and gastrointestinal stromal tumour was admitted to the hospital for back and abdominal pain and subfebrile episodes. Transoesophageal echocardiography showed large vegetations in the native aortic valve. The patient underwent [64Cu]Cu-DOTATATE PET/CT, which showed no uptake at the site of the suspected infection. The patient underwent surgical valve replacement. The post-operative period was characterized by Candida albicans sternitis, and after prolonged hospitalization, the patient died of respiratory failure as a complication of sepsis.
UNASSIGNED: In conclusion, this is the first case series presenting two patients with definite IE (modified Duke criteria), who were scanned with the novel [64Cu]Cu-DOTATATE PET/CT. Patient 1, with endocarditis in the MVP, showed an uptake of the tracer, while Patient 2, with native aortic valve endocarditis, did not show any uptake.

Neuroendocrine tumors (NETs) may manifest as large masses in the abdominopelvic region that exhibit mobility and shifting, potentially leading to diagnostic uncertainty both before and after treatment. A meticulous analysis of PET/CT scans is advantageous in accurately identifying the precise location of large abdominopelvic masses. Tumor heterogeneity may be present in NETs with large abdominopelvic masses and may be easily identified on dual-tracer (68Ga-DOTATATE and 18F-FDG) PET/CT scans. In this scenario, the combined use of chemotherapy and peptide receptor radionuclide therapy is a more effective treatment option than monotherapy. Here, we present a case of a NET with wandering, large, heterogeneous masses in the abdominopelvic regions that were identified using dual-tracer PET/CT. After the administration of temozolomide chemotherapy in a combined chemotherapy-peptide receptor radionuclide therapy approach, we observed an upregulation in the expression of somatostatin receptor in the abdominopelvic masses.

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BACKGROUND: In modern positron emission tomography (PET) with multi-modality imaging (e.g., PET/CT and PET/MR), the attenuation correction (AC) is the single largest correction factor for image reconstruction. One way to assess AC methods and other reconstruction parameters is to utilize software-based simulation tools, such as a lesion insertion tool. Extensive validation of these simulation tools is required to ensure results of the study are clinically meaningful.
OBJECTIVE: To evaluate different PET AC methods using a synthetic lesion insertion tool that simulates lesions in a patient cohort that has both PET/MR and PET/CT images. To further demonstrate how lesion insertion tool may be used to extend knowledge of PET reconstruction parameters, including but not limited to AC.
METHODS: Lesion quantitation is compared using conventional Dixon-based MR-based AC (MRAC) to that of using CT-based AC (CTAC, a \"ground truth\"). First, the pre-existing lesions were simulated in a similar environment; a total of 71 lesions were identified in 18 pelvic PET/MR patient images acquired with a time-of-flight simultaneous PET/MR scanner, and matched lesions were inserted contralaterally on the same axial slice. Second, synthetic lesions were inserted into four anatomic target locations in a cohort of four patients who didn\'t have any observed clinical lesions in the pelvis.
RESULTS: The matched lesion insertions resulted in unity between the lesion error ratios (mean SUVs), demonstrating that the inserted lesions successfully simulated the original lesions. In the second study, the inserted lesions had distinct characteristics by target locations and demonstrated negative max-SUV%diff trends for bone-dominant sites across the patient cohort.
CONCLUSIONS: The current work demonstrates that the applied lesion insertion tool can simulate uptake in pelvic lesions and their expected SUV values, and that the lesion insertion tool can be extended to evaluate further PET reconstruction corrections and algorithms and their impact on quantitation accuracy and precision.

Objective: This study aimed to predict therapeutic efficacy among diffuse large B-cell lymphoma (DLBCL) after R-CHOP (-like) therapy using baseline 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) radiomics. Methods: A total of 239 patients with DLBCL were enrolled in this study, with 82 patients having refractory/relapsed disease. The radiomics signatures were developed using a stacking ensemble approach. The efficacy of the radiomics signatures, the National Comprehensive Cancer Network-International Prognostic Index (NCCN-IPI), conventional PET parameters model, and their combinations in assessing refractory/relapse risk were evaluated using receiver operating characteristic (ROC) curves, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy and decision curve analysis. Results: The stacking model, along with the integrated model that combines stacking with the NCCN-IPI and SDmax (the distance between the two lesions farthest apart, normalized to the patient\'s body surface area), showed remarkable predictive capabilities with a high area under the curve (AUC), sensitivity, specificity, PPV, NPV, accuracy, and significant net benefit of the AUC (NB-AUC). Although no significant differences were observed between the combined and stacking models in terms of the AUC in either the training cohort (AUC: 0.992 vs. 0.985, p = 0.139) or the testing cohort (AUC: 0.768 vs. 0.781, p = 0.668), the integrated model exhibited higher values for sensitivity, PPV, NPV, accuracy, and NB-AUC than the stacking model. Conclusion: Baseline PET radiomics could predict therapeutic efficacy in DLBCL after R-CHOP (-like) therapy, with improved predictive performance when incorporating clinical features and SDmax.

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