The study aims to determine the physiological and pathophysiological distribution of the radiopharmaceutical (Ga68-PSMA-617) and investigate whether there are differences in distribution according to the laboratory, histopathological and clinical findings that can affect image evaluation. Also, we aimed to determine cut-off values to distinguish physiological and pathological uptake in prostate, bone, and lymph nodes. 229 prostate cancer patients who underwent Ga68-PSMA PET/CT at our department were retrospectively analyzed. The patients were grouped according to PET/CT results, Gleason scores, PSA values, received treatments, metastatic status and other laboratory values. The SUV values of the organs, tissues, and pathological lesions of the patients in these subgroups were compared among themselves. No significant difference was detected in the physiological uptake of lymph nodes and bone between the groups. In the group with patients that received androgen deprivation therapy (ADT), the bone metastasis SUV values were found to be higher and the SUV values of the submandibular gland and renal cortex were found to be lower (Mann-Whitney U, p = 0.043; 0.004; 0.01, respectively). In the group with patients who received radiotherapy, the normal prostate tissue SUV values were determined to be higher (Mann-Whitney U, p = 0.009). The SUV values of the submandibular gland, muscle, liver, and blood pool were found to be lower in the group of patients with high serum LDH values. The cut-off SUVmax value was determined to be 6.945 (sensitivity 89.6%, specificity 98.1%) for primary prostate lesion; 4.72 for lymph node metastasis; 4.25 for bone metastasis. The serum PSA cut-off value to distinguish the negative/positive groups was found to be 1,505 (sensitivity 79.7%, specificity 77.3%). In conclusion, PSMA-617 demonstrates a similar biodistribution with other PSMA ligands. The physiological uptake of lymph nodes and bone which are mostly metastasized in prostate cancer, are not affected by the factors we examined. It should be kept in mind that the normal prostate tissue uptake may increase in patients receiving radiotherapy, and the physiological/pathological uptake of the organs may differ due to the changes in PSMA expression in patients receiving ADT, tumor burden, and kidney function may affect the biodistribution.

Prostate-specific membrane antigen (PSMA) is a well-known biomarker of prostate cancer. Previously, our group reported that the succinimidyl-cystatin-urea-glutamate (SCUE) moiety has a high affinity for PSMA. In this study, we developed the novel technetium-99m-labeled PSMA-targeting probe "[99mTc]Tc-(Ham-SCUE)2" based on a hydroxamamide chelate with a bivalent SCUE and evaluated its potential as a SPECT imaging probe for the diagnosis of PSMA-expressing prostate cancer. Ham-SCUE was synthesized by a one-step reaction with Ham-Mal and cysteine-urea-glutamine. Then, Ham-SCUE was reacted with [99mTc]NaTcO4 for 10min at room temperature to obtain [99mTc]Tc-(Ham-SCUE)2. [99mTc]Tc-(Ham-SCUE)2 was added to LNCaP (high PSMA expression) cells or PC3 (low PSMA expression) cells, and their radioactivity was measured 60min after administration. The blocking study was performed by co-incubation of LNCaP cells with various concentrations of 2-PMPA (a PSMA inhibitor) for 15min before adding [99mTc]Tc-(Ham-SCUE)2. The biodistribution of [99mTc]Tc-(Ham-SCUE)2 in LNCaP/PC3 dual xenografted C.B.-17/Icr scid/scid Jcl mice was evaluated for 120min after intravenous injection. The blocking study was performed by pretreatment of mice with 2-PMPA (10mg/kg weight). [99mTc]Tc-(Ham-SCUE)2 was acquired at radiochemical yields of 56% with a radiochemical purity of over 95%. The cellular uptake level of [99mTc]Tc-(Ham-SCUE)2 by LNCaP cells was significantly higher than that by PC3 cells (LNCaP: 11.12 ± 0.71 vs. PC3: 1.40 ± 0.13%uptake/mg protein, p < 0.01), and the uptake was significantly suppressed by pretreatment with 2-PMPA (2.56 ± 0.37%uptake/mg protein, p < 0.05). IC50 of 2-PMPA was 245 ± 47nM. In the in vivo study, the radioactivity of LNCaP tumor tissue was significantly higher than that of PC3 tumor tissue at 120min after the administration of [99mTc]Tc-(Ham-SCUE)2 (LNCaP: 9.97 ± 2.79, PC3: 1.16 ± 0.23%ID/g, p < 0.01), and was suppressed by pretreatment with 2-PMPA (2.50 ± 0.45%ID/g, p < 0.01). [99mTc]Tc-(Ham-SCUE)2 has the potential to be a SPECT imaging agent for diagnosing high PSMA-expressing prostate cancer.

The current study is intended to investigate the effect of new organ involvement on overall survival (OS) and modify the Response Evaluation Criteria in PSMA Imaging (RECIP) by including new organ involvement to RECIP 1.0. This retrospective study includes 114 patients diagnosed with metastatic castration-resistant prostate cancer (mCRPC) between September 2017 and June 2022 who had received docetaxel treatment and had baseline and post-treatment prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) images. The inclusion criteria were patients with pre- and post-treatment [18F]FDG PET/CT images and whose [18F]FDG PET images were negative. Those whose data were unavailable, who had additional malignancy, or who received abiraterone, enzalutamide, or Lutetium (Lu)-177 treatment were excluded. Age, Gleason score (GS), TPSA (total prostate-specific antigen) levels, surgical history, and OS information were recorded for each patient. The 114 patients herein had a median age of 72.5 (51-91) years and a median GS of 8 (7-10). New lesions were observed in 59 patients (51.7%) and new organ PSMA uptake was observed in 14 patients (12.2%). In the multivariate Cox regression analysis, volume-based treatment response (vTR)-total lesion PSMA (TLP), RECIP PSMA-VOL, modified RECIP (mRECIP) PSMA-VOL, and mRECIP TLP were independent prognostic factors for mortality (p < 0.001, p = 0.006, p = 0.003, and p = 0.003, respectively). The median OS of patients with new organ involvement and new lesion with PSMA uptake was 9.3months (95% CI 2.1-16.5months) and 11.8months (95% CI 7.4-16.2months), respectively. The study concluded that new organ involvement had a shorter OS than new lesion involvement. In the mRECIP that we developed, unlike RECIP, we demonstrated that both PSMA-VOL and TLP value were independent prognostic factors for mortality.

Cardiac positron emission tomography (PET) can visualize and quantify the molecular and physiological pathways of cardiac function. However, cardiac and respiratory motion can introduce blurring that reduces PET image quality and quantitative accuracy. Dual cardiac- and respiratory-gated PET reconstruction can mitigate motion artifacts but increases noise as only a subset of data are used for each time frame of the cardiac cycle. The objective of this study is to create a zero-shot image denoising framework using a conditional generative adversarial networks (cGANs) for improving image quality and quantitative accuracy in non-gated and dual-gated cardiac PET images. Our study included retrospective list-mode data from 40 patients who underwent an 18F-fluorodeoxyglucose (18F-FDG) cardiac PET study. We initially trained and evaluated a 3D cGAN-known as Pix2Pix-on simulated non-gated low-count PET data paired with corresponding full-count target data, and then deployed the model on an unseen test set acquired on the same PET/CT system including both non-gated and dual-gated PET data. Quantitative analysis demonstrated that the 3D Pix2Pix network architecture achieved significantly (p value<0.05) enhanced image quality and accuracy in both non-gated and gated cardiac PET images. At 5%, 10%, and 15% preserved count statistics, the model increased peak signal-to-noise ratio (PSNR) by 33.7%, 21.2%, and 15.5%, structural similarity index (SSIM) by 7.1%, 3.3%, and 2.2%, and reduced mean absolute error (MAE) by 61.4%, 54.3%, and 49.7%, respectively. When tested on dual-gated PET data, the model consistently reduced noise, irrespective of cardiac/respiratory motion phases, while maintaining image resolution and accuracy. Significant improvements were observed across all gates, including a 34.7% increase in PSNR, a 7.8% improvement in SSIM, and a 60.3% reduction in MAE. The findings of this study indicate that dual-gated cardiac PET images, which often have post-reconstruction artifacts potentially affecting diagnostic performance, can be effectively improved using a generative pre-trained denoising network.

The purpose of this study was to determine the value of sentinel lymph node biopsy (SLNB) in the laryngeal SCC, using intra-operative peri-tumoral injection of Tc-99m-phytate. Patients with biopsy-proven squamous cell carcinoma of the larynx were included. On the day of surgery, after anesthesia induction, suspension laryngoscopy was performed to inject 74MBq/0.4ml Tc-99m-phytate in four aliquots into the sub-mucosal peri-tumoral location. After a 10-min wait, a portable gamma probe was used to locate sentinel nodes. Subsequently, all patients underwent laryngectomy and neck dissection. Both sentinel nodes and non-sentinel nodes were examined using hematoxylin and eosin (H&E) staining. Twenty-six patients with a diagnosis of laryngeal carcinoma were included in the study. The SLN detection rate was 65.4%, with a 100% detection rate in the supraglottic region and a 52.6% detection rate for glottis/transglottic patients. Permanent pathology results showed lymph node involvement in four patients, but only one patient had a negative result in the SLNB, resulting in an overall false negative rate of 25%. The sensitivity of the SLN technique was 75% overall, 100% in the supraglottic region, and 67% in the glottis/transglottic region. The accuracy and feasibility of SLNB may be related to the location of the tumors in the larynx. For supraglottic tumors, the technique seems to be feasible with a low false negative rate. For glottis/transglottic tumors, both the detection rate and false negative rate seem to be suboptimal. Further studies are needed to validate our results.

To establish and validate novel predictive models for predicting bone metastasis (BM) in newly diagnosed prostate adenocarcinoma (PCa) via single-photon emission computed tomography radiomics. In a retrospective review of the clinical single-photon emission computed tomography (SPECT) database, 176 patients (training set: n = 140; validation set: n = 36) who underwent SPECT/CT imaging and were histologically confirmed to have newly diagnosed PCa from June 2016 to June 2022 were enrolled. Radiomic features were extracted from the region of interest (ROI) in a targeted lesion in each patient. Clinical features, including age, total prostate-specific antigen (t-PSA), and Gleason grades, were included. Statistical tests were then employed to eliminate irrelevant and redundant features. Finally, four types of optimized models were constructed for the prediction. Furthermore, fivefold cross-validation was applied to obtain sensitivity, specificity, accuracy, and area under the curve (AUC) for performance evaluation. The clinical usefulness of the multivariate models was estimated through decision curve analysis (DCA). A radiomics signature consisting of 27 selected features which were obtained by radiomics' LASSO treatment was significantly correlated with bone status (P < 0.01 for both training and validation sets). Collectively, the models showed good predictive efficiency. The AUC values ranged from 0.87 to 0.98 in four models. The AUC values of the human experts were 0.655 and 0.872 in the training and validation groups, respectively. Most radiomic models showed better diagnostic accuracy than human experts in the training and validation groups. DCA also demonstrated the superiority of the radiomics models compared to human experts. Radiomics models are superior to humans in differentiating between benign bone and prostate cancer bone metastases; it can be used to facilitate personalized prediction of BM in newly diagnosed PCa patients.

Information about developed positron emission tomography (PET) tracers and obtained clinical PET images is publicly available in a database. However, findings regarding the kinetic parameters of PET tracers are yet to be summarized. Therefore, in this study, we created an open-access database of central nervous system (CNS) kinetic parameters in the healthy human brain for existing PET tracers (DOCK-PET). Our database includes information on the kinetic parameters and compounds of existing CNS-PET tracers. The kinetic parameter dataset comprises the analysis methods, VT, BPND, K parameters, relevant literature, and study details. The list of PET tracers and kinetic parameter information was compiled through keyword-based searches of PubMed and the Molecular Imaging and Contrast Agent Database (MICAD). The kinetic parameters obtained, including VT, BPND, and K parameters, were reorganized based on the defined brain anatomical regions. All data were rigorously double-checked before being summarized in Microsoft Excel and JavaScript Object Notation (JSON) formats. Of the 247 PET tracers identified through searches using the PubMed and MICAD websites, the kinetic parameters of 120 PET tracers were available. Among the 120 PET tracers, compound structures with chemical and physical properties were obtained from the PubChem website or the ChemDraw software. Furthermore, the affinity information of the 104 PET tracers was gathered from PubChem or extensive literature surveys of the 120 PET tracers. We developed a comprehensive open-access database, DOCK-PET, that includes both kinetic parameters of healthy humans and compound information for existing CNS-PET tracers.

This study seeks to evaluate how recent COVID-19 infection affects myocardial perfusion and functional parameters derived from gated myocardial perfusion imaging in patients undergoing evaluation for coronary artery disease. The goal is to enhance our understanding of COVID-19's influence on the cardiovascular system. Conducted at Farshchian Heart Hospital from 2022 to 2023, this case-control study enrolled patients suspected of coronary artery disease, stratified into two groups: those with confirmed COVID-19 infection within the past 6months (study group) and those without prior COVID-19 infection (control group). Employing a 2-day protocol, stress testing and gated SPECT MPI were performed. Statistical analysis included descriptive statistics, Chi-square test, Student's t test, and Mann-Whitney U test. Among the 86 patients included, 43 were in each group. Significantly higher summed stress core and summed difference score values were observed in the study group compared to the control group (p < 0.05). In addition, the study group exhibited significantly altered global left ventricular ejection fraction, end-diastolic volume, and end-systolic volume (p < 0.05). Non-perfusion findings, including transient ischemic dilation and transient right ventricular visualization, were more prevalent in the study group. Recent COVID-19 infection is associated with impaired myocardial perfusion and altered functional parameters as detected by MPI. These findings underscore the intricate interplay between COVID-19 and cardiovascular health, emphasizing the importance of comprehensive evaluation and management strategies to address cardiac complications in affected individuals. Further research is warranted to elucidate the underlying mechanisms and optimize patient care in the context of COVID-19-associated cardiovascular manifestations.

Predicting the malignancy of pure ground-glass nodules (GGNs) using CT is challenging. The optimal role of [18F]FDG PET/CT in this context has not been clarified. We compared the performance of [18F]FDG PET/CT in evaluating GGNs for predicting invasive adenocarcinomas (IACs) with CT. From June 2012 to December 2020, we retrospectively enrolled patients with pure GGNs on CT who underwent [18F]FDG PET/CT within 90days. Overall, 38 patients with 40 ≥ 1-cm GGNs were pathologically confirmed. CT images were analyzed for size, attenuation, uniformity, shape, margin, tumor-lung interface, and internal/surrounding characteristics. Visual [18F]FDG positivity, maximum standardized uptake value (SUVmax), and tissue fraction-corrected SUVmax (SUVmaxTF) were evaluated on PET/CT. The histopathology of the 40 GGNs were: 25 IACs (62.5%), 9 minimally invasive adenocarcinomas (MIA, 22.5%), and 6 adenocarcinomas in situ (AIS, 15.0%). No significant differences were found in CT findings according to histopathology, whereas visual [18F]FDG positivity, SUVmax, and SUVmaxTF were significantly different (P=0.001, 0.033, and 0.018, respectively). The size, visual [18F]FDG positivity, SUVmax, and SUVmaxTF showed significant diagnostic performance to predict IACs (area under the curve=0.693, 0.773, 0.717, and 0.723, respectively; P=0.029, 0.001, 0.018, and 0.013, respectively). In the multivariate logistic regression analysis, visual [18F]FDG positivity discriminated IACs among GGNs among various CT and PET findings (P=0.008). [18F]FDG PET/CT demonstrated superior diagnostic performance compared to CT in differentiating IAC from AIS/MIA among pure GGNs, thus it has the potential to guide the proper management of patients with pure GGNs.