Search Results (575)

Objective: We evaluated the feasibility of a machine-learning (ML) model based on clinical features and radiomics from [¹⁸F]FDG PET/CT images to differentiate between infected and non-infected intracavitary vascular grafts and endografts (iVGEI). Methods: Three ML models were developed: one based on pre-treatment criteria to diagnose a vascular graft infection (“MAGIC-light features”), another using radiomics features from diagnostic [¹⁸F]FDG-PET scans, and a third combining both datasets. The training set included 92 patients (72 iVGEI-positive, 20 iVGEI-negative), and the external test set included 20 iVGEI-positive and 12 iVGEI-negative patients. The abdominal aorta and iliac arteries in the PET/CT scans were automatically segmented using SEQUOIA and TotalSegmentator and manually adjusted, extracting 96 radiomics features. The best-performing models for the MAGIC-light features and PET-radiomics features were selected from 343 unique models. Most relevant features were combined to test three final models using ROC analysis, accuracy, sensitivity, and specificity. Results: The combined model achieved the highest AUC in the test set (mean ± SD: 0.91 ± 0.02) compared with the MAGIC-light-only model (0.85 ± 0.06) and the PET-radiomics model (0.73 ± 0.03). The combined model also achieved a higher accuracy (0.91 vs. 0.82) than the diagnosis based on all the MAGIC criteria and a comparable sensitivity and specificity (0.70 and 1.00 vs. 0.76 and 0.92, respectively) while providing diagnostic information at the initial presentation. The AUC for the combined model was significantly higher than the PET-radiomics model (p = 0.02 in the bootstrap test), while other comparisons were not statistically significant. Conclusions: This study demonstrated the potential of ML models in supporting diagnostic decision making for iVGEI. A combined model using pre-treatment clinical features and PET-radiomics features showed high diagnostic performance and specificity, potentially reducing overtreatment and enhancing patient outcomes. Full article

Background/Objectives: ¹⁸F-PSMA-1007 is one of the more widely used radioligands in prostate cancer imaging with PET/CT. Its major advantage lies in the low urinary tracer activity due to primarily hepatobiliary clearance, but unexpectedly high tracer accumulation in the bladder can occur, potentially hindering assessment of lesions near the prostate bed. This study assesses the impact of furosemide on ¹⁸F-PSMA-1007 tracer accumulation in the bladder. Methods: In this single-center, retrospective, intra-individual comparative analysis, 18 patients undergoing two consecutive ¹⁸F-PSMA-1007 PET/CT scans for biochemical relapse (BCR) or persistence (BCP)—one with and one without prior furosemide administration—were included. Images were acquired 60 min post-injection of 250 MBq of tracer activity. Standardized Uptake Values (SUVmax, SUVpeak, SUVmean) were measured in the bladder and in tissues with physiological uptake by three readers. Differences were analyzed using Wilcoxon signed-rank tests. The inter-reader agreement was assessed using intraclass correlation coefficient. Results: Furosemide significantly decreased bladder SUVmax, SUVpeak, and SUVmean (all p < 0.001). Mean bladder SUVmax decreased from 13.20 ± 10.40 to 3.92 ± 3.47, SUVpeak from 10.94 ± 8.02 to 3.47 ± 3.13, and SUVmean from 8.74 ± 6.66 to 2.81 ± 2.56, representing a large effect size (r ≈ 0.55). Physiological tracer uptake in most organs was not significantly influenced by furosemide (all p > 0.05). Conclusions: Despite the predominantly hepatobiliary clearance of ¹⁸F-PSMA-1007, furosemide-induced forced diuresis leads to a significant reduction in tracer activity in the bladder, which in clinical practice could help in early detection of tumor recurrence. Full article

Background/Objectives: Gastrin-releasing peptide receptor (GRPR) is overexpressed in breast cancer and might be used as a theranostics target. The expression of GRPR strongly correlates with estrogen receptor (ER) expression. Visualization of GRPR-expressing breast tumors might help to select the optimal treatment. Developing GRPR-specific probes for SPECT would permit imaging-guided therapy in regions with restricted access to PET facilities. In this first-in-human study, we evaluated the safety, biodistribution, and dosimetry of the [^99mTc]Tc-DB8 GRPR-antagonistic peptide. We also addressed the important issue of finding the optimal injected peptide mass. Methods: Fifteen female patients with ER-positive primary breast cancer were enrolled and divided into three cohorts receiving [^99mTc]Tc-DB8 (corresponding to three distinct doses of 40, 80, or 120 µg DB8) comprising five patients each. Additionally, four patients with ER-negative primary tumors were injected with 80 µg [^99mTc]Tc-DB8. The injected activity was 360 ± 70 MBq. Planar scintigraphy was performed after 2, 4, 6, and 24 h, and SPECT/CT scans followed planar imaging 2, 4, and 6 h after injection. Results: No adverse events were associated with [^99mTc]Tc-DB8 injections. The effective dose was 0.009–0.014 mSv/MBq. Primary tumors and all known lymph node metastases were visualized irrespective of injected peptide mass. The highest uptake in the ER-positive tumors was 2 h after injection of [^99mTc]Tc-DB8 at a 80 µg DB8 dose (SUV_max 5.3 ± 1.2). Injection of [^99mTc]Tc-DB8 with 80 µg DB8 provided significantly (p < 0.01) higher uptake in primary ER-positive breast cancer lesions than injection with 40 µg DB8 (SUV_max 2.0 ± 0.3) or 120 µg (SUV_max 3.2 ± 1.4). Tumor-to-contralateral breast ratio after injection of 80 μg was also significantly (p < 0.01, ANOVA test) higher than ratios after injection of other peptide masses. The uptake in ER-negative lesions was significantly lower (SUV_max 2.0 ± 0.3) than in ER-positive tumors. Conclusions: Imaging using [^99mTc]Tc-DB8 is safe, tolerable, and associated with low absorbed doses. The tumor uptake is dependent on the injected peptide mass. The injection of an optimal mass (80 µg) provides the highest uptake in ER-positive tumors. At optimal dosing, the uptake was significantly higher in ER-positive than in ER-negative lesions. Full article

Background: The accurate prediction of pathological complete response (pCR) following total neoadjuvant therapy (TNT) is crucial for optimising treatment protocols in locally advanced rectal cancer (LARC). Although conventional imaging techniques such as MRI show limitations in assessing treatment response, metabolic imaging utilising 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET-CT) provides distinctive information by quantifying tumour glycolytic activity. This study investigates the predictive value of sequential 18F-FDG PET-CT parameters, focusing on Total Lesion Glycolysis (TLG), in predicting pCR after TNT. Methods: We conducted a retrospective analysis of 33 LARC patients (T3–4/N0–1) treated with TNT (neoadjuvant-chemoradiation followed by consolidation FOLFOX chemotherapy). Sequential PET-CT scans were performed at baseline, interim (after 4 cycles of FOLFOX), and post-TNT. Metabolic parameters, including maximum standardised uptake value (SUVmax) and TLG, were measured. Receiver operating characteristic (ROC) analysis assessed the predictive performance of these parameters for pCR. Results: The pCR rate was 21.2% (7/33). Post-TNT TLG ≤ 10 demonstrated excellent predictive accuracy for pCR (AUC 0.887, 92.3% sensitivity, 85.7% specificity, and 96.0% PPV), outperforming SUVmax (AUC 0.843). Interim TLG ≤ 10 also showed a strong predictive value (AUC 0.824, 100% sensitivity, and 71.4% specificity). Conclusions: TLG may serve as a reliable metabolic biomarker for predicting pathologic complete response (pCR) after total neoadjuvant therapy (TNT) in locally advanced rectal cancer (LARC). Its inclusion in clinical decision-making could improve patient selection for organ preservation strategies, thereby reducing the need for unnecessary surgeries in the future. However, given that the study is based on a small retrospective design, the findings should be interpreted with caution and used alongside other decision-making tools until more comprehensive data are collected from larger studies. Full article

Background: This Phase 2 trial evaluated the efficacy, tolerability, and safety of [¹⁷⁷Lu]Lu-PSMA-617 (¹⁷⁷Lu-PSMA-617) in patients with ≥1 measurable lesion and progressive prostate-specific membrane antigen-positive (PSMA+) metastatic castration-resistant prostate cancer (mCRPC) in Japan. Methods: This study comprises four parts; data from three parts are presented here. Part 1 evaluated safety and tolerability; Parts 2 (post-taxane) and 3 (pre-taxane/taxane-naive) assessed the overall response rate (ORR; primary endpoint), overall survival (OS), radiographic progression-free survival (rPFS), disease control rate (DCR), PFS, and safety; and Part 4 is the expansion part. Patients received 7.4 GBq (±10%) ¹⁷⁷Lu-PSMA-617 Q6W for up to six cycles. Results: Of the 35 patients who underwent a [⁶⁸Ga]Ga-PSMA-11 (⁶⁸Ga-PSMA-11) PET/CT scan, 30 received ¹⁷⁷Lu-PSMA-617 (post-taxane, n = 12; pre-taxane, n = 18). No dose-limiting toxicity was noted in Part 1 (n = 3). Post- and pre-taxane patients had a median of three and five cycles, respectively. The primary endpoint, ORR, met the pre-specified threshold, with the lower limit of the 90% confidence interval (CI) above the threshold of 5% for post-taxane and 12% for pre-taxane. Post- and pre-taxane patients had an ORR of 25.0% (90% CI: 7.2–52.7) and 33.3% (90% CI: 15.6–55.4), respectively. In post- and pre-taxane patients, the DCR was 91.7% and 83.3%, the median rPFS was 3.71 and 12.25 months, and the median PFS was 3.71 and 5.59 months, respectively. The median OS was 14.42 and 12.94 months in post- and pre-taxane patients, respectively. The most common adverse events were constipation, decreased appetite, decreased platelet count, anemia, and nausea. Conclusions: The primary endpoint (ORR) was met. The safety profile of ¹⁷⁷Lu-PSMA-617 was consistent with the VISION and PSMAfore studies, with no new safety signals in the Japanese patients with mCRPC. Full article

Background/Objectives: Red bone marrow irradiation is a major concern for patients with advanced prostate cancer undergoing [¹⁷⁷Lu]Lu-PSMA therapy. However, low uptake in the red bone marrow and the presence of bone lesions complicate image-based red bone marrow dosimetry. This study aimed to investigate the general feasibility of image-based red bone marrow activity estimation for [¹⁷⁷Lu]Lu-PSMA treatment and to develop a fully automated workflow for clinical implementation. Methods: In the first part of the study, 175 virtual patient phantoms with realistic ¹⁷⁷Lu activity distributions were generated based on 639 pre-therapeutic [¹⁸F]F-PSMA-1007 PET/CT scans. The SIMIND Monte Carlo tool was used to simulate the ¹⁷⁷Lu SPECT acquisitions (24 h post-injection (p.i.)), which were used to assess the uncertainty of red bone marrow activity estimation. In the second part, red bone marrow self- and cross-absorbed doses were estimated for four therapy cycles of 20 patients. Results: The simulation study shows a significant overestimation of activity in skeletal sites with bone lesions, with median recovery coefficients (RCs) across all phantoms yielding a median of 225% (range: 106–1015%). In contrast, the median RCs were markedly lower in skeletal sites neighboring or distant to lesion-carrying sites (105% [72–163%] and 107% [77–130%], respectively). The median total absorbed dose to the red bone marrow was 20.8 mGy/GBq (range: 5.6–297.9 mGy/GBq). Median blood levels decreased with an increasing median cumulative total absorbed dose. Conclusions: Reliable estimation of activity concentration in skeletal sites without bone lesion infiltration has been shown to be feasible. Based on this finding, an automated workflow for routine image-based red bone marrow dosimetry was developed. Full article

This study assesses the clinical deployment of SubtlePET™, a commercial AI-based denoising algorithm, across three radiotracers—¹⁸F-FDG, ⁶⁸Ga-PSMA-11, and ¹⁸F-FDOPA—with the goal of improving image quality while reducing injected activity, technologist radiation exposure, and scan time. A retrospective analysis on a digital PET/CT system showed that SubtlePET™ enabled dose reductions exceeding 33% and time savings of over 25%. AI-enhanced images were rated interpretable in 100% of cases versus 65% for standard low-dose reconstructions. Notably, 85% of AI-enhanced scans received the maximum Likert quality score (5/5), indicating excellent diagnostic confidence and noise suppression, compared to only 50% with conventional reconstruction. The quantitative image quality improved significantly across all tracers, with SNR and CNR gains of 50–70%. Radiotracer dose reductions were particularly substantial in low-BMI patients (up to 41% for FDG), and the technologist exposure decreased for high-exposure roles. The daily patient throughput increased by an average of 4.84 cases. These findings support the robust integration of SubtlePET™ into routine clinical PET practice, offering improved efficiency, safety, and image quality without compromising lesion detectability. Full article

Background: The recent introduction of whole-body positron emission tomography/ computed tomography (PET/CT) scanners and multi-bed, multi-time point acquisition technique enable calculating fluorodeoxyglucose (FDG) kinetics in the whole body. However, validating parametric, Patlak-derived data is difficult on phantoms. Methods: This prospective study investigated the effect of quantification methods mean, max, and peak on the metabolic rate (MR-FDG) and distribution volume (DV-FDG) quantification, as well as the diagnostic accuracy of parametric Patlak FDG-PET scans in diagnosing lung lesions and lymph node metastases, using histopathology and follow-up as reference standards. Dynamic whole-body FDG PET was acquired for 80 minutes in 34 patients with indeterminate lung lesions and kinetic parameters extracted from lung lesions and representative mediastinal and hilar lymph nodes. Results: All quantification methods—mean, max, and peak—demonstrated high diagnostic accuracy (AUC: MR-FDG: 0.987–0.991 and 0.893–0.905; DV-FDG: 0.948–0.975 and 0.812–0.825) for differentiating benign from malignant lymph nodes and lung lesions. Differences in the magnitude of MR-FDG (−4.76–14.09) and DV-FDG (−10.64–46.10%) were substantial across methods. Variability was more pronounced in lymph nodes (MR-FDG: 1.37–3.48) than in lung lesions (MR-FDG: 3.31–5.04). The variability was lowest between mean and max quantification, with percentage differences of 40.87 ± 5.69% for MR-FDG and 39.26 ± 7.68% for DV-FDG. Conclusions: The choice of method to measure MR-FDG and DV-FDG greatly influences the results, especially in smaller lesions with large and systematic differences. For lung lesions, a conversion factor between mean and max methods of 40% provides acceptable agreement, facilitating retrospective comparisons of measurements, e.g., in meta-analyses. Full article

Background: Adrenal glands are situated cranially and in close proximity to both kidneys. The rabbit is a preferred animal pet species and is also used as an experimental model in research. The aim of this study was to investigate the CT anatomical features of the rabbit adrenal glands, using the CT device SOMATOM. Methods: Ten sexually mature clinically healthy rabbits, with body weights from 2.5 to 3.0 kg were used. They were separated into two groups—five males and five females. CT algorithm: Transverse, sagittal, and dorsal CT studies were performed. The animals were positioned in supine recumbency. They were anesthetized with 15 mg/kg Zoletil^® 50. Helical CT was carried out. The body was scanned from the intrathoracic part of the abdominal cavity to the pelvic inlet. CCD, DVD, and MLD dimensions were measured. Results: Transverse CT scans at the Th12 and L1 level visualized the topography of the right and left adrenal glands. Sagittal CT scans of Regio abdominis, 10 mm to the right and to the left of the median plane, showed the right and left adrenal glands as findings with intermediate attenuation. The dorsal CT investigation of Regio abdominis 30 mm and 45 mm ventral to the spine demonstrated both glands in the vicinity of abdominal organs and large blood vessels. CCD of the right adrenal gland was 6.9 ± 0.5 mm, DVD of the same gland was 5.7 ± 0.7 mm, and MLD was—3.9 ± 0.3 mm. CCD of the left adrenal gland was 5.4 ± 0.6 mm, DVD was—4.0 ± 1.1 mm, and MLD was—4.1 ± 0.9 mm. Conclusions: CCD and DVD of the right adrenal gland were greater than the same parameters of the left gland. MLD of the right adrenal gland was lower than the same parameter measured for the left one. Full article

Background: Interdigitating dendritic cell sarcoma (IDCS) is a very rare haematologic malignant tumour that arises from antigen-presenting cells. While it primarily affects the lymph nodes, extranodal manifestations have been observed, and there is a slight male predominance. Due to its rarity, diagnosing IDCS can be challenging, as illustrated in our case report of a 61-year-old woman. Methods: In this case presentation, the oncological management of a patient suspected of having malignant melanoma metastasis in the neck lymph nodes is discussed. This includes otorhinolaryngological examinations, fine needle aspiration biopsy, PET CT imaging, and histological analysis with immunohistochemistry. Results: The patient’s medical history included the excision of a pigmented lesion from the left ala of her nose, which was diagnosed as malignant melanoma. After surgical treatment, she experienced a tumour-free period of one year; however, during a follow-up ultrasonography three pathological lymph nodes were detected on the left side of her neck. Initially, a nodal metastasis of melanoma was suspected. Yet, fine needle aspiration cytology revealed myofibroblastic tumour invasion, and a re-biopsy showed no signs of malignancy. To further investigate, PET-CT scans were conducted, and a modified radical neck dissection was performed based on the findings. The histological analysis of the lymph nodes revealed an IDCS, a second independent tumour distinct from the initially diagnosed malignant melanoma, originating from the submandibular, upper jugular, and mid-jugular lymph nodes. Conclusions: This case highlights the diagnostic difficulties associated with IDCS. Initially, the clinical suspicion of malignant melanoma was considered, necessitating further examinations and a multidisciplinary approach to reach a final diagnosis and provide the patient with appropriate treatment. Full article

Primary hyperparathyroidism is commonly caused by parathyroid adenomas, hyperplasia, or, rarely, carcinoma. In up to 20% of cases, parathyroid tissue may be ectopic, often located in the mediastinum due to aberrant embryologic migration. Ectopic parathyroid glands pose a diagnostic and therapeutic challenge, and an accurate preoperative localization is essential for an effective and safe resection. Imaging modalities such as CT scan, TC-sestamibi scintigraphy, PET/CT, ultrasonography and MRI are routinely employed, whereas combined techniques offer improved diagnostic accuracy. Emerging approaches, however, including PET/CT with choline tracers, have shown promise in enhancing sensitivity in complex or recurrent cases. When ectopic glands are in the mediastinum, thoracic surgical intervention is required. Traditional open approaches, such as sternotomy or thoracotomy, are associated with significant morbidity. The development and evolution of minimally invasive surgery (MIS) has become the preferred approach in selected cases. When MIS is performed, intraoperative assessment and parathyroid identification are crucial to ensure complete gland removal. Intraoperative parathyroid hormone (ioPTH) monitoring provides real-time confirmation of surgical success. The integration of advanced imaging, intraoperative monitoring, and minimally invasive techniques significantly improves surgical outcomes while minimizing complications and accelerating patient recovery. Ultimately, the effective treatment of ectopic parathyroid glands relies on a personalized approach, adapting both diagnostic and surgical strategies to the unique anatomical and clinical context of each patient. Integration of advanced imaging, intraoperative monitoring, and minimally invasive techniques, combined with a multidisciplinary team involving endocrinologists, radiologists, and thoracic surgeons, is key to optimizing outcomes and reducing patient morbidity. Full article

Objectives: This study aimed to evaluate the consistency of Centiloid (CL) values calculated using three commercially available software platforms: BTXBrain (v1.1.2), MIM (v7.3.7), and SCALE PET (v2.0.1). Methods: A total of 239 patients who underwent amyloid PET/CT with either F-18 flutemetamol (FMM) or F-18 florbetaben (FBB) were retrospectively analyzed. CL values were calculated using BTXBrain, MIM, and SCALE PET. Linear regression, Passing–Bablok regression, and Bland–Altman analysis were performed to assess the agreement between CL values. Subgroup analyses were conducted for each radiotracer. CL values were compared according to visual interpretation status. Results: Strong correlations were observed between CL values derived from the three software platforms (R² > 0.95). However, Passing–Bablok regression revealed significant proportional bias, with CL values from BTXBrain being lower than others, and CL values from SCALE PET being higher than others as CL values increased. Bland–Altman plots visualized the proportional bias, particularly between BTXBrain and SCALE PET. Subgroup analyses by radiotracer showed similar results. CL values in visually positive scans were significantly higher than those in visually negative scans across all platforms. Conclusions: The three commercial software programs demonstrated high consistency in CL quantification. However, a notable systematic bias was observed. Further evaluation of various scanner effects and CL calculation methods is warranted to improve the consistency and reproducibility of CL quantification in clinical practice. Full article

Background/Objectives: In many cases, the detection of a single lesion could revolutionise patient clinical management; not all localisations, especially those with a low uptake and, consequently, a low Tumour-to-Background Ratio (TBR), are readily detectable using [¹⁸F]F-FDG PET/CT. LAFOV-PET offers a potential enhancement in lesion detection, but the proportion of patients who would benefit from its use has yet to be determined. With the present analysis, we aimed to assess which clinical contexts the enhancement in lesion detection could affect the most. Methods: This retrospective study included 764 patients who underwent [¹⁸F]F-FDG PET/CT between January and April 2024. Data were obtained through a review of PET/CT reports. Inclusion criteria comprised patients who attended our centre for cancer pathologies or masses of undetermined nature (MUNs) in a staging setting, excluding patients who had undergone a prior [¹⁸F]F-FDG PET/CT scan or who had received therapy for any cancer pathology. This analysis focused on the total number of lesions identified, as well as the SUVmax of the lesion with the highest uptake. We analysed the proportion of patients who were within the range of number of lesions between 1 and 2, as well as who had an SUVmax of the lesion with the highest uptake between 2 and 5, either in the whole patient population or in the pathologies with a larger numerosity in the present study. Results: Among the 862 scans analysed, 289 (34%) were found to be negative, while 573 (66%) presented at least one localisation. In total, 4.5% of patients presented both a lesion number of between 1 and 2 and an SUVmax of the lesion with the highest uptake between 2 and 5. Among the malignancies that were the most common in the analysed population, a higher-than-average proportion of patients meeting these criteria were found in melanoma (6.2%), breast cancer (5.9%), and multiple myeloma (4.8%) patients. Conversely, the conditions that presented a lower proportion of patients in this range were suffering from MUNs (4.0%), lung cancer (2.1%), head–neck cancer (2.1%), suspected lymphoma (2.0%), and colon cancer (0.0%). Conclusions: Our analysis shows that almost 1 in 20 patients evaluated at oncological staging with [¹⁸F]F-FDG PET/CT could benefit from the increased diagnostic sensitivity offered by LAFOV-PET scanners. These data, although preliminary, support the need for future prospective controlled studies to confirm the actual clinical impact of implementing LAFOV-PET in current practice. Full article

In this article, we present a case of a 49-year-old woman presenting with a recurrent metastatic neuroendocrine tumor. Background: Insulinomas are neuroendocrine tumors derived from beta cells of the pancreas that secrete insulin. Usually, they are benign tumors; however, metastatic insulinomas are an extremely rare malignant form of these tumors, carrying a significantly worse prognosis. Case Presentation: A 49-year-old woman, a patient in the University Hospital in Wroclaw in the Department of Endocrinology, Diabetes and Isotope Therapy, first presented with abdominal pain in 2009, when ultrasound and further examination led to the diagnosis of a tumor in the pancreas (a solid pseudopapillary tumor of the pancreas—meta NET G2), and the patient underwent distal pancreatectomy with splenectomy. For ten years, she was under observation, and her symptoms, such as abdominal pain, nausea, weight loss, and general weakness, reappeared in 2019. Then, magnetic resonance imaging (MRI) showed a lesion in the liver, and further histopathology revealed neuroendocrine tumor (NET) metastasis to the liver. In 2022, the patient presented with loss of consciousness and convulsion, loss of weight, and hypoglycemia after meals. In April 2022, the daily glycemic profile was recorded and a 72 h fasting test was performed; however, their results excluded insulinoma. Positron emission tomography–computed tomography (PET-CT) with 18F-fluorodeoxyglucose (18F-FDG) and PET with gallium-68-DOTA-(Tyr3)-octreotate (68Ga-DOTA-TATE) showed a metastatic proliferative process in the liver. Persistent hypoglycemia led to another hospitalization in May 2022, and repeated tests allowed for the diagnosis of insulinoma. Treatment with somatostatin analogs and diazoxide was started. A CT scan in November 2022 and a PET scan in January 2023 showed new metastases to the liver, bones, and cervical lymph nodes, and it was decided to intensify the treatment. In May 2023, the patient was qualified for Lutathera treatment for insulinoma at the University Clinical Hospital in Poznań. In June 2023, another disturbing symptom was reported by the patient, a painful lump in the breast. During diagnostics, metastases with high proliferation markers were found in both breasts. Two months later, in August 2023, the patient received another dose of Lutathera. In October 2023, significant progression of liver lesions, metastases to bones of the spine, ribs, and pelvis, and periaortic and pelvic lymphadenopathy were found as well as elevated values of neuron-specific enolase and calcitonin. The patient was also referred to the Palliative Medicine Home Hospice. In consultation with the Lower Silesian Cancer Center, the decision was made to forgo further treatment with PRRT and initiate systemic chemotherapy. Despite the chosen treatment, the patient died on 27/DEC/2023. Conclusions: This case report can serve clinicians, as it presents a case of an extremely rare and insidious tumor, metastatic insulinoma. Full article

Background/Objectives: Attenuation correction (AC) is essential for achieving quantitatively accurate PET imaging. In ⁶⁸Ga-PSMA PET, however, artifacts such as respiratory motion, halo effects, and truncation errors in CT-based AC (CT-AC) images compromise image quality and impair model training for deep learning-based AC. This study proposes a novel artifact-refinement framework that filters out corrupted PET-CT images to create a clean dataset for training an image-domain AC model, eliminating the need for anatomical reference scans. Methods: A residual neural network (ResNet) was trained using paired PET non-AC and PET CT-AC images from a dataset of 828 whole-body ⁶⁸Ga-PSMA PET-CT scans. An initial model was trained using all data and employed to identify artifact-affected samples via voxel-level error metrics. These outliers were excluded, and the refined dataset was used to retrain the model with an L2 loss function. Performance was evaluated using metrics including mean error (ME), mean absolute error (MAE), relative error (RE%), RMSE, and SSIM on both internal and external test datasets. Results: The model trained with the artifact-free dataset demonstrated significantly improved performance: ME = −0.009 ± 0.43 SUV, MAE = 0.09 ± 0.41 SUV, and SSIM = 0.96 ± 0.03. Compared to the model trained on unfiltered data, the purified data model showed enhanced quantitative accuracy and robustness in external validation. Conclusions: The proposed data purification framework significantly enhances the performance of deep learning-based AC for ⁶⁸Ga-PSMA PET by mitigating artifact-induced errors. This approach facilitates reliable PET imaging in the absence of anatomical references, advancing clinical applicability and image fidelity. Full article