Search Results (274)

Background: Traumatic head injury (THI) includes a diverse range of hemorrhagic brain lesions (HBL), which are distinct phenotypes with characteristic pathophysiological mechanisms. Computed tomography (CT) is the cornerstone of the initial assessment and diagnosis; however, its sensitivity is limited, especially in mild head injury. Blood-derived biomarkers, including Neuron-Specific Enolase (NSE) and S-100B, have been extensively studied; however, their efficacy in distinguishing HBL subtypes remains unclear. We evaluated whether circulating serum levels of S-100B and NSE can discriminate between distinct intracranial HBLs and extracranial hemorrhagic lesions (ECH). Methods: This is an interim analysis of a prospective, randomized, double-blind clinical trial including 434 adult patients with blunt THI. HBL phenotypes identified by CT scan included subarachnoid hemorrhage (SAH), subdural hematoma (SDH), epidural hematoma (EDH), and brain contusion (BC). Unique lesions were considered while overlapping lesions were excluded. Subgaleal hematoma (SGH) was included as an example of ECH. Serum S-100B was assessed within 6 h post-injury, while serum NSE was evaluated at admission, 24 h, and 48 h thereafter. Serum NSE and inflammatory cytokines were quantified in duplicates using a Human Magnetic Luminex 5-plex assay, while serum S-100B concentrations were measured separately. Serum epinephrine concentrations were quantified using an ELISA. Biomarker profiles were analyzed based on lesion phenotype, lesion multiplicity, injury pattern, and clinical outcomes, including hospital length of stay (HLOS) and the Glasgow Outcome Scale—Extended (GOSE). Results: Admission median S-100B levels were higher in patients with SAH (495 pg/mL) and lower in those with SGH (191 pg/mL); however, they did not show statistically significant difference among HBL phenotypes. They were significantly higher in patients with polytrauma TBI (420 pg/mL) compared to isolated TBI (258 pg/mL). Baseline and 48 h NSE concentrations were significantly higher in SDH (25,089 and 28,438 pg/mL) than in other THI lesions (p = 0.04). There were no statistically significant changes in NSE values over time across all THI lesions except for SDH in which they raised more after 48 h (p = 0.02). They had a significant drop in polytrauma over the time (p = 0.001). Compared to intracranial lesions, S-100 B levels were significantly lower in SGH and in skull fractures without intracranial hematomas. Both S-100B and NSE levels were elevated in individuals with unfavorable GOSE scores. Conclusions: In this secondary exploratory analysis, elevated serum NSE and S-100B levels discriminate between extra- and intracranial lesions and appear to represent distinct but complementary aspects of THI, indicating neuronal damage and its temporal evolution, and predicting clinical and functional outcomes. The present findings reflect association and not causation. Future studies incorporating larger or multicenter cohorts, volumetric imaging, and long-term outcomes are required to validate and refine biomarker-guided algorithms for personalized THI care. Full article

Background: The generation of synthetic CT images from MRI scans represents a crucial step toward enabling MRI-only clinical workflows and supporting multi-modal integration in medical imaging, particularly in radiotherapy planning. Despite significant advancements in deep learning models, many current methods still struggle to reconstruct high-density structures, especially bone, and exhibit limited accuracy in density values. This shortcoming is largely attributed to the passage of excessive or noisy features through skip connections in the traditional U-Net architecture, which degrade the quality of information transmitted to the decoder, negatively impacting the clarity of anatomical boundaries and the pixel-wise accuracy of the resulting synthetic image. Methods: In this work, we propose an enhanced 3D U-Net architecture in which the Convolutional Block Attention Module (CBAM) is systematically integrated within each skip connection. The CBAM sequentially applies channel and spatial attention to adaptively reweight encoder feature maps before fusion with the decoder, thereby emphasizing anatomically relevant structures while suppressing irrelevant feature propagation. The model was trained and evaluated on the SynthRAD2023 (Task 1—Brain) MRI–CT dataset. To rigorously assess the contribution of the attention mechanism, a dedicated ablation study was conducted comparing three variants: 3D U-Net with Squeeze-and-Excitation (SE), Coordinate Attention (CA), and the proposed CBAM module. Performance was evaluated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Normalized Cross-Correlation (NCC). Results: The ablation study demonstrated that the CBAM-enhanced model consistently outperformed both SE- and CA-based variants across all quantitative metrics. Specifically, the proposed method achieved an MAE of $38.2\pm 5.4$ HU and an RMSE of $51.0\pm 12.0$ HU, representing the lowest reconstruction errors among the evaluated models. In addition, it obtained a PSNR of $29.45\pm 2.10$ dB, SSIM of $0.940\pm 0.031$, and NCC of $0.967\pm 0.015$, indicating superior structural preservation and strong voxel-wise correspondence between synthesized and reference CT volumes. These results confirm that the sequential integration of channel and spatial attention provides a statistically and practically meaningful improvement for high-fidelity MRI-to-CT synthesis. Conclusions: Generating high-resolution brain CT images from brain MRI scans using a 3D U-Net network enhanced with a CBAM module can contribute to supporting the clinical workflow by providing additional diagnostic data without the need for extra radiological examinations, thereby enhancing diagnostic efficiency and reducing radiation exposure. This technique helps reduce patient exposure to radiation and improves accessibility in resource-limited settings. Furthermore, this method is valuable for retrospective studies, surgical planning, and image-guided therapy, where complete multi-modal data may not always be available. Full article

Mild traumatic brain injury (mTBI) in adults is extremely common worldwide, but only a small fraction of these patients harbor clinically significant intracranial injuries. Computed tomography (CT) of the head is the standard diagnostic tool to detect traumatic brain hemorrhages or lesions, yet indiscriminate CT scanning of all mTBI patients is inefficient, costly, and exposes patients to ionizing radiation. To optimize patient care, numerous clinical decision rules and guidelines have been developed internationally to identify which adult patients with mTBI should undergo head CT. This review provides a global perspective on the indications for head CT in adult mTBI, comparing key decision rules including the Canadian CT Head Rule, New Orleans Criteria, UK NICE Head Injury Guidelines, and others. Methods: We conducted a comprehensive analysis of major international guidelines and decision rules for head CT in adult mTBI, focusing on their inclusion criteria, risk factors, and diagnostic performance. Results: All the examined rules prioritize near-100% sensitivity for identifying patients who need neurosurgical intervention, but they differ greatly in specificity and recommended CT utilization rates. North American rules such as the New Orleans Criteria tend to favor higher sensitivity, scanning almost all patients with any symptom, whereas the Canadian CT Head Rule and certain European guidelines (NICE, Scandinavian) are more selective, significantly reducing CT usage while maintaining safety. Discussion: We discuss how these variations reflect different healthcare settings and risk tolerances, and we examine the implications for neurosurgical practice. We also highlight challenges in guideline implementation, the impact on global CT utilization, and emerging approaches (such as biomarker-assisted triage) that may further refine decision-making. In conclusion, appropriate use of clinical decision rules for head CT in mTBI can safely minimize unnecessary imaging, but local adaptation and clinician judgment remain crucial to ensure that no significant injuries are missed while avoiding over-scanning. Full article

Background and objectives: Early biomarkers that can reliably predict treatment outcomes during CDK4/6 inhibitor therapy remain an unmet clinical need in patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2−) metastatic breast cancer (MBC). Metabolic changes on ^18F-FDG PET/CT may precede radiologic response and provide insight into tumor biology and early treatment resistance. Methods: This two-center retrospective study included 203 patients with HR+/HER2− MBC who received first-line CDK4/6 inhibitors (ribociclib or palbociclib) plus endocrine therapy between 2018 and 2024. Baseline and interim ^18F-FDG PET/CT scans performed after 2–4 cycles were evaluated. Early metabolic response was defined as a ≥30% reduction in SUVmax on the most metabolically active lesion, consistent with PERCIST 1.0. Progression-free survival (PFS) and overall survival (OS) were analyzed using Kaplan–Meier and multivariable Cox models. ROC analysis assessed the discriminative performance of ΔSUVmax for predicting disease progression. Results: Among 203 patients, 153 (75.4%) achieved a ≥30% SUVmax reduction. Responders had significantly longer PFS (median 44.4 vs. 4.8 months; p < 0.001) and OS (median not reached vs. 32.0 months; p < 0.001). Metabolic response remained independently associated with improved PFS (HR 0.24; 95% CI 0.15–0.37; p < 0.001) and OS (HR 0.37; 95% CI 0.20–0.67; p = 0.001) after adjustment for tumor grade, endocrine resistance, and visceral disease involvement. Non-responders demonstrated more aggressive baseline features, including higher rates of liver (34.0% vs. 15.0%) and brain metastasis (10.0% vs. 1.3%), as well as lower progesterone receptor expression (median 30% vs. 60%). Conclusions: Early metabolic response assessed by SUV-max on interim ^18F-FDG PET/CT is independently associated with substantially improved PFS and OS in HR+/HER2− MBC receiving treatment with CDK4/6 inhibitors. Although the predictive accuracy of ΔSUVmax alone was modest, the strong survival gradient suggests meaningful prognostic value. Prospective studies with standardized imaging time points and comprehensive metabolic metrics are warranted to define the role of PET-guided treatment adaptation: Full article

Previous cases of trigeminal neuralgia (TN) caused by fungal sinusitis have been reported, but mainly in immunocompromised patients. We present a case of fungal sinusitis masquerading as trigeminal neuralgia in an immunocompetent patient and discuss the potential implications of these two diseases. The patient is a 59-year-old male who presented with a four-year duration of left facial pain. He had been diagnosed and treated for trigeminal neuralgia by a pain specialist but was subsequently referred to ENT after a MRI of the brain showed left maxillary sinusitis. Nasoendoscopy findings and a CT scan of the paranasal sinuses were concordant with left maxillary sinusitis. The patient underwent left functional endoscopic sinus surgery and recovered uneventfully. Our study shows that even in immunocompetent patients who present with non-resolving or worsening facial pain resembling the original diagnosis of TN, clinicians should remain vigilant for the possibility of alternative underlying pathologies including fungal sinusitis. Full article

Presently, the segmentation of brain tumors from magnetic resonance imaging (MRI) scans is a very important challenge in the medical area, and it has a huge impact on correct diagnosis, efficient treatment planning, and patient prognosis. We present here the Contextual Transformer U-Net (CT-UNet), a novel deep learning approach that can significantly increase the accuracy and speed of brain tumor segmentation. The CT-UNet method features Transformer blocks embedded in a U-Net layout that extracts the most important contextual information across different types of MRI sequences, thereby drastically refining the delineation of tumor regions. We have tested CT-UNet on the Brain Tumor Segmentation (BraTS) challenge dataset that includes a large variety of tumor types, localization, and progression stages. To check the model’s performance, we used the Dice coefficient, sensitivity, specificity, precision, and Hausdorff distance metrics. The findings from our experiments demonstrate that CT-UNet has a substantial advantage over the classical segmentation model, and the 0.92 Dice coefficient it has achieved testifies to its state-of-the-art tumor localization in terms of both extent and form. Besides that, CT-UNet has achieved a very high sensitivity (0.90) and specificity (0.94); thus, it has been perfectly capable of discriminating tumor from non-tumor tissues. Spatial accuracy has also been improved significantly, as can be seen from the 7.5 mm Hausdorff distance achieved by this model, which means it can closely replicate the given tumor boundaries. By employing dynamic modality fusion and incorporating the Transformer mechanism into the established U-Net architecture, we have raised the bar for brain tumor segmentation. Our solution paves the way for another breakthrough in medical imaging technologies. CT-UNet not only speeds up the workflow of radiologists but also facilitates more targeted therapeutic strategies that may result in better patient care and prognosis. Yet the main goal of this work is to provide a basis for future studies that can consider incorporating deep learning methods in a routine clinical setting, thus paving the way for healthcare providers to benefit from both technical and clinical advantages. Full article

Computed tomography (CT) images are stored at a 12-bit depth. However, many deep learning libraries and pre-trained models are designed for 8-bit images, requiring an intermediate compression step before restoring the original 12-bit physical range. This process causes information loss and can compromise image reliability. This study investigated the impact of two CT resampling methods (8-bit compression; 12-bit decompression) on dose calculation and image quality. Ten total marrow and lymphoid irradiation patients were selected. CT scans were resampled using linear and non-linear look-up tables (l_LUT/nl_LUT). Original and resampled CTs were evaluated considering: (i) Hounsfield unit (HU) root mean squared error (RMSE); (ii) dose-volume histogram (DVH) statistics for target volume and several organs; (iii) 3D gamma passing rate (GPR) with a 1%/1.25 mm criterion; (iv) lymph nodes contouring and diagnostic quality (scale 1–5). The RMSE for l_LUT vs. nl_LUT was 7 ± 1 vs. 10 ± 1 HU. Maximum differences in DVH statistics were 0.4%, with a 3D-GPR = 100% for all cases. CTs resampled with l_LUT exhibited evident brain pixelation (score = 1), whereas nl_LUT matched the original CT quality (score = 4). Both LUTs were acceptable for lymph nodes delineation. The nl_LUT optimized the CT resampling process, providing a more efficient method for possible deep learning applications in synthetic CT generation. Full article

Lung cancer is considered to be a significant cause of death in the world, and the timely identification of nodules in the lungs in CT scans is very important to enhance the prognosis of patients. Although the state of the art of nodule delineation using deep learning-based segmentation models was achieved, major problems, including high feature diversity, low spatial discrimination, and overfitting of the models, require stronger feature-processing approaches. This research explores an enhanced symmetric encoder–decoder segmentation network known as the Improved Group–Shuffle Module (IGSM) to overcome these shortcomings. The most important feature of the proposed method is the IGSM, which hierarchically divides feature maps into a few groups, then transforms them independently, and then randomly switches channels between groups to increase inter-group interaction of features and diversity. This IGSM method is inspired by human brain functions, which are processed in specialized cortex areas, which are mimicked in this work through small-group feature processing. Channel shuffling is designed based on inter-modular communication in the human brain through coherent information sharing among the small groups of cortices. Through this mechanism, the model is much better at capturing discriminative spatial and contextual patterns, especially on complex and subtle nodule structures. The IGSM configurations have been optimized, specifically, the placement of the modules, grouping size, and shuffle permutation strategies. The proposed model’s performance is then compared with the benchmarked models, like U-Net and DeepLab, with various performance indicators such as mean Intersection over Union (mIoU), Dice Score, Accuracy, Sensitivity, and Specificity. The simulation results proved the superiority of the IGSM-enhanced model with the mIoU of 0.7735, the Dice Score of 0.9665, and the Accuracy of 0.9873. The addition of the group and shuffle module not only enhances the discrimination between the nodules and their background, but it also improves the ability to generalize over a variety of nodules’ morphology, thus producing a reliable tool for automated detection of lung cancer. Full article

Objective: We present the first clinical experience with the BIOGRAPH One next-generation PET/MRI system scanner, evaluating its performance for body and brain imaging in patients across multiple tracers. Methods: A total of 59 patients were scanned on the BIOGRAPH One PET/MRI following standard clinical PET/CT (n = 52) or first-generation PET/MRI (Biograph mMR, n = 7). Scans comprised 30 total body (TB), whole body (WB), or regional scans with [¹⁸F]FDG, and 29 brain scans with either [¹⁸F]FDG (n = 5), [¹⁸F]FE-PE2I (n = 10), [¹⁸F]FET (n = 4), or [⁶⁸Ga]Ga-DOTATOC (n = 10). The PET image quality was visually assessed using a 5-point Likert scale (1 = very good to 5 = very bad) and compared with clinical scans acquired on either a current-generation digital PET/CT or a first-generation PET/MRI system, including evaluation of diagnostic concordance. PET quantification and image noise was compared in brain and WB/TB [¹⁸F]FDG PET scans. Results: PET image quality was rated as good or very good in 93% of scans with a median [inter-quartile range] score of 1.5 [1.5;2]. In 99% of cases, image quality was judged equal to or better than the clinical reference scan (median score 3 [2.5;3]). Diagnostic concordance was observed in 99% of readings. Imaging metrics revealed the anticipated regional bias in brain imaging, while no significant bias was observed in body imaging. Image noise was comparable to that observed with digital PET/CT and demonstrated superiority over first-generation PET/MRI despite potential degradation related to isotope decay in BIOGRAPH One PET/MRI acquisitions scans performed at the end of the imaging workflow. Conclusions: Within the study limitations related to sequential imaging, the BIOGRAPH One PET/MRI scanner demonstrated improved PET sensitivity and workflow potential over its first-generation predecessor, which may allow for broader clinical and research applications. Full article

Major traumas result from the application of multiple force components that, in adulthood, can lead to high mortality and morbidity. In forensic practice, pathological consequences arising from the rapid flexion–extension of an adult victim’s soma are observed, with typical intracranial and ophthalmological findings. The totality of these findings allows for a contribution to the definition of the Shaken Adult Syndrome (SAS). A comprehensive review, employing the PRISMA methodology, was conducted on international works pertaining to SAS. This resulted in the identification of six scientific papers, which were analyzed separately. It emerged that, for the diagnosis of SAS, the same diagnostic triad as Shaken Baby Syndrome is valid, comprising subdural hemorrhages, retinal hemorrhages, and encephalopathy. This syndrome appears to encompass a broad spectrum of pathological conditions, ranging from whiplash to diffuse axonal injury (DAI). At the conclusion of this work, we proposed a diagnostic flowchart that allows for suspected predictive diagnosis of SAS, both in live patients presenting to emergency medical services and in post-mortem cadavers. For this purpose, the collection of anamnesis and circumstantial data, the detection of external injuries, and the execution of cranial CT scans will be essential. Ultimately, microscopic examinations of the brain with specific immunomarkers and of ocular structures will enable the identification of pathognomonic findings for SAS. Full article

Insects rely on a variety of sensory cues for orientation, with antennae playing a central role in receiving and transmitting information about the environment. Philaenus spumarius (Hemiptera: Aphrophoridae), a spittlebug and vector of the bacterium Xylella fastidiosa, has a reduced number of antennal sensilla, yet demonstrates effective multimodal communication through olfactory and vibrational signals. This study aimed to investigate how the simplified sensory system of P. spumarius relates to the primary neuropils of the brain. We examined the ultrastructural organization of Johnston’s organ using scanning and transmission electron microscopy, complemented by previous data on antennal sensilla. Brain organization was investigated by Micro-CT and confocal laser scanning microscopy, which enabled us to identify the primary neuropiles. In addition, we conducted antennal and single sensillum backfills to trace sensory neurons to the brain. Our findings provide insight into the adaptation of a simplified sensory system for effective communication and orientation in P. spumarius. Full article

Background/Objectives: The external occipital protuberance (EOP) is an anatomical landmark with radiological and anthropological implications. Although the morphology and prevalence of EOP have been studied in many populations, data remain lacking for Northeastern Thais. Population-specific characterization of EOP variation may improve diagnostic and forensic accuracy applications. Materials and Methods: This study has investigated the prevalence and morphometry of EOPs using two primary sources: CT brain scans from 750 adult patients (375 males, 375 females) and anatomical investigations of 1060 dry skulls. EOPs were classified as Type I (flat), Type II (crest), or Type III (spur). Measurements for Type II (crest-shaped) EOPs were performed using standardized linear and angular parameters. Data differences were analyzed by sex and age group; intra- and inter-observer reliability was calculated for imaging measurements. Results: The study showed that Type II EOP was most common in both CT (56.1%) and dry skull (64.6%) samples. Type I was significantly more frequent in females (CT: 37.0%; dry skull: 32.8%), while Type III prevalence was higher in males (CT: 28.5%; dry skull: 18.4%). After age 60, the incidence of Type III declined in both datasets. Type II EOPs were significantly larger in males (mean crest length in CT: males 7.1 ± 0.1 mm, females 5.6 ± 0.1 mm; p < 0.001), with notable sex- and age-associated variation in associated angular dimensions. Conclusions: These findings established the first region-specific morphometric reference database for EOP in Northeastern Thais. The demonstrated sexual dimorphism in Type II EOP measurements provided the foundational data that may support future applications in clinical assessment, radiological interpretation, and forensic sex estimation in this population. Full article

Background and Clinical Significance: Adults suffering from cerebellar metastases are often at high risk for rapid deterioration of their neurological status because the posterior fossa has limited compliance and the location of these metastases are close to the brain stem and important cerebrospinal fluid (CSF) pathways. In this paper, we present a longitudinal, patient-centered report on the history of an elderly individual who suffered from cognitive comorbidities and experienced a sudden loss of function in her cerebellum. Our goal in reporting this case is to provide a comparison between the patient’s pre-operative and post-operative neurological examinations; the imaging studies she had before and after surgery; the surgical techniques utilized during her operation; and the outcome of her post-operative course in a way that will be helpful to other patients who have experienced a similar situation. Case Presentation: We report the case of an 80-year-old woman who initially presented with progressive ipsilateral limb-trunk ataxia, impaired smooth pursuit eye movement, and rebound nystagmus, but preserved pyramidal and sensory functions. Her quantitative bedside assessments included some of the components of the Scale for the Assessment and Rating of Ataxia (SARA), and a National Institute of Health Stroke Scale (NIHSS) score of 3. These findings indicated dysfunction of the left neocerebellar hemisphere and possible dentate nucleus involvement. The patient’s magnetic resonance imaging (MRI) results demonstrated an expansive mass with surrounding vasogenic edema and marked compression and narrowing of the exits of the fourth ventricle which placed the patient’s CSF pathways at significant risk of occlusion, while the aqueduct and inlets were patent. She then underwent a left lateral suboccipital craniectomy with controlled arachnoidal CSF release, preservation of venous drainage routes, subpial corticotomy oriented along the lines of the folia, stepwise internal debulking, and careful protection of the cerebellar peduncles and dentate nucleus. Dural reconstruction utilized a watertight pericranial graft to restore the cisternal compartments. Her post-operative intensive care unit (ICU) management emphasized optimal venous outflow, normoventilation, and early mobilization. Histopathology confirmed the presence of metastatic carcinoma, and staging suggested that the most likely source of the primary tumor was the lungs. Immediately post-operation, computed tomography (CT) imaging revealed a smooth resection cavity with open foramina of Magendie and Luschka, intact contours of the brain stem, and no evidence of bleeding or hydrocephalus. The patient’s neurological deficits, including dysmetria, scanning dysarthria, and ataxic gait, improved gradually during the first 48 h post-operatively. Upon discharge, the patient demonstrated an improvement in her limb-kinetic subscore on the International Cooperative Ataxia Rating Scale (ICARS) and demonstrated independent ambulation. At two weeks post-operation, CT imaging revealed decreasing edema and stable cavity size, and the patient’s modified Rankin scale had improved from 3 upon admission to 1. There were no episodes of CSF leakage, wound complications, or new cranial nerve deficits. A transient post-operative psychotic episode that was likely secondary to her underlying Alzheimer’s disease was managed successfully with short-course pharmacotherapy. Conclusions: The current case study demonstrates the value of anatomy-based microsurgical planning, preservation of venous and CSF pathways, and targeted peri-operative management to facilitate rapid recovery of function in older adults who suffer from cerebellar metastasis and cognitive comorbidities. The case also demonstrates the importance of early multidisciplinary collaboration to allow for timely initiation of both adjuvant stereotactic radiosurgery and molecularly informed systemic therapy. Full article

This study identifies a significant association among blood-based biomarkers of traumatic brain injury (TBI) and the Marshall CT classification of TBI (MCTC) scores, but not with Glasgow Coma Scale (GCS) scores. We aimed to determine whether GCS and MCTC scores relate to glial fibrillary acid protein (GFAP), ubiquitin carboxy hydrolase-1 (UCH-L1), tau, neurofilament light chain (NfL), and phosphorylated tau (p-tau231) concentrations following acute TBIs. Participants included patients from 20 trauma centers across 12 regional sites in the United States and Canada with an initial CT scan within 6 h after TBI and GCS scores of 3 to 12. Blood samples collected upon hospital arrival were analyzed for biomarker concentrations (pg/mL). Concentrations from 271 patients with GCS ≥ 9 were compared to 145 with GCS ≤ 9. Samples from 347 patients with MCTC < 3 were compared to 70 with MCTC ≥ 3. No significant differences in GCS groups were found (p’s > 0.5), while MCTC groups differed significantly (p’s < 0.001). Higher concentrations of plasma GFAP, NfL, and p-tau231 correlated with MCTC scores > 3, with no associations with GCS. Future research might show an application in individual risk assessments to improve triaging of TBI patients. Full article

Positron emission tomography/computed tomography (PET/CT) scanners equipped with silicon photomultiplier detectors offer superior sensitivity and count-rate performance. The aim of this study was to evaluate the feasibility and impact of shortening the acquisition duration in brain tumor ¹¹C-methionine PET using a silicon photomultiplier PET/CT system, and to assess how point spread function (PSF) correction influences quantitative values. In the phantom study, a brain tumor phantom was scanned using the Biograph Vision silicon photomultiplier-based PET/CT system. Data were acquired for 10, 5, 3, and 1 min, and the images were reconstructed with and without PSF correction. In the clinical study, 20 patients who underwent ¹¹C-methionine PET were retrospectively analyzed. PET data were acquired over 10 min and subsequently reconstructed for 10, 5, and 3 min. We evaluated quantitative parameters including the maximum standardized uptake value (SUVmax), and their relative errors under shortened acquisition durations were analyzed. In the phantom study, the SUVmax increased with shorter acquisition durations; however, this increase was less pronounced with PSF correction. In the clinical study, relative errors of SUVmax for the 5 and 3 min acquisitions with PSF correction were 2.9 ± 3.8% and 5.2 ± 5.4%, respectively. They were smaller than those without PSF correction (5.5 ± 5.1% and 12.7 ± 8.5%), indicating superior quantitative stability with shortened acquisition duration. The combination of the Biograph Vision system and PSF correction enabled the acquisition of high-quality PET images with shortened scan times. Full article