The role of baseline 18F-FDG PET/CT for survival prognosis in NSCLC patients undergoing immunotherapy: a systematic review and meta-analysis.

Background: The value of pretreatment baseline 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET)/computed tomography (CT) as a prognostic factor for survival of patients with non-small-cell lung cancer (NSCLC) receiving immunotherapy remained uncertain. Objectives: To investigate the prognostic ability of baseline 18F-FDG PET/CT in patients with NSCLC receiving immunotherapy. Design: A systematic review and meta-analysis. Data sources and methods: We searched the PubMed, EMBASE, and Cochrane Central Register of Controlled Trials databases until May 7, 2024, and extracted data related to patient characteristics, semiquantitative parameters of 18F-FDG PET/CT, and survival. We pooled hazard ratios (HRs) to evaluate the prognostic value of the maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) for overall survival (OS) and progression-free survival (PFS). Results: A total of 22 studies (1363 patients, average age range 30-88 years) were included. Baseline 18F-FDG PET/CT-derived MTV was significantly associated with both OS (HR: 1.124, 95% confidence interval (CI) 1.058-1.195, I 2 = 81.70%) and PFS (HR: 1.069, 95% CI: 1.016-1.124, I 2 = 71.80%). Other baseline 18F-FDG PET/CT-derived parameters, including SUVmax (OS: HR: 0.930, 95% CI: 0.718-1.230; PFS: HR: 0.979, 95% CI: 0.759-1.262), SUVmean (OS: HR: 0.801, 95% CI: 0.549-1.170; PFS: HR: 0.688, 95% CI: 0.464-1.020), and TLG (OS: HR: 0.999, 95% CI: 0.980-1.018; PFS: HR: 0.995, 95% CI: 0.980-1.010), were not associated with survival. Sensitivity analyses by removing one study at a time did not significantly alter the association between MTV and PFS or between MTV and OS. There was no evidence of publication bias. Conclusion: Pretreatment baseline 18F-FDG PET/CT-derived MTV might be a prognostic biomarker in NSCLC patients receiving immunotherapy. Further studies are needed to support routine use.

Using PET/CT scans to predict survival in lung cancer patients receiving immunotherapy: a study review Aims and Purpose of the Research We wanted to know if a type of scan called ¹⁸F-FDG PET/CT can help predict how long people with a type of lung cancer (NSCLC) will live after treatment with immunotherapy. Background of the Research This research matters because NSCLC is a common and serious type of lung cancer. Knowing how long patients might live after treatment can help doctors plan better care. Many people are affected by this disease, so finding good ways to predict survival can help a lot of patients. Methods and Research Design They reviewed and analyzed data from 22 different studies involving 1363 patients, with ages ranging from 30 to 88 years.We focused on certain measurements from the scans, like SUV_max, SUV_mean, MTV, and TLG. We checked if these measurements were linked to how long patients lived and how long they lived without their cancer getting worse. Results and Importance We found that one of these measurements, the Metabolic Tumor Volume (MTV), was linked to how long the patients lived and how long they stayed free of disease after treatment. Specifically, higher MTV was associated with poorer overall survival and progression-free survival. The other measurements (SUV_max, SUV_mean, and TLG) did not show a significant connection to patient survival. In conclusion, the MTV from PET/CT scans might help doctors predict the outcomes for lung cancer patients undergoing immunotherapy. However, more studies are needed to confirm these findings and to consider using this measurement regularly in clinical practice.

Association of Cardiovascular Risk Factors and Coronary Calcium Burden with Epicardial Adipose Tissue Volume Obtained from PET-CT Imaging in Oncological Patients.

Whole-body positron emission tomography (PET)-computed tomography (CT) imaging performed for oncological purposes may provide additional parameters such as the coronary artery calcium (CAC) and epicardial adipose tissue (EAT) volume with cost-effective prognostic information in asymptomatic people beyond traditional cardiovascular risk factors. We evaluated the feasibility of measuring the CAC score and EAT volume in cancer patients without known coronary artery disease (CAD) referred to whole-body 18F-FDG PET-CT imaging, regardless of the main clinical problem. We also investigated the potential relationships between traditional cardiovascular risk factors and CAC with EAT volume. A total of 109 oncological patients without overt CAD underwent whole-body PET-CT imaging with 18F-fluorodeoxyglucose (FDG). Unenhanced CT images were retrospectively viewed for CAC and EAT measurements on a dedicated platform. Overall, the mean EAT volume was 99 ± 49 cm3. Patients with a CAC score ≥ 1 were older than those with a CAC = 0 (p < 0.001) and the prevalence of hypertension was higher in patients with detectable CAC as compared to those without (p < 0.005). The EAT volume was higher in patients with CAC than in those without (p < 0.001). For univariable age, body mass index (BMI), hypertension, and CAC were associated with increasing EAT values (all p < 0.005). However, the correlation between the CAC score and EAT volume was weak, and in multivariable analysis only age and BMI were independently associated with increased EAT (both p < 0.001), suggesting that potential prognostic information on CAC and EAT is not redundant. This study demonstrates the feasibility of a cost-effective assessment of CAC scores and EAT volumes in oncological patients undergoing whole-body 18F-FDG PET-CT imaging, enabling staging cancer disease and atherosclerotic burden by a single test already included in the diagnostic work program, with optimization of the radiation dose and without additional costs.

Automated computed tomography-derived fractional flow reserve model for diagnosing haemodynamically significant coronary artery disease: a prospective validation study.

Aims: This study aims to assess the diagnostic performance of a novel computed tomography-derived fractional flow reserve (CT-FFR) algorithm and to compare its accuracy at three predefined sites: (i) at the location of invasive FFR measurements (CT-FFRatloc), (ii) at selected sites determined by an automated module integrated within the algorithm (CT-FFRauto), and (iii) distally in the vessel (CT-FFRdistal). Methods and results: We prospectively recruited 108 consecutive patients with stable symptoms of coronary artery disease and at least one suspected obstructive lesion on coronary computed tomography angiography (CCTA). CT-FFR was validated against invasive FFR as gold standard using FFR ≤ 0.80 to define myocardial ischaemia. CT-FFRatloc showed good correlation with invasive FFR (r = 0.67) and improved the ability to detect myocardial ischaemia compared with CCTA at both lesion [area under the curve (AUC) 0.83 vs. 0.65, P < 0.001] and patient level (AUC 0.87 vs. 0.74, P = 0.007). CT-FFRauto demonstrated similar diagnostic accuracy to CT-FFRatloc and significantly improved specificity compared with CT-FFRdistal (86% vs. 49%, P < 0.001). High end CT quality improved the diagnostic performance of CT-FFRauto, demonstrating an AUC of 0.92; similarly, the performance was improved in patients with low-to-intermediate coronary artery calcium score with an AUC of 0.88. Conclusion: Implementing an automated module to determine the site of CT-FFR evaluations was feasible, and CT-FFRauto demonstrated comparable diagnostic accuracy to CT-FFRatloc when assessed against invasive FFR. Both CT-FFRatloc and CT-FFRauto improved the diagnostic performance compared with CCTA and improved specificity compared with CT-FFRdistal. High end CT quality and low-to-intermediate calcium burden improved the diagnostic performance of our algorithm. ClinicalTrialsgov Identifier: NCT03045601.

Antimicrobial peptide LyeTx I mn∆K labeled with 68Ga is a potential PET radiopharmaceutical for molecular imaging of infections.

BACKGROUND: Antimicrobial peptides have been radiolabeled and investigated as molecular diagnostic probes due to their propensity to accumulate in infectious sites rather than aseptic inflammatory lesions. LyeTx I is a cationic peptide from the venom of Lycosa erythrognatha, exhibiting significant antimicrobial activity. LyeTx I mn∆K is a shortened derivative of LyeTx I, with an optimized balance between antimicrobial and hemolytic activities. This study reports the first 68Ga-radiolabeling of the DOTA-modified LyeTx I mn∆K and primarily preclinical evaluations of [68Ga]Ga-DOTA(K)-LyeTx I mn∆K as a PET radiopharmaceutical for infection imaging. METHODS: DOTA(K)-LyeTx I mn∆K was radiolabeled with freshly eluted 68Ga. Radiochemical yield (RCY), radiochemical purity (RCP), and radiochemical stability (in saline and serum) were evaluated using ascending thin-layer chromatography (TLC) and reversed-phase high-performance liquid chromatography (RP-HPLC). The radiopeptide's lipophilicity was assessed by determining the logarithm of the partition coefficient (Log P). Serum protein binding (SBP) and binding to Staphylococcus aureus (S. aureus) cells were determined in vitro. Ex vivo biodistribution studies and PET/CT imaging were conducted in healthy mice (control) and mice with infection and aseptic inflammation to evaluate the potential of [68Ga]Ga-DOTA(K)-LyeTx I mn∆K as a specific PET radiopharmaceutical for infections. RESULTS: [68Ga]Ga-DOTA(K)-LyeTx I mn∆K was obtained with a high RCY (>90 %), and after purification through a Sep-Pak C18 cartridge, the RCP exceeded 99 %. Ascending TLC and RP-HPLC showed that the radiopeptide remained stable for up to 3.0 h in saline solution and up to 1.5 h in murine serum. [68Ga]Ga-DOTA(K)-LyeTx I mn∆K exhibited hydrophilic characteristics (Log P = -2.4 ± 0.1) and low SPB (ranging from 23.3 ± 0.4 % at 5 min of incubation to 10.5 ± 1.1 % at 60 min of incubation). The binding of [68Ga]Ga-DOTA(K)-LyeTx I mn∆K to S. aureus cells was proportional to bacterial concentration, with binding percentages of 8.8 ± 0.5 % (0.5 × 109 CFU.mL-1), 16.2 ± 1.4 % (1.0 × 109 CFU.mL-1), and 62.2 ± 0.6 % (5.0 × 109 CFU.mL-1). Ex vivo biodistribution studies and PET/CT images showed higher radiopeptide uptake at the infection site compared to the aseptic inflammation site; the latter was similar to the control group. Target-to-non-target (T/NT) ratios obtained by ex vivo biodistribution data were approximately 1.0, 1.3, and 3.0 at all investigated time intervals for the control, aseptic inflammation, and infection groups, respectively. Furthermore, T/NT ratios obtained from PET/CT images were 1.1 ± 0.1 for the control group and 1.4 ± 0.1 for the aseptic inflammation group. For the infection group, T/NT ratio was 5.0 ± 0.3, approximately 5 times greater compared to the former groups. CONCLUSIONS: The results suggest the potential of [68Ga]Ga-DOTA(K)-LyeTx I mn∆K as a PET radiopharmaceutical for molecular imaging of infections.

Contrast-Enhanced Micro-CT Imaging of Murine Mandibles: A Multi-Method Approach for Simultaneous Hard and Soft Tissue Analysis.

AIM: To develop and evaluate a novel multi-method micro-computed tomography (µCT) imaging protocol for enhanced visualization of both hard and soft tissues in murine mandibles, addressing the limitations of traditional imaging techniques in dental research. MATERIALS AND METHODS: We employed a contrast-enhanced (CE) µCT imaging technique using Lugol's iodine as a contrast agent to visualize the intricate structures of murine mandibles. The protocol involved the combination of conventional µCT imaging as well as CE-µCT, including decalcification with EDTA, allowing for simultaneous assessment of hard and soft tissues. The method is compared with standard imaging modalities, and the ability to visualize detailed anatomical features is discussed. RESULTS: The CE-µCT imaging technique provided superior visualization of murine mandibular structures, including dental pulp, periodontal ligaments and the surrounding soft tissues, along with conventional µCT imaging of alveolar bone and teeth. This method revealed detailed anatomical features with high specificity and contrast, surpassing traditional imaging approaches. CONCLUSION: Our findings demonstrate the potential of CE-µCT imaging with Lugol's iodine as a powerful tool for dental research. This technique offers a comprehensive view of the murine mandible, facilitating advanced studies in tissue engineering, dental pathology and the development of dental materials.

Study on the impact of bowtie filter on photon-counting CT imaging.

Objective.The aim of this study was to investigate the impact of the bowtie filter on the image quality of the photon-counting detector (PCD) based CT imaging.Approach.Numerical simulations were conducted to investigate the impact of bowtie filters on image uniformity using two water phantoms, with tube potentials ranging from 60 to 140 kVp with a step of 5 kVp. Subsequently, benchtop PCD-CT imaging experiments were performed to verify the observations from the numerical simulations. Additionally, various correction methods were validated through these experiments.Main results.It was found that the use of a bowtie filter significantly alters the uniformity of PCD-CT images, depending on the size of the object and the x-ray spectrum. Two notable effects were observed: the capping effect and the flattening effect. Furthermore, it was demonstrated that the conventional beam hardening correction method could effectively mitigate such non-uniformity in PCD-CT images, provided that dedicated calibration parameters were used.Significance.It was demonstrated that the incorporation of a bowtie filter results in varied image artifacts in PCD-CT imaging under different conditions. Certain image correction methods can effectively mitigate and reduce these artifacts, thereby enhancing the overall quality of PCD-CT images.

Head and Neck Cancer and Sarcopenia: An Integrative Clinical and Functional Review.

Sarcopenia is recognized as a crucial factor impacting the prognosis, treatment responses, and quality of life of HNC patients. This review discusses various mechanisms, including common etiological factors, such as aging, chronic inflammation, and metabolic dysregulation. Cancer-related factors, including tumor locations and treatment modalities, contribute to the development of sarcopenia. The clinical implications of sarcopenia in HNC patients extend beyond reduced muscle strength; it affects overall mobility, reduces quality of life, and increases the risk of falls and fractures. Sarcopenia serves as an independent predictor of postoperative complications, chemotherapy dose-limiting toxicity, and treatment outcomes, which affect therapy planning and perioperative management decisions. Methods to assess sarcopenia in HNC patients encompass various techniques. A sarcopenia assessment offers a potentially efficient and readily available tool for clinical practice. Interventions and management strategies for sarcopenia involve exercise interventions as a cornerstone; however, challenges arise due to patient-specific limitations during cancer treatment. A routine body composition analysis is proposed as a valuable addition to HNC patient management, with ongoing research required to refine preoperative exercise and nutrition programs for improved treatment outcomes and survival.

Multiparametric Approach to the Colorectal Cancer Phenotypes Integrating Morphofunctional Assessment and Computer Tomography.

(1) Background: Accurate body composition assessment in CCR patients is crucial due to the high prevalence of malnutrition, sarcopenia, and cachexia affecting survival. This study evaluates the correlation between body composition assessed by CT imaging as a reference technique, BIVA, nutritional ultrasound, and handgrip strength in CCR patients. (2) Methods: This retrospective study included CCR patients assessed by the Endocrinology and Nutrition Services of Virgen de la Victoria in Malaga and Vall d'Hebron in Barcelona from October 2018 to July 2023. Assessments included anthropometry, BIVA, NU, HGS, and AI-assisted CT analysis at the L3 level for body composition. Pearson's analysis determined the correlation of CT-derived variables with BIVA, NU, and HGS. (3) Results: A total of 267 CCR patients (mean age 68.2 ± 10.9 years, 61.8% men) were studied. Significant gender differences were found in body composition and strength. CT-SMI showed strong correlations with body cell mass (r = 0.65), rectus femoris cross-sectional area (r = 0.56), and handgrip strength (r = 0.55), with a Cronbach's alpha of 0.789. CT-based adipose tissue measurements showed significant correlations with fat mass (r = 0.56), BMI (r = 0.78), A-SAT (r = 0.49), and L-SAT (r = 0.66). Regression analysis indicated a high predictive power for CT-SMI, explaining approximately 80% of its variance (R2 = 0.796). (4) Conclusions: Comprehensive screening of colorectal cancer patients through BIVA, NU, HGS, and CT optimizes the results of the evaluation. These methods complement each other in assessing muscle mass, fat distribution, and nutritional status in CCR. When CT is unavailable or bedside assessment is needed, HGS, BIVA, and NU provide an accurate assessment of body composition.

Validation of radiolabelled exendin for beta cell imaging by ex vivo autoradiography and immunohistochemistry of human pancreas.

BACKGROUND: Estimation of beta cell mass is currently restricted to evaluating pancreatic tissue samples, which provides limited information. A non-invasive imaging technique that reliably quantifies beta cell mass enables monitoring of changes of beta cell mass during the progression of diabetes mellitus and may contribute to monitoring of therapy effectiveness. We assessed the specificity of radiolabelled exendin for beta cell mass quantification in humans. Fourteen adults with pancreas tumours were injected with 111In-labeled exendin-4 prior to pancreatic resection. In resected pancreas tissue, endocrine-exocrine ratios of tracer uptake were determined by digital autoradiography and accumulation of 111In-labeled exendin-4 was compared to insulin and GLP-1 receptor staining. Of four participants, abdominal single photon emission computed tomography/computed tomography (SPECT/CT) images were acquired to quantify pancreatic uptake in vivo RESULTS: Tracer uptake was predominantly present in the endocrine pancreas (endocrine-exocrine ratio: 3.6 [2.8-10.8]. Tracer accumulation showed overlap with insulin-positive regions, which overlapped with GLP-1 receptor positive areas. SPECT imaging showed pancreatic uptake of radiolabelled exendin in three participants. CONCLUSION: Radiolabelled exendin specifically accumulates in the islets of Langerhans in human pancreas tissue. The clear overlap between regions positive for insulin and the GLP-1 receptor substantiate the beta cell specificity of the tracer. Radiolabelled exendin is therefore a valuable imaging agent for human beta cell mass quantification and has the potential to be used for a range of applications, including improvement of diabetes treatment by assessment of the effects of current and novel diabetes therapies on the beta cell mass. TRIAL REGISTRATION: ClinicalTrials.gov NCT03889496, registered 26,032,019, URL https://clinicaltrials.gov/study/NCT03889496?term=NCT03889496 . CLINICALTRIALS: gov NCT04733508, registered 02022021, URL https://clinicaltrials.gov/study/NCT04733508 .

Enhanced prognostic accuracy in severe TBI: a comprehensive nomogram analysis.

OBJECTIVE: This study aims to enhance prognostic accuracy in severe traumatic brain injury (STBI) by developing a novel nomogram that integrates clinical and paraclinical data. METHODS: Data from 263 STBI patients were analyzed, focusing on critical variables such as age, Glasgow Coma Scale scores, pupil responsiveness, CT findings, and blood markers. A rigorous regression analysis was conducted to identify significant predictors. The nomogram underwent internal and external validation, and its predictive performance was compared with existing models through a meta-analysis. RESULTS: The novel nomogram demonstrated superior predictive accuracy for STBI outcomes compared to traditional models. Key predictors, including age, Glasgow Coma Scale scores, pupil responsiveness, CT findings, and specific blood markers, were harmonized to provide a more precise prognostic tool. Validation processes confirmed the robustness and reliability of the nomogram. CONCLUSION: The developed nomogram represents a significant advancement in STBI prognosis, offering clinicians a powerful tool to improve patient care strategies. By integrating CT imaging and blood parameters, the nomogram enhances the precision of outcome predictions, facilitating better-informed clinical decisions.

Advanced artificial intelligence framework for T classification of TNM lung cancer in18FDG-PET/CT imaging.

The integration of artificial intelligence (AI) into lung cancer management offers immense potential to revolutionize diagnostic and treatment strategies. The aim is to develop a resilient AI framework capable of two critical tasks: firstly, achieving accurate and automated segmentation of lung tumors and secondly, facilitating the T classification of lung cancer according to the ninth edition of TNM staging 2024 based on PET/CT imaging. This study presents a robust AI framework for the automated segmentation of lung tumors and T classification of lung cancer using PET/CT imaging. The database includes axial DICOM CT and18FDG-PET/CT images. A modified ResNet-50 model was employed for segmentation, achieving high precision and specificity. Reconstructed 3D models of segmented slices enhance tumor boundary visualization, which is essential for treatment planning. The Pulmonary Toolkit facilitated lobe segmentation, providing critical diagnostic insights. Additionally, the segmented images were used as input for the T classification using a CNN ResNet-50 model. Our classification model demonstrated excellent performance, particularly for T1a, T2a, T2b, T3 and T4 tumors, with high precision, F1 scores, and specificity. The T stage is particularly relevant in lung cancer as it determines treatment approaches (surgery, chemotherapy and radiation therapy or supportive care) and prognosis assessment. In fact, for Tis-T2, each increase of one centimeter in tumor size results in a worse prognosis. For locally advanced tumors (T3-T4) and regardless of size, the prognosis is poorer. This AI framework marks a significant advancement in the automation of lung cancer diagnosis and staging, promising improved patient outcomes.

Feasibility of ultra-low activity 18F-FDG PET/CT imaging in children.

OBJECTIVES: To investigate the feasibility of pediatric 18F-FDG total-body PET/CT imaging with an ultra-low activity and explore an optimized acquisition time range. METHODS: A total of 38 pediatric patients were prospectively enrolled and underwent dynamic total-body PET/CT imaging using ultra-low 18F-FDG activity (0.37 MBq/kg). The 60-minute list-mode raw data were acquired and then reconstructed as static PET images by using 50-51, 50-52, 50-53, 50-54, 50-55, 50-58, 50-60, and 45-60 minutes data, which were noted as G1, G2, G3, G4, G5, G8, G10, and G15, respectively. Image qualities were subjectively evaluated using the Likert scale and were objectively evaluated by the quantitative metrics including standard uptake value (SUV), signal-to-noise ratio (SNR), target-to-background ratio (TBR), and contrast-to-noise ratio (CNR). RESULTS: The injected activity of FDG was 13.38 ± 5.68 MBq (4.40-28.16 MBq) and produced 0.58 ± 0.19 mSv (0.29-1.04 mSv) of effective dose. The inter-reader agreement of subjective image quality was excellent (kappa = 0.878; 95% CI, 0.845-0.910). The average scores of image quality for G1-G15 were 1.10 ± 0.20, 2.03 ± 0.26, 2.66 ± 0.35, 3.00 ± 0.27, 3.32 ± 0.34, 4.25 ± 0.30, 4.49 ± 0.36, and 4.70 ± 0.37, respectively. All image scores are above 3 and all lesions are detectable starting from G8. SNRs of backgrounds, TBRs, and CNRs were significant differences from the control group before G8 (all P < 0.05). CONCLUSION: The image quality of the 8 min acquisition for pediatric 18F-FDG total-body PET/CT with an ultra-low activity could meet the diagnostic requirements. ADVANCES IN KNOWLEDGE: This study confirms the feasibility of ultra-low dose PET imaging in children, and its methods and findings may guide clinical practice. pediatric patients will benefit from reduced radiation doses.

A Case Report of Inguinal Hernia Containing the Appendix: Amyand's Hernia.

Numerous types of hernias have been reported in the literature. A unique and uncommon type of hernia known as an Amyand's hernia occurs when the inguinal sac contains the vermiform appendix. Due to its rarity, it is usually difficult to diagnose and often goes unreported. However, when it goes unnoticed and untreated, it can lead to complications such as strangulation and perforation. This is where medical imaging plays a pivotal role. This case study aims to provide an overview of Amyand's hernia while highlighting the vital role that imaging plays in diagnosing the condition, identifying any associated problems, characterizing the pathology, and classifying the hernia. This supports grading the severity and determining the appropriate course of management.

Detection of damage caused by Nezara viridula on soybean using novel imaging approaches based on computed tomography and image color analysis.

Soybean (Glycine max L.) is an important leguminous plant, in which pests trigger significant damage every year. Important members of this community are insects with piercing-sucking mouthpart, especially the southern green stinkbug, Nezara viridula L.. This insect with its extraoral digestion causes visible alterations (morphological and color changes) in the seeds. We aimed to obtain precise information about the extent and nature of damage in soybeans caused by N. viridula using nondestructive imaging methods. Two infestation conditions were applied: one with controlled numbers of pests (six insects/15 pods) and another with naturally occurring pests (samples collected from the apical part of the plant and samples from whole plants). An intact control group was also included, resulting in four treatment groups. Seed samples were analyzed by computed tomography (CT) and image color analysis under laboratory conditions. According to our CT findings, the damage caused by N. viridula changed the radiodensity, volume, and shape (Solidity) of the soybean seeds during the pod-filling and maturing period. Radiodensity was significantly reduced in all three damaged categories compared to the intact sample; the mean radiodensity reduction range was 49-412 HU. The seed volume also decreased significantly (25%-80% decrease), with a threefold reduction for samples exposed to regulated damage compared to natural ones. The samples exposed to natural damage showed significant but minor reduction in solidity, while samples exposed to regulated damage showed a prominent decrease (~12%). Image color analysis showed that the damaged samples were well distinguishable, and the differences were statistically verifiable. The achieved data derived from our external and internal imaging approaches contribute to a better understanding of the internal chemical processes, and CT analysis helps to understand the alteration trends of the hidden structure of seeds caused by a pest. Our results can contribute to the development of a practically applicable system based on image analysis, which can identify lots damaged by insects.

Deep bone oncology Diagnostics: Computed tomography based Machine learning for detection of bone tumors from breast cancer metastasis.

Purpose: The objective of this study is to develop a novel diagnostic tool using deep learning and radiomics to distinguish bone tumors on CT images as metastases from breast cancer. By providing a more accurate and reliable method for identifying metastatic bone tumors, this approach aims to significantly improve clinical decision-making and patient management in the context of breast cancer. Methods: This study utilized CT images of bone tumors from 178 patients, including 78 cases of breast cancer bone metastases and 100 cases of non-breast cancer bone metastases. The dataset was processed using the Medical Image Segmentation via Self-distilling TransUNet (MISSU) model for automated segmentation. Radiomics features were extracted from the segmented tumor regions using the Pyradiomics library, capturing various aspects of tumor phenotype. Feature selection was conducted using LASSO regression to identify the most predictive features. The model's performance was evaluated using ten-fold cross-validation, with metrics including accuracy, sensitivity, specificity, and the Dice similarity coefficient. Results: The developed radiomics model using the SVM algorithm achieved high discriminatory power, with an AUC of 0.936 on the training set and 0.953 on the test set. The model's performance metrics demonstrated strong accuracy, sensitivity, and specificity. Specifically, the accuracy was 0.864 for the training set and 0.853 for the test set. Sensitivity values were 0.838 and 0.789 for the training and test sets, respectively, while specificity values were 0.896 and 0.933 for the training and test sets, respectively. These results indicate that the SVM model effectively distinguishes between bone metastases originating from breast cancer and other origins. Additionally, the average Dice similarity coefficient for the automated segmentation was 0.915, demonstrating a high level of agreement with manual segmentations. Conclusion: This study demonstrates the potential of combining CT-based radiomics and deep learning for the accurate detection of bone metastases from breast cancer. The high-performance metrics indicate that this approach can significantly enhance diagnostic accuracy, aiding in early detection and improving patient outcomes. Future research should focus on validating these findings on larger datasets, integrating the model into clinical workflows, and exploring its use in personalized treatment planning.

Intramuscular myxoma: unusual observation of spontaneous tumor size shrinkage.

Soft tissue tumors, whether benign or malignant, may grow over time or remain stable, but they usually do not spontaneously decrease in size. However, there are exceptions, such as inflammatory conditions, desmoid tumors, or benign cysts. Intramuscular myxomas are benign soft tissue tumors that typically present as a solitary, slow-growing, painless mass. They are generally treated by surgical resection, after which recurrence is rare. Here, we present a brief series of three unusual cases of intramuscular myxomas that spontaneously decreased in size. They were located in the cervical region, the right lower extremity, and the paravertebral lumbar region. Imaging findings and percutaneous biopsies confirmed the diagnosis in all cases. Follow-up imaging showed a spontaneous reduction in lesion volume over time, far exceeding the amount of tissue sample removed during biopsy. This unusual observation of spontaneous shrinkage may call into question the subsequent therapeutic approach to these lesions.

High-Density Lipoprotein Mimetic Peptide 4F Reduces Toxic Amyloid-Beta Exposure to the Blood-Brain Barrier Endothelium in Alzheimer's Disease Transgenic Mice.

Aß accumulation in the blood-brain barrier (BBB) endothelium, which lines the cerebrovascular lumen, is a significant contributor to cerebrovascular dysfunction in Alzheimer's disease (AD). Reduced high-density lipoprotein (HDL) levels are associated with increased AD risk, and the HDL mimetic peptide 4F has been developed as a promising therapeutic agent to improve cerebrovascular health in AD. In this study, we evaluated the impact of 4F on 125I-Aß42 blood-to-brain distribution using dynamic SPECT/CT imaging in both wild-type and APP/PS1 transgenic mice. Graphical analysis of the imaging data demonstrated that 4F significantly reduced the blood-to-brain influx rate in wild-type mice and the distribution of 125I-Aß42 in the BBB endothelium in APP/PS1 mice. To elucidate the molecular mechanisms underlying the effect of 4F, we evaluated its impact on the p38 pathway and its role in mediating Aß42 trafficking in human BBB endothelial cell monolayers. Treatment with 4F significantly decreased Aß42 induced p38 activation in BBB endothelial cells. Furthermore, inhibition of p38 kinase significantly reduced endothelial accumulation of fluorescence-labeled Aß42 and luminal-to-abluminal permeability across the cell monolayer. While our previous publication has hinted at the potential of 4F to reduce Aß accumulation in the brain parenchyma, the current findings demonstrated the protective effect of 4F in reducing Aß42 accumulation in the BBB endothelium of AD transgenic mice. These findings revealed the impact of a clinically tested agent, the HDL mimetic peptide 4F, on Aß exposure to the BBB endothelium and offer novel mechanistic insights into potential therapeutic strategies to treat cerebrovascular dysfunction in AD.

Differential diagnosis between low-risk and high-risk thymoma: Comparison of diagnostic performance of radiologists with and without deep learning model.

Background: There are few CT-based deep learning (DL) studies on thymoma according to the World Health Organization classification. Purpose: To develop a CT-based DL model to distinguish between low-risk and high-risk thymoma and to compare the diagnostic performance of radiologists with and without the DL model. Material and Methods: 159 patients with 160 thymomas were included. A fine-tuning VGG16 network model with Adam optimizer was used, followed by k-fold cross validation. The dataset consisted of three axial slices, including the maximum tumor size from the CT volume data. The data were augmented 50 times by rotation, zoom, shear, and horizontal/vertical flip. Three independent networks for the CT dataset were considered, and the result was determined by voting. Three radiologists independently diagnosed thymomas with and without the model. The area under the curve (AUC) of the diagnostic performance was compared using receiver operating characteristic analysis. Results: Accuracy of the DL model was 71.3%. Diagnostic performance of the radiologists was as follows: AUC and accuracy without the DL model, 0.61-0.68 and 61.9%-69.3%; and with the DL model, 0.66-0.69 and 68.1%-70.0%, respectively. AUC of the diagnostic performance showed no significant differences between radiologists with and without the DL model. The DL model tended to increase the diagnostic accuracy, but AUC was not significantly improved. Conclusion: Diagnostic performance of the DL was comparable to that of radiologists. The DL model assistance tended to increase diagnostic accuracy.

Pulmonary Pasteurella multocida infection with tree-in-bud appearance.

Here, we report a case of zoonosis pulmonary Pasteurella multocida infection with a tree-in-bud appearance. In cases showing a tree-in-bud appearance on chest CT images, pulmonary P. multocida infection should be considered in the differential diagnosis, especially in patients with pets.