Tomography最新文献

Background: As a diagnostic radiology procedure, computed tomography (CT) contributes to patient radiation exposure; hence, it deserves special consideration. The use of diagnostic reference levels (DRLs) is an efficient way to optimize patient radiation dosage. The computed tomography dose index volume (CTDIv) and the dose-length product (DLP) help to measure DRLs. Methods: A retrospective analysis was conducted on 106 patients (43.9% male, 56.1% female; mean age of 48.18 years) who underwent computed tomography chest, abdomen, and pelvis (CT CAP) scans using a Toshiba Aquilion Prime 160-slice CT scanner. Data included patient demographics, CT parameters (mA, tube rotation time, pitch, slice thickness, and slice count), and dose indices: dose length product (DLP), computed tomography dose index volume (CTDIvol), and effective dose. Cancer risks were calculated based on effective dose, patient demographics, and scan parameters. Results: This study demonstrated that the mean values for DLP, CTDIvol, and effective dose were 1719.64 ± 488.45 mGy·cm, 25.97 ± 6.96 mGy, and 27.5 ± 7.82 mSv, respectively. Cancer risk estimates ranged from 0.048% to 1.58%, with higher risks observed for females, younger patients. Significant correlations were found between dose indices and technical parameters, including pitch, kVp, tube rotation time, and slice thickness (p < 0.005). Conclusions: The mean values for DLP, CTDIvol, and effective dose for abdominopelvic scans were higher than those found in previous studies, with significant correlation of weight on these values. Optimizing CT protocols and establishing DRLs tailored to clinical indications are critical for minimizing radiation exposure and enhancing patient safety.

Objectives: To assess amide proton transfer weighted (APTw) MR imaging capabilities in differentiating high-grade glial tumors across alpha-thalassemia/mental retardation X-linked (ATRX) expression, tumor-suppressor protein p53 expression (p53), O6-methylguanine-DNA methyltransferase promoter (MGMTp) methylation, isocitrate dehydrogenase (IDH) status, and proliferation marker Ki-67 (Ki-67 index) as a preoperative diagnostic aid. Material & Methods: A total of 42 high-grade glioma WHO grade 4 (HGG) patients were evaluated prospectively (30 males and 12 females). All patients were examined using conventional MRI, including the following: T1w-MPRAGE pre- and post-contrast administration, conventional T2w and 3D FLAIR, and APTw imaging with a 3T MR scanner. Receiver operating characteristic (ROC) curves were calculated for the APTw% mean, median, and max signal for the different molecular biomarkers. A logistic regression model was constructed for combined mean and median APTw% signals for p53 expression. Results: The whole-tumor max APTw% signal could significantly differentiate MGMTp from non-MGMTp HGG, p = 0.035. A cutoff of 4.28% max APTw% signal yielded AUC (area under the curve) = 0.702, with 70.6% sensitivity and 66.7% specificity. The mean/median APTw% signals differed significantly in p53 normal versus p53-overexpressed HGG s: 1.81%/1.83% vs. 1.15%/1.18%, p = 0.002/0.006, respectively. Cutoffs of 1.25%/1.33% for the mean/median APTw% signals yielded AUCs of 0.786/0.757, sensitivities of 76.9%/76.9%, and specificities of 50%/66.2%, p = 0.002/0.006, respectively. A logistic regression model with a combined mean and median APTw% signal for p53 status yielded an AUC = 0.788 and 76.9% sensitivity and 66.2% specificity. ATRX-, IDH- wild type (wt) vs. mutation (mut), and the level of Ki-67 did not differ significantly, but trends were found: IDH-wt and low Ki-67 showed higher mean/median/max APTw% signals vs. IDH-mut and high Ki-67, respectively. ATRX-wt vs. mutation showed higher mean and median APTw% signals but lower max APTw% signal. Conclusions: APTw imaging can potentially be a useful marker for the stratification of p53 expression and MGMT status in high-grade glioma in the preoperative setting and potentially aid surgical decision-making.

Introduction: Diffusion-weighted imaging (DWI) is a non-invasive technique for acquiring liver pathology data and characterizing liver lesions. This modality shows promise for applications in the initial diagnosis and monitoring of liver diseases, providing valuable insights for clinical assessment and treatment strategies. Intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), and diffusion tensor imaging (DTI) are advanced forms of DWI. These techniques have proven effective for assessing liver lesions, including liver tumors and fibrosis. However, the results can be inconsistent. Thus, it is essential to summarize the current applications of these methods in liver fibrosis, identify existing limitations, and suggest future directions for development.

Methods: This review assessed studies concerning liver DWI and its applications published in the PubMed database over the last nine years. It presents these techniques' fundamental principles and key factors before discussing their application in liver fibrosis.

Results and conclusions: It has been observed that advanced DWI sequences remain unreliable in ensuring the robustness and reproducibility of measurements when assessing liver fibrosis grades, due to inconsistent results and significant overlap among these techniques across different stages of fibrotic conditions.

Aortic valve stenosis (AS) is a valvular heart disease that imposes a high afterload on the left ventricle (LV) due to restricted opening of the aortic valve, resulting in LV hypertrophy. Severe AS can lead to syncope, angina pectoris, and heart failure. The number of patients with AS has been increasing due to aging populations, the growing prevalence of lifestyle-related diseases, and advances in diagnostic technologies. Therefore, accurate diagnosis and appropriate treatment of AS are essential. In recent years, transcatheter aortic valve implantation (TAVI) has become feasible, and the number of procedures has rapidly increased, particularly among elderly patients. As treatment options for AS expand and diversify, detailed pre-procedural evaluation has become increasingly important. In particular, diagnostic imaging modalities such as computed tomography (CT) have advanced significantly, with notable improvements in image quality. With recent advancements in CT technology-such as increased detector rows, faster gantry rotation speeds, new image reconstruction methods, and the introduction of dual-energy imaging-the scope of cardiac assessment has expanded beyond the coronary arteries to include valves, myocardium, and the entire heart. This includes evaluating restricted AV opening and cardiac function using four-dimensional imaging, assessing AV annulus diameter and AS severity via calcium scoring with a novel motion correction algorithm, and detecting myocardial damage through late-phase contrast imaging using new reconstruction techniques. In cases of pre-TAVI evaluation or congenital bicuspid valves, CT is also valuable for assessing extracardiac structures, such as access routes and associated congenital heart anomalies. In addition, recent advancements in CT technology have made it possible to significantly reduce radiation exposure during cardiac imaging. CT has become an extremely useful tool for comprehensive cardiac evaluation in patients with aortic stenosis, especially those being considered for surgical treatment.

Background: Recent advances in single-photon emission computed tomography (SPECT) technology, particularly cadmium-zinc-telluride (CZT) detectors, have improved spatial resolution and contrast in cerebral blood flow imaging. This study aimed to investigate whether these improvements translate to enhanced diagnostic accuracy for Alzheimer's disease (AD). Methods: We compared conventional SPECT (eCAM) with CZT SPECT in 29 patients (mean age 60.9 ± 17.6 years, 69% female) with suspected neurodegenerative diseases. Results: Gray matter/white matter contrast was significantly higher in CZT SPECT compared to eCAM (1.615 ± 0.096 vs. 1.458 ± 0.068, p < 0.001). However, diagnostic accuracy for AD did not improve with CZT SPECT. For the participating psychiatrist, sensitivity decreased from 0.750 (eCAM) to 0.625 (CZT), while for the radiologist, specificity dropped from 0.571 (eCAM) to 0.429 (CZT). Overall accuracy slightly decreased for both readers. Conclusions: These findings suggest that while CZT SPECT offers superior image quality, it may not immediately translate to improved diagnostic accuracy for AD. The study highlights the importance of specialized training for clinicians in interpreting higher-resolution CZT SPECT images to fully leverage their potential in neurodegenerative disease diagnosis. Future research should focus on developing standardized training protocols and larger, multi-center studies to validate these findings.

Background: CT image guidance and navigation, although routinely used in complex endovascular procedures, is an unexplored territory in evolving vascular robotic procedures. In robotic surgery, it promises the better localization of vasculature, the optimization of port placement, less inadvertent tissue damage, and increased patient safety during the dissection of retroperitoneal structures. However, unknown tissue displacement resulting from induced pneumoperitoneum and positional changes compared to the preoperative CT scan can pose significant limitations to the reliability of image guidance. We aimed to study the displacement of retroperitoneal organs and vasculature due to factors such as increased intra-abdominal pressure (IAP) due to CO₂ insufflation and patient positioning (PP) using intraoperative CT imaging in a cadaveric model.

Methods: A thawed, fresh-frozen human cadaveric model was positioned according to simulated procedural workflows. Intra-arterial, contrast-enhanced CT scans were performed after the insertion of four laparoscopic ports in the abdomen. CT scans were performed with 0-5-15-25 mmHg IAPs in supine, left lateral decubitus, right lateral decubitus, Trendelenburg, and reverse Trendelenburg positions. Euclidean distances between fixed anatomical bony and retroperitoneal vascular landmarks were measured and compared across different CT scans.

Results: Comparing the effects of various IAPs to the baseline (zero IAP) in the same PP, an average displacement for retroperitoneal vascular landmarks ranged from 0.6 to 3.0 mm (SD 1.0-2.8 mm). When changing the PPs while maintaining the same IAP, the average displacement of the retroperitoneal vasculature ranged from 2.0 to 15.0 mm (SD 1.7-7.2 mm).

Conclusions: Our preliminary imaging findings from a single cadaveric model suggest minimal (~3 mm maximum) target vasculature displacement in the retroperitoneum due to elevated IAP in supine position and higher displacement due to changes in patient positioning. Similar imaging studies are needed to quantify procedural workflow-specific and anatomy-specific deformation, which would be invaluable in developing and validating advanced tissue deformation models, facilitating the routine applicability and usefulness of CT image guidance for target delineation during robotic vascular procedures.

Advances in breast cancer treatment have shifted the focus from maximizing local control to balancing oncologic efficacy with treatment de-escalation and toxicity reduction. Whole-breast irradiation (WBI) following breast-conserving surgery remains the standard of care, but with up to 90% of recurrences occurring near the tumor bed, partial breast irradiation (PBI) has emerged as a viable alternative. Large randomized controlled trials (such as IMPORT LOW, Florence, and GEC-ESTRO) have demonstrated comparable ipsilateral breast tumor recurrence (IBTR) rates between PBI and WBI, reinforcing its oncologic safety in well-selected patients. However, challenges remain in optimizing fractionation schedules, refining patient selection, and minimizing late toxicity. Recent innovations, including MRI-guided radiotherapy (MRgRT) and neoadjuvant PBI, offer improved tumor targeting, real-time plan adaptation, and enhanced normal tissue sparing. These advancements hold promise for further reducing radiation-related morbidity and improving cosmetic outcomes. As PBI progresses, integrating novel imaging modalities and hypofractionated regimens will be crucial to refining protocols. This review synthesizes the latest evidence on PBI techniques, clinical outcomes, and emerging technologies to guide future research and clinical decision-making in precision breast radiotherapy.

Background: Neonatal birth-related intracranial subdural hemorrhages (SDHs) represent a form of bleeding inside the skull that occurs in newborns. This condition includes the extravasation of blood both in the encephalic parenchyma and in the extra-axial spaces. Recent studies have shown that SDH and particularly post-traumatic birth-related hemorrhages represent a frequent occurrence, but they are often asymptomatic. The gold standard for the diagnosis and follow-up of patients with SDH is multiparametric Magnetic Resonance Imaging. The aim of this study is to describe our experience by reporting several cases of SDH with different distribution and Central Nervous System involvement by the MRI of this pathology in infants up to 30 days of age. Methods: We analyzed the age and sex of the patients included in this study, the localization of SDH in different CNS areas, and their frequency using distribution plots and pie charts. Results: About the analysis of the SDH locations in the 32 patients, the most common location was the cerebellum (31/32, 96.9%), followed by parietal and occipital lobes (19/32, 59.4%; 18/32, 56.2%, respectively), falx cerebri (11/32, 34.4%), tentorium cerebelli (10/32, 31.2%), temporal lobes (6/32, 18.7%), and finally cervical and dorsal spine in the same patients (4/32, 12.5%). According to SDH locations, the patients were divided into supratentorial, infratentorial, both, and Spinal Canal. Conclusions: Our study confirmed the literature data regarding the neonatal birth-related SDH high frequency, but also allowed us to focus our attention on the rarest spinal SDH localizations with the same benign evolution.

Objective: This study aimed to assess the diagnostic value of contrast-enhanced ultrasound (CEUS) time-intensity curve (TIC) parameters in detecting non-ossified thyroid cartilage invasion in patients with laryngeal squamous cell carcinoma (SCC). Methods: A CEUS TIC analysis was performed on 32 cases from 27 patients with histologically confirmed laryngeal SCC. The diagnostic performance of time to peak (TTP), peak intensity (PI), wash-in slope (WIS), area under the curve (AUC), and their quantitative differences (∆TTP, ∆PI, ∆WIS, and ∆AUC) to discriminate between the invaded and the non-invaded non-ossified thyroid cartilage was determined using ROC analysis. A logistic regression analysis was employed to identify significant predictors. Results: In an ROC analysis, of all TIC parameters analyzed separately, ∆TTP showed the greatest diagnostic performance (AUC: 0.85). A ∆TTP cut-off of ≤ 8.9 s differentiated between the invaded and the non-invaded non-ossified thyroid cartilage with a sensitivity of 100%, specificity of 76.9%, and accuracy of 81.3%. A combination of ∆TTP and PI increased the AUC to 0.93, specificity to 100%, and accuracy to 96.8%, but reduced the sensitivity to 83.3%. Meanwhile, the visual assessment of enhancement on CEUS to detect cartilage invasion had 83.3% sensitivity and 84.6% specificity. In a univariate logistic regression, only ∆TTP was a significant predictor of non-ossified thyroid cartilage invasion (OR: 0.80; 95% CI: 0.64-1.00). For every second increase in ∆TTP, the probability of thyroid cartilage invasion decreased by 20%. Conclusions: CEUS TIC parameters, particularly a combination of ∆TTP and PI, showed high diagnostic performance in the detection of non-ossified thyroid cartilage invasion in laryngeal SCC.

Background: According to the World Health Organization (WHO), approximately 5% of children and 2.5% of adults suffer from attention deficit hyperactivity disorder (ADHD). This disorder can have significant negative consequences on people's lives, particularly children. In recent years, methods based on artificial intelligence and neuroimaging techniques, such as MRI, have made significant progress, paving the way for development of more reliable diagnostic tools. In this proof of concept study, our aim was to investigate the potential utility of neuroimaging data and clinical information in combination with a deep learning-based analytical approach, more precisely, a novel feature extraction technique for the diagnosis of ADHD with high accuracy. Methods: Leveraging the ADHD200 dataset, which encompasses demographic information and anatomical MRI scans collected from a diverse ADHD population, our study focused on developing modern deep learning-based diagnostic models. The data preprocessing employed a pre-trained Visual Geometry Group16 (VGG16) network to extract two-dimensional (2D) feature maps from three-dimensional (3D) anatomical MRI data to reduce computational complexity and enhance diagnostic power. The inclusion of personal attributes, such as age, gender, intelligence quotient, and handedness, strengthens the diagnostic models. Four deep-learning architectures-convolutional neural network 2D (CNN2D), CNN1D, long short-term memory (LSTM), and gated recurrent units (GRU)-were employed for analysis of the MRI data, with and without the inclusion of clinical characteristics. Results: A 10-fold cross-validation test revealed that the LSTM model, which incorporated both MRI data and personal attributes, had the best diagnostic performance among all tested models in the diagnosis of ADHD with an accuracy of 0.86 and area under the receiver operating characteristic (ROC) curve (AUC) score of 0.90. Conclusions: Our findings demonstrate that the proposed approach of extracting 2D features from 3D MRI images and integrating these features with clinical characteristics may be useful in the diagnosis of ADHD with high accuracy.