Computed Tomography Imaging Research Articles

Anatomical Configuration of the MB2 Canal Using High-Resolution Cone-Beam Computed Tomography.

This study aimed to evaluate the anatomical configuration of the mesiobuccal (MB) root of the maxillary first molar and to assess the prevalence of the second mesiobuccal canal (MB2). A total of 307 high-resolution cone-beam computed tomography images of maxillary molars were analyzed. These images were classified based on the anatomical configuration and prevalence of the MB2 canal. An experienced evaluator examined the images by dynamically navigating through the entire tomographic volume, making necessary adjustments to the MB root in the axial, sagittal, and coronal planes along the canal trajectory. The anatomical configurations were classified according to Vertucci's classification. Overall, the prevalence of the MB2 canal within the sample was 90%. The most common anatomical configuration of the MB root was type IV (35%), followed by type VI (25%). MB roots with a single foramen were observed in 24% of the specimens, while 77% exhibited 2 foramina. No statistically significant differences were found between genders regarding prevalence and anatomical classifications (P < .05). The MB2 canal is highly prevalent, with the most common anatomical configuration being Vertucci's type IV, followed by type VI.

Anatomical investigation of safety determining factors for keyhole drilling trajectories for robotic cochlear implant surgery.

Cochlear implants (CI) are the most successful bioprosthesis in medicine probably due to the tonotopic anatomy of the auditory pathway and of course the brain plasticity. Correct placement of the CI arrays, respecting the inner ear anatomy are therefore important. The ideal trajectory to insert a cochlear implant array is defined by an entrance through the round window membrane and continues as long as possible parallel to the basal turn of the cochlea. Image-guided surgery can directly drill with a robotic arm through the mastoid and execute an exact drilling of this precalculated most ideal trajectory. Here, we aim to identify critical anatomical structures determining the safest keyhole drilling trajectory by comparing easy and difficult CI surgeries performed with the HEARO Procedure: a robotic tool for image-guided surgery. Cone-beam computed tomography images of patients who underwent robot-assisted cochlear implantation surgery (RACIS) were included. Three of 25 cases had to be converted to conventional surgery because of the current safety mitigations based on anatomical distance. Radiological images in DICOM format were transferred to dedicated software (OTOPLAN® Cascination GMHB Bern Switzerland) for analyses. Surgical segmentation and previously planned trajectories were analyzed for these 25 cases by comparing cochlear sizes, facial recess sizes, round window sizes, and trajectory angles. In addition, facial recess angle, and cochlear orientation angles were measured with RadiAnt DICOM Viewer (Medixant, Pozan, Poland). Facial recess size, facial recess angle, and distance between the facial nerve and safe trajectory were smaller in patient who converted from robotic surgery to conventional. A significant positive correlation existed between basal turn angle and in-plane angle (p = 0.001, r = 0.859). In addition, there was a significant negative correlation between the basal turn length and the last electrode insertion depth degree (p = 0.007, r = 0.545). In our robotic surgery cases, we demonstrate that the limiting factors of anatomical relationships are constituted by the dimensions of the facial recess and the cochlear orientation. The findings of this study are considered to be a reference for future studies in achieving collision-free trajectory planning in robotic-assisted cochlear implant surgery.

Multi-region nomogram for predicting central lymph node metastasis in papillary thyroid carcinoma using multimodal imaging: A multicenter study.

Central lymph node metastasis (CLNM) is associated with high recurrence rate and low survival in patients with papillary thyroid carcinoma (PTC). However, there is no satisfactory model to predict CLNM in PTC. This study aimed to integrate PTC deep learning feature based on ultrasound (US) images, fat radiomics features based on computed tomography (CT) images and clinical characteristics to construct a multimodal and multi-region nomogram (MMRN) for predicting the CLNM in PTC. We enrolled 661 patients diagnosed with PTC by thyroidectomy from two independent centers. Patients were divided into the primary cohort, internal test cohort (ITC), and external test cohort (ETC), and collected their US images and CT images. Resnet50 was employed to predict the CLNM status of PTC based on US images. Using radiomics feature extraction methods to extract fat radiomics features from CT images. Feature selection was conducted using the least absolute shrinkage and selection operator (LASSO) regression. The predictive performance of the MMRN was evaluated using five-fold cross-validation. We comprehensively evaluated the DLRCN and compared it with five radiologists. In the ITC and ETC, the area under the curves (AUCs) of MMRN were 0.829 (95 % CI: 0.822, 0.835) and 0.818 (95 % CI: 0.808, 0.828). The calibration curve revealed good predictive accuracy between the actual probability and predicted probability (P > 0.05). Decision curve analysis showed that the MMRN was clinically useful. Under equal specificity or sensitivity, the performance of MMRN increased by 6.5 % or 2.9 % compared to radiologist assessments. The incorporation of fat radiomics features led to significant net reclassification improvement (NRI) and integrated discrimination improvement (IDI) (NRI=0.174, P < 0.05, IDI=0.035, P < 0.05). The MMRN demonstrated good performance in predicting the CLNM status of PTC, which was comparable to radiologist assessments. The fat radiomics features exhibited supplementary value for predicting CLNM in PTC.

End-to-End CT Radiomics-Based Pipeline for Predicting Renal Interstitial Fibrosis Grade in CKD Patients.

Non-invasive assessment of renal fibrosis in patients with chronic kidney disease (CKD) remains a clinical challenge. This study aims to integrate radiomics and clinical factors to develop an end-to-end pipeline for predicting interstitial fibrosis (IF) in CKD patients. This retrospective study included 80 patients with CKD, with 53 patients in training set and 27 patients in test set. All patients underwent renal computed tomography (CT) scans and biopsy. Patients were classified into two groups based on their renal IF grade: mild-moderate and severe. Radiomics features were extracted from the automatically segmented right renal region on CT images, and univariate analysis along with multiple Least Absolute Shrinkage and Selection Operator (LASSO) was employed to construct the radiomics signature. Subsequently, logistic regression models were developed to create the radiomics model and the combined model. The predictive performance of both models was evaluated through discrimination, calibration, and decision curve analysis (DCA), and a nomogram was constructed for the model demonstrating superior performance. The combined model significantly outperformed the radiomics model, achieving a cross-validated AUC of 0.935±0.041 in the training set, compared to 0.804±0.024 for the radiomics model. In the test set, the combined model outperformed the radiomics model, with an AUC of 0.918 [95% CI 0.799-1] vs. 0.764 [95% CI 0.549-0.979], p=0.031 (DeLong test, Statistic: -2.152). Calibration curves and DCA indicated that the combined model demonstrated good calibration and better clinical net benefit. This end-to-end workflow could serve as a potential non-invasive tool to predict renal IF grade (mild-moderate vs. severe) in CKD patients.

G-UNETR++: A Gradient-Enhanced Network for Accurate and Robust Liver Segmentation from Computed Tomography Images

G-UNETR++: A Gradient-Enhanced Network for Accurate and Robust Liver Segmentation from Computed Tomography Images

Utility of Diaphragm Dome Height as a Marker of Operational Lung Volume Changes, Disease Burden and Exacerbations in Patients with Mild-to-Moderate COPD: An Observational Study Within the CanCOLD Cohort

BackgroundDynamic hyperinflation is central to dyspnoea, exercise limitation, and exacerbations in chronic obstructive pulmonary disease (COPD). While studied previously in moderate-severe COPD, the relevance of diaphragm dome height on clinically important outcomes has been under-investigated in mild-to-moderate COPD.MethodsCanadian Cohort Obstructive Lung Disease participants with spirometry-confirmed COPD, symptom-limited incremental cardiopulmonary exercise testing, and computed tomography image data were included. Base-to-apex left and right diaphragm dome height (DDH) was automatically segmented, with increased height implying less flattening and thus less hyperinflation. Dynamic hyperinflation was defined as ≥150 mL reduction in inspiratory capacity (IC) from rest to peak-exercise. Cross-sectional linear regression models were fitted between left and right DDH (predictor variables) with peak IC (ICpeak), peak workload (Wpeak), FEV1, and CAT score (outcome variables), and in longitudinal (Anderson-Gill) models with “symptom-based” and “event-based” exacerbations. Results are reported as parameter estimates or hazard ratios with 95%CIs per interquartile range dome height increment.ResultsAmong 304 participants (mean age 64.7±10.3, 41.8% female, 44.4% with mild COPD), each left and right DDH increment, respectively, was associated with ICpeak(0.21[0.13,0.29]L, 0.13[0.07,0.19]L), Wpeak(9.54[5.03,14.04]W, 6.04[2.45,9.62]W), FEV1(0.17[0.10,0.25]L, 0.08[0.02,0.14]L), and CAT score (−1.36[−2.39,−0.33], −0.82[−1.63,0.00]). Left DDH alone was associated with both symptom-based (HR: 0.82[0.74,0.91]) and event-based (0.83[0.73,0.95]) exacerbations. Of 167/304 participants with confirmed dynamic hyperinflation (ΔIC=−0.47±0.25 L), left DDH alone was associated with all outcomes (ICpeak, Wpeak, FEV1, CAT, and symptom-based/event-based exacerbations).ConclusionsLeft DDH appears to be a clinically important marker for operational lung volume changes, lung function, exercise performance, disease burden, and exacerbations in mild-to-moderate COPD.

A predictive clinical-radiomics nomogram for early diagnosis of mesenteric arterial embolism based on non-contrast CT and biomarkers.

Mesenteric artery embolism (MAE) is a relatively uncommon abdominal surgical emergency, but it can lead to catastrophic clinical outcomes if the diagnosis is delayed. This study aims to build a prediction model of clinical-radiomics nomogram for early diagnosis of MAE based on non-contrast computed tomography (CT) and biomarkers. In this retrospective study, a total of 364 patients confirmed as MAE (n = 131) or non-MAE (n = 233) who were randomly divided into a training cohort (70%) and a validation cohort (30%). In the training cohort, the minimum redundancy maximum relevance (mRMR) and the least absolute shrinkage and selection operator (LASSO) algorithms were used to select optimal radiomics features from non-contrast CT images for calculating Radscore which was utilized to establish the radiomics model. Logistic regression analysis was performed to screen clinical factors, and then generate the clinical model. A predictive nomogram model was built using Radscore and the selected clinical risk factors, which was evaluated through the receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA). Thirteen radiomics features were chosen to calculate Radscore. Age, white blood cell (WBC) count, creatine kinase (CK) and D-dimer were determined as the independent clinical factors. The clinical-radiomics nomogram model showed the best performance in training cohort. The nomogram model was with higher area under curve (AUC) value of 0.93, compared to radiomics model with AUC value of 0.90 or clinical model with AUC value of 0.78 in the validation cohort. The calibration curve showed that nomogram model achieved a good fit in both cohorts (P = 0.59 and 0.92, respectively). The DCA indicated that nomogram model was significantly favorable for clinical usefulness of MAE diagnosis. The nomogram provides an effective tool for the early diagnosis of MAE, which may play a crucial role in shortening the time for therapeutic decision-making, thereby reducing the risk of intestinal necrosis and death.

Serum Biomarkers of Pulmonary Damage and Risk for Progression of Rheumatoid Arthritis-Associated Interstitial Lung Disease.

To investigate baseline and change of pulmonary damage biomarkers (serum Krebs von den Lungen 6 [KL-6], human surfactant protein D [hSP-D], and matrix metalloproteinase 7 [MMP-7]) with rheumatoid arthritis-associated interstitial lung disease (RA-ILD) progression. In the Korean Rheumatoid Arthritis Interstitial Lung Disease (KORAIL) cohort, a prospective cohort, we enrolled patients with RA and ILD confirmed by chest computed tomography imaging and followed annually. ILD progression was defined as worsening in physiological and radiological domains of the 2022 American Thoracic Society, European Respiratory Society, Japanese Respiratory Society, and Latin American Thoracic Society guideline for progressive pulmonary fibrosis (PPF). Associations between biomarkers and RA-ILD progression were analyzed using multivariable Cox regression, adjusting for potential confounders. We analyzed 136 patients with RA-ILD (mean age 66.5 yrs, 30% male, 60.3% with usual interstitial pneumonia pattern). During a median 3.0 years of follow-up, 47 patients (34.6%) experienced progression. Higher baseline KL-6 and hSP-D levels were associated with higher risk of ILD progression (multivariable hazard ratios [HRs] 1.37 [95% CI 1.03-1.82] and 1.51 [95% CI 1.09-2.08], respectively), whereas only the highest quartile of MMP-7 showed an increased risk (multivariable HR 2.60 [95% CI 1.07-6.33]). Increasing levels of serum KL-6 at 1 year showed the strongest association with progression (ΔKL-6: multivariable HR 2.00 [95% CI 1.29-3.11]), additionally adjusting for baseline biomarker levels. In this first prospective study to apply PPF criteria to RA-ILD, 34.6% progressed over 3 years. Higher baseline KL-6 and hSP-D were associated with progression. In follow-up, greater change in KL-6 was associated with progression. Serial measurement of pulmonary damage biomarkers may predict RA-ILD progression and may be helpful in monitoring patients and treatment decisions.

3D Printing as an Aid in Acetabular Defects Compared to Established Diagnostics - a Survey.

The treatment of acetabular defects in revision arthroplasty is an increasing challenge. Different classifications have been introduced for preoperative planning to achieve the best possible result. 3D printing is a way to better visualize and understand these defects. The aim of this study was to facilitate classification, provide young doctors with a better understanding of complex defects, and ultimately improve preoperative planning and patient safety.The study was conducted at the 2022 BOUT congress, where health care professionals were provided with X-rays, a computed tomography (CT) scan, and a 3D print to classify acetabulums according to Paprosky and ADC. A questionnaire was administered to gather information on their familiarity with the classification systems and perception of 3D models in the clinic.The study involved 14 participants, mostly resident physicians, with some familiarity with the Paprosky and ADC classifications. The 3D printing method resulted in the highest rate of correct classifications for acetabular defects compared to X-ray and CT imaging. Participants found the 3D model useful for clinical applications and rated it higher than X-ray and CT imaging for classifying acetabular defects.Acetabular defects present a challenge in assessment, preoperative planning, and surgical management due to their complex anatomy. Overall, we were able to show that the use of a 3D model increases the accuracy in the classification of acetabular defects. The use of 3D printing in orthopedics and trauma surgery is showing more and more advantages and has opened up new methods for the education of medical students and young surgeons.

Radiomics and dosiomics approaches to estimate lung function after stereotactic body radiation therapy in patients with lung tumors.

Lung function assessment is essential for determining the optimal treatment strategy for radiation therapy in patients with lung tumors. This study aimed to develop radiomics and dosiomics approaches to estimate pulmonary function test (PFT) results in post-stereotactic body radiation therapy (SBRT). Sixty-four patients with lung tumors who underwent SBRT were included. Models were created to estimate the PFT results at 0-6months (Cohort 1) and 6-24months (Cohort 2) after SBRT. Radiomics and dosiomics features were extracted from the computed tomography (CT) images and dose distributions, respectively. To estimate the PFT results, Models A (dose-volume histogram [DVH] + radiomics features) and B (DVH + radiomics + dosiomics features) were created. In the PFT results, the forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) were estimated using each model, and the ratio of FEV1 to FVC (FEV1/FVC) was calculated. The Pearson's correlation coefficient (Pearson r) and area under the curve (AUC) for FEV1/FVC (< 70%) were calculated. The models were evaluated by comparing them with the conventional calculation formulae (Conventional). The Pearson r (FEV1/FVC) values were 0.30, 0.64, and 0.69 for Conventional and Models A and B (Cohort 2), respectively, and the AUC (FEV1/FVC < 70%) values were 0.63, 0.80, and 0.78, respectively. This study demonstrates the possibility of estimating lung function after SBRT using radiomics and dosiomics features based on planning CT images and dose distributions.

Tongue squamous cell carcinoma-targeting Au-HN-1 nanosystem for CT imaging and photothermal therapy

Tongue squamous cell carcinoma (TSCC) is a prevalent malignancy that afflicts the head and neck area and presents a high incidence of metastasis and invasion. Accurate diagnosis and effective treatment are essential for enhancing the quality of life and the survival rates of TSCC patients. The current treatment modalities for TSCC frequently suffer from a lack of specificity and efficacy. Nanoparticles with diagnostic and photothermal therapeutic properties may offer a new approach for the targeted therapy of TSCC. However, inadequate accumulation of photosensitizers at the tumor site diminishes the efficacy of photothermal therapy (PTT). This study modified gold nanodots (AuNDs) with the TSCC-targeting peptide HN-1 to improve the selectivity and therapeutic effects of PTT. The Au-HN-1 nanosystem effectively targeted the TSCC cells and was rapidly delivered to the tumor tissues compared to the AuNDs. The enhanced accumulation of photosensitizing agents at tumor sites achieved significant PTT effects in a mouse model of TSCC. Moreover, owing to its stable long-term fluorescence and high X-ray attenuation coefficient, the Au-HN-1 nanosystem can be used for fluorescence and computed tomography imaging of TSCC, rendering it useful for early tumor detection and accurate delineation of surgical margins. In conclusion, Au-HN-1 represents a promising nanomedicine for imaging-based diagnosis and targeted PTT of TSCC.

The Impact of Weighting Factors on Dual-Energy Computed Tomography Image Quality in Non-Contrast Head Examinations: Phantom and Patient Study.

Background: This study aims to evaluate the impact of various weighting factors (WFs) on the quality of weighted average (WA) dual-energy computed tomography (DECT) non-contrast brain images and to determine the optimal WF value. Because they simulate standard CT images, 0.4-WA reconstructions are routinely used. Methods: In the initial phase of the research, quantitative and qualitative analyses of WA DECT images of an anthropomorphic head phantom, utilizing WFs ranging from 0 to 1 in 0.1 increments, were conducted. Based on the phantom study findings, WFs of 0.4, 0.6, and 0.8 were chosen for patient analyses, which were identically carried out on 85 patients who underwent non-contrast head DECT. Three radiologists performed subjective phantom and patient analyses. Results: Quantitative phantom image analysis revealed the best gray-to-white matter contrast-to-noise ratio (CNR) at the highest WFs and minimal noise artifacts at the lowest WF values. However, the WA reconstructions were deemed non-diagnostic by all three readers. Two readers found 0.6-WA patient reconstructions significantly superior to 0.4-WA images (p < 0.001), while reader 1 found them to be equally good (p = 0.871). All readers agreed that 0.8-WA images exhibited the lowest image quality. Conclusions: In conclusion, 0.6-WA reconstructions demonstrated superior image quality over 0.4-WA and are recommended for routine non-contrast brain DECT.

Cardiac computer tomography-derived radiomics in assessing myocardial characteristics at the connection between the left atrial appendage and the left atrium in atrial fibrillation patients.

To evaluate the feasibility of utilizing cardiac computer tomography (CT) images for extracting the radiomic features of the myocardium at the junction between the left atrial appendage (LAA) and the left atrium (LA) in patients with atrial fibrillation (AF) and to evaluate its asscociation with the risk of AF. A retrospective analysis was conducted on 82 cases of AF and 56 cases in the control group who underwent cardiac CT at our hospital from May 2022 to May 2023, with recorded clinical information. The morphological parameters of the LAA were measured. A radiomics model, a clincal feature model and a model combining radiomics and clinical features were constructed. The radiomics model was built by extracting radiomic features of the myocardial tissue using Pyradiomics, and employing Least absolute shrinkage and selection operator (LASSO) method for feature selection, combining random forest with support vector machine (SVM) classifier. There were 82 cases in the AF group [44 males, 65.00 (59, 70)], and 56 cases in the control group (21 males, 61.09 ± 7.18). Age, BMI, hypertension, CHA2DS-VASC score, neutrophil to lymphocyte ratio (NLR), LAA volume, LA volume, the myocardial thickness at the junction of LAA and LA, the area, circumference, short diameter, and long diameter of the LAA opening, were significantly different between the AF group and the control group (P < 0.05). After conducting multivariate logistic regression analysis, it was found that BMI, the myocardial thickness at the junction of the LAA and the LA, LA volume, NLR and CHA2DS-VASC score were related to AF. 12 radiomics features of the myocardium at the junction of the LAA and the LA were extracted and identified. ROC curve analysis confirmed that the nomogram based on radiomics scores and clinical factors can effectively predict AF (AUC 0.869). Radiomics enables the extraction of the myocardial characteristics at the junction of the LAA and the LA, which are related with AF, facilitating the assessment of its relationship with the risk of AF. The combination of radiomics with clinical characteristics enhances the evaluation capabilities significantly.

Evaluation of a patient-specific 3D-printed guide for ventral slot surgery in dogs: An ex vivo study.

To evaluate the accuracy of ventral slot creation in canine cadavers with a three-dimensional (3D)-printed drill guide compared to the freehand technique. Ex vivo study. Eight canine cadavers (23.4-39.8 kg). Computed tomography (CT) data was used to create patient-specific 3D-printed surgical guides for ventral slot creation. Intervertebral sites were randomized to undergo either a guided (n = 12) or freehand (n = 12) ventral slot by a novice surgery resident. Postoperative CT images were used to compare ventral slot dimensions, shape, and position. Free-hand ventral slots were significantly shorter than the intended dimensions (p < .01). Dimensions of the guide-assisted ventral slots were not statistically different from the planned dimensions (p = .88, p = .72). Use of the guides resulted in improved accuracy for ventral slot positioning relative to midline and slot shape (difference in coefficient of variations, 32%, and 40%, respectively). Ventral slot dimensions were more accurate when created with the patient-specific 3D-printed guide compared to the freehand technique. Use of a 3D-printed patient specific surgical guide improves accuracy of ventral slot creation in canine cadavers and improves surgical precision when used by a single novice surgical resident. The results of this study support evaluation of the guides in small breed cadavers and live patients.

Correlation between axial and coronal common bile duct diameters in computed tomography: a retrospective study of 1064 patients

BackgroundThe measurement of the common bile duct (CBD) diameter is essential for evaluating bile duct pathologies. The axial plane of computed tomography (CT) images is the established method for CBD diameter measurement. However, modern software enables easy reconstruction of axial CT images into the coronal plane, allowing for CBD diameter measurement in this plane. This study aimed to investigate the correlation between measurements in the axial and coronal planes.ResultsThe three reviewers demonstrated fair reliability in measuring CBD diameter in axial and coronal planes, with intraclass correlation coefficients of 0.776 and 0.799, respectively. A positive correlation was observed between the two diameters (r = 0.943), with 88.9% of axial diameter variation explained by coronal diameter and approximately 0.29 + (0.94 × coronal diameter) (R2 = 0.889, p < 0.001). When a cutoff value of 7 mm was used to predict an abnormal axial diameter, the agreement between axial and coronal CBD diameters was substantial (Kappa = 0.715) with discordance between the two measurements identified in 6.2% of cases (66/1064) when a) coronal diameter < 7 mm but axial measurement ≥ 7 mm (39/1064; 3.7%) and b) coronal diameter ≥ 7 mm but axial measurement < 7 mm (27/1064; 2.5%). In univariable linear regression and multivariable analyses, the strongest independent factors associated with increased axial CBD diameter were presence of focal CBD lesion, age ≥ 60 years, and cholecystectomy.ConclusionThere was a strong positive correlation between axial and coronal CBD diameters with substantial agreement when using a 7-mm cutoff and fair reliability in their measurements.

Treatment of a collapse fracture of the anterolateral tibial plateau with a lateral locking plate and the Jail screw technique

BackgroundTo explore the advantages of a lateral tibial locking plate combined with Jail screw fixation in the treatment of anterolateral tibial plateau collapse fracture (ATPCF).MethodsA retrospective analysis was conducted on patients with ATPCFs admitted to our hospital from February 2019 to February 2023. Twenty-six patients were successfully included, including 15 males and 11 females, with an average age of 58.6 ± 7.8 years (range 45–68 years). All fractures were Schatzker type II fractures. After fracture reduction and fixation, a lateral locking titanium plate was placed through the anterolateral approach of the tibial plateau, and two screws of appropriate length were placed in the sagittal direction according to the Jail screw technique. Postoperative evaluation indices included surgery time, fracture healing time, the degree of tibial plateau collapse shown by computed tomography (CT) images at 3 days and 1 year after surgery, and the patient's knee range of motion at 1 year after surgery. The effects of fracture reduction and fixation before surgery, 3 days after surgery and 1 year after surgery were evaluated by the Rasmussen radiological score. The Hospital for Special Surgery (HSS) knee score was used to evaluate the knee joint function of patients at 1 year after surgery.ResultsThe average operation time was 64 ± 6.8 min (range 56–82 min). The fractures healed clinically at 13.8 ± 2.8 weeks (range 12–18 weeks) postoperation. After 15 ± 3.1 months (range 12–19 months) of average follow-up, all the patients were pain-free with a full range of motion and stable knees. At the 1-year postoperative assessment, the CT images showed no secondary collapse of the articular surface, the average knee range of motion was 136.3 ± 2.5° (range, -5° to 135°), the average Rasmussen radiological score was 16.2 ± 0.8 points, and the average HSS knee score was 93.6 ± 3.2 points.ConclusionsThe fixation of a anterolateral tibial plateau collapse fracture(ATPCF) using a lateral locking plate and the Jail screw technique has achieved good knee joint function, providing a new option for the treatment of ATPCFs. The clinical efficacy is satisfactory in the short term, avoiding secondary articular surface collapse.

Association of Increased CT-Attenuation of Visceral Adipose Tissue After Surgery with Poor Survival Outcomes in Patients with Stage II-III Gastric Cancer: A Retrospective Cohort Study.

This study aimed to investigate whether post-operative changes in the computed tomography (CT)-attenuation of subcutaneous (SAT) and visceral (VAT) adipose tissues were significantly associated with recurrence-free survival (RFS), peritoneal RFS, and overall survival (OS) in patients with stage II-III gastric cancer. This retrospective study analyzed 243 patients with stage II-III gastric cancer who underwent curative surgery. CT-attenuation values of SAT (SAT HU) and VAT (VAT HU) were measured from non-contrast-enhanced abdominopelvic CT images taken pre-operatively and 6 months post-operatively. Changes in SAT HU (ΔSAT HU) and VAT HU (ΔVAT HU) between the two CT scans were calculated. The prognostic value of these variables for predicting survival outcomes was assessed. Correlation analyses showed that both ΔSAT HU and ΔVAT HU were significantly positively correlated with T stage, TNM stage, and tumor size (p < 0.05). In the multivariate survival analysis, ΔVAT HU emerged as an independent significant predictor for RFS (p = 0.002, hazard ratio, 2.437), peritoneal RFS (p = 0.023, hazard ratio, 2.457), and OS (p = 0.043, hazard ratio, 2.204) after adjusting for age, sex, histopathological classification, T stage, and N stage. Patients with high ΔVAT HU had worse RFS, peritoneal RFS, and OS compared to those with low ΔVAT HU. Change in CT-attenuation of VAT following surgery was significantly correlated with tumor characteristics and was a significant predictor of RFS, peritoneal RFS, and OS in patients with stage II-III gastric cancer.

Artificial Intelligence for Cervical Spine Fracture Detection: A Systematic Review of Diagnostic Performance and Clinical Potential.

Systematic review. Artificial intelligence (AI) and deep learning (DL) models have recently emerged as tools to improve fracture detection, mainly through imaging modalities such as computed tomography (CT) and radiographs. This systematic review evaluates the diagnostic performance of AI and DL models in detecting cervical spine fractures and assesses their potential role in clinical practice. A systematic search of PubMed/Medline, Embase, Scopus, and Web of Science was conducted for studies published between January 2000 and July 2024. Studies that evaluated AI models for cervical spine fracture detection were included. Diagnostic performance metrics were extracted and included sensitivity, specificity, accuracy, and area under the curve. The PROBAST tool assessed bias, and PRISMA criteria were used for study selection and reporting. Eleven studies published between 2021 and 2024 were included in the review. AI models demonstrated variable performance, with sensitivity ranging from 54.9% to 100% and specificity from 72% to 98.6%. Models applied to CT imaging generally outperformed those applied to radiographs, with convolutional neural networks (CNN) and advanced architectures such as MobileNetV2 and Vision Transformer (ViT) achieving the highest accuracy. However, most studies lacked external validation, raising concerns about the generalizability of their findings. AI and DL models show significant potential in improving fracture detection, particularly in CT imaging. While these models offer high diagnostic accuracy, further validation and refinement are necessary before they can be widely integrated into clinical practice. AI should complement, rather than replace, human expertise in diagnostic workflows.

Neural Radiance Fields (NeRF) for 3D Reconstruction of Monocular Endoscopic Video in Sinus Surgery.

To validate the use of neural radiance fields (NeRF), a state-of-the-art computer vision technique, for rapid, high-fidelity 3-dimensional (3D) reconstruction in endoscopic sinus surgery (ESS). An experimental cadaveric pilot study. Academic medical center. Complete bilateral endoscopic sinus surgery was performed on 3 cadaveric specimens, followed by postsurgical nasal endoscopy using a 0° rigid endoscope. NeRF was utilized to generate 3D reconstructions from the monocular endoscopic video feed. Reconstructions were calibrated, scaled, and then co-registered to postoperative computed tomography (CT) image sets to assess accuracy. Reconstruction error was determined by comparing ethmoid sinus measurements on NeRF reconstructions and CT image sets. NeRF-based 3D scene reconstructions were successfully generated and co-registered to corresponding CT images for 5 out of 6 cadaveric nasal cavity sides. The mean reconstruction errors and standard error of the mean (SEM) for ethmoid length and height were 0.17 (SEM 0.59) and 0.70 (SEM 0.44) mm, respectively. NeRF demonstrates significant potential for dynamic, high-fidelity 3D surgical field reconstruction in ESS, offering submillimeter accuracy comparable to postoperative CT data in cadaveric specimens. This innovative approach may ultimately augment dynamic real-time intraoperative navigation through co-registration of the 3D reconstruction with preoperative imaging to potentially reduce the risk of injury to critical structures, optimize surgical completeness and, thereby, improve surgical outcomes. Further refinement and validation in live surgical settings are necessary to fully realize its clinical utility.

DIAGNOSTIC ACCURACY OF ULTRASOUND FOR RENAL TUMORS IN ADULTS TAKING CONTRAST ENHANCED COMPUTED TOMOGRAPHY AS GOLD STANDARD

Background: Renal cell carcinoma (RCC) accounts for the majority of renal malignancies in adults, with an increasing global incidence attributed to advances in diagnostic imaging and the growing prevalence of risk factors. Early and accurate detection of RCC is crucial for effective treatment and improved prognosis. Ultrasonography is widely used as a first-line diagnostic tool for renal tumors due to its accessibility, cost-effectiveness, and safety. However, its accuracy compared to computed tomography (CT), the gold standard for RCC diagnosis, remains an area of interest. Objective: To determine the diagnostic accuracy of ultrasonography in detecting renal tumors in adults, using contrast-enhanced computed tomography as the gold standard. Methods: This cross-sectional study included 188 participants recruited from the Urology, Nephrology, and Radiology departments of Allied Hospital Faisalabad. Patients with space-occupying lesions detected on grey-scale ultrasound were included, while those with impaired renal function or iodine contrast allergies were excluded. Ultrasound examinations were performed using an Ecostemylab 7 Doppler machine, and CT imaging was conducted with the Siemens CT Somatom Sensation 64 scanner. Patient demographic data, clinical history, and imaging findings were recorded. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall diagnostic accuracy were calculated using CT as the gold standard. Results: The mean age of participants was 49.95 ± 10.08 years, with 91.9% males and 8.1% females. Tumor sizes on ultrasound were &gt;4 cm in 3%, &gt;5 cm in 42.4%, and &gt;6 cm in 54.5%, while CT showed &gt;4 cm in 24.24%, &gt;5 cm in 52.2%, and &gt;6 cm in 23.23%. Ultrasound identified 26.3% benign and 73.7% malignant lesions, while CT identified 20.2% benign and 79.8% malignant lesions. Ultrasonography demonstrated a sensitivity of 87.34%, specificity of 80%, PPV of 94.52%, NPV of 61.54%, and overall diagnostic accuracy of 85.86%. Conclusion: Ultrasonography is a reliable first-line diagnostic tool for renal tumors, demonstrating high diagnostic accuracy. While it is cost-effective and safe, its limitations in specific subgroups necessitate confirmation with CT for comprehensive evaluation.