Slice Thickness Research Articles

"Top-Down" Scission of Polymer into Target Chains with Tunable Molecular Weight via Ultramicrotome.

Molecular weight is a crucial characteristic of polymers which has a great influence on various polymer properties. Controlling molecular weight is a key aim in polymer research. Traditionally, chemical synthesis as a "bottom-up" approach is the most common method to tune polymer molecular weight. Alternatively, breaking polymer chains by mechanical forces (e.g., ultrasound, ball-mill grinding, and flow) is another pathway to adjust the molecular weight distribution. Herein, a new "top-down" approach employing ultramicrotome to cut the polymer chains to manipulate the polymer molecular weight is reported. By controlling the slice thickness and polymer swelling conditions, and the initial high molecular weight polymer chains can be cropped into fragment chains with designed molecular weight in a well-defined way. This work presents a new strategy to manipulate polymer molecular weight and will also provide a unique platform for further study of polymer mechanochemistry.

Syn2Real: synthesis of CT image ring artifacts for deep learning-based correction

Objective. We strive to overcome the challenges posed by ring artifacts in x-ray computed tomography (CT) by developing a novel approach for generating training data for deep learning-based methods. Training such networks require large, high quality, datasets that are often generated in the data domain, time-consuming and expensive. Our objective is to develop a technique for synthesizing realistic ring artifacts directly in the image domain, enabling scalable production of training data without relying on specific imaging system physics.Approach. We develop 'Syn2Real,' a computationally efficient pipeline that generates realistic ring artifacts directly in the image domain. To demonstrate the effectiveness of our approach, we train two versions of UNet, vanilla and a high capacity version with self-attention layers that we call UNetpp, withℓ2and perceptual losses, as well as a diffusion model, on energy-integrating CT images with and without these synthetic ring artifacts.Main Results.Despite being trained on conventional single-energy CT images, our models effectively correct ring artifacts across various monoenergetic images, at different energy levels and slice thicknesses, from a prototype photon-counting CT system. This generalizability validates the realism and versatility of our ring artifact generation process.Significance.Ring artifacts in x-ray CT pose a unique challenge to image quality and clinical utility. By focusing on data generation, our work provides a foundation for developing more robust and adaptable ring artifact correction methods for pre-clinical, clinical and other CT applications.

Imaging and Image Processing Techniques for High-Resolution Visualization of Connective Tissue with MRI: Application to Fascia, Aponeurosis, and Tendon

Recent interest in musculoskeletal connective tissues like tendons, aponeurosis, and deep fascia has led to a greater focus on in vivo medical imaging, particularly MRI. Given the rapid T2* decay of collagenous tissues, advanced ultra-short echo time (UTE) MRI sequences have proven useful in generating high-signal images of these tissues. To further these advances, we discuss the integration of UTE with Diffusion Tensor Imaging (DTI) and explore image processing techniques to enhance the localization, labeling, and modeling of connective tissues. These techniques are especially valuable for extracting features from thin tissues that may be difficult to distinguish. We present data from lower leg scans of 30 healthy subjects using a non-Cartesian MRI sequence to acquire axial 2D images to segment skeletal muscle and connective tissue. DTI helped differentiate aponeurosis from deep fascia by analyzing muscle fiber orientations. The dual echo imaging methods yielded high-resolution images of deep fascia, where in-plane spatial resolutions were between 0.3 × 0.3 mm to 0.5 × 0.5 mm with a slice thickness of 3–5 mm. Techniques such as K-Means clustering, FFT edge detection, and region-specific scaling were most effective in enhancing images of deep fascia, aponeurosis, and tendon to enable high-fidelity modeling of these tissues.

Intra-individual radiomic analysis of pericoronary adipose tissue: Photon-counting detector vs energy-integrating detector CT angiography.

The impact of novel photon-counting detector (PCD)-CT technology on in-vivo radiomics is not fully understood. This study aimed to compare the intra-individual stability and reproducibility of pericoronary adipose tissue (PCAT) radiomic features between PCD-CT and energy-integrating detector (EID)-CT in patients undergoing coronary CT angiography (CCTA) on both systems. Patients undergoing clinically indicated CCTA on an EID-CT were prospectively enrolled for research PCD-CCTA within 30days. Image acquisition parameters were standardized; PCD-CT datasets were reconstructed both down-sampled to 0.6mm to match the clinical scan (PCD-CTDS) and at 0.2mm ultrahigh-resolution mode (PCD-CTUHR). Automatic PCAT segmentation was performed; a total of 110 radiomic feature classes were extracted and compared across the three datasets (EID-CT, PCD-CTDS, and PCD-CDUHR). Feature stability was assessed using paired t-test filtered for false discoveries using Benjamini-Hochberg method, and reproducibility using intraclass correlation coefficient (ICC). A total of 42 patients (34 male [81.0%]; 67.9±7.6years) were included. Feature stability was 91% for EID-CT vs. PCD-CTDS, but decreased for UHR datasets (EID-CT vs. PCD-CTUHR: 55%; PCD-CTDS vs. PCD-CTUHR: 51%). However, inter-scanner reproducibility was poor in both comparisons (EID-CT vs. PCD-CTDS median ICC: 0.43 [0.03-0.69]; EID-CT vs. PCD-CTUHR: 0.29 [0.01-0.51]). Nevertheless, reproducibility improved within PCD-CT datasets (PCD-CTDS vs. PCD-CTUHR: 0.72 [0.48-0.83]), regardless of the difference in slice thickness. Most PCAT radiomic features remained stable between EID-CT and PCD-CTDS, although inter-scanner reproducibility was poor, emphasizing the significant impact of detector technology. Conversely, reproducibility of features within PCD-CT datasets showed more consistent results, even when comparing standard to UHR.

Diagnostic performance of dual-energy computed tomography (DECT) quantitative parameters for detecting metastatic cervical lymph nodes in patients with papillary thyroid cancer: A systematic review and meta-analysis.

This study systematically evaluated the diagnostic performance of dual-energy computed tomography (DECT) quantitative parameters in detecting cervical lymph node metastasis in patients with papillary thyroid cancer (PTC). We searched PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, and Wanfang Data databases for relevant original studies from database inception to March 2024. The quality of the included studies was evaluated using the QUADAS-2 tool. A bivariate random-effects model was used to calculate the pooled sensitivity and specificity of DECT. The threshold effect was determined by calculating Spearman correlation coefficients, meta-regression and subgroup analysis were performed to evaluate the sources of variability. Publication bias was assessed using the asymmetry of Deek's funnel plot. Thirteen studies involving 951 patients (2,782 lymph nodes) were included in this meta-analysis. We analyzed four quantitative parameters of DECT, among which the normalized iodine concentration (NIC) in the arterial phase had the highest area under the receiver operating characteristic curve (AUC). The combined sensitivity, specificity, and AUC were 83% (95% confidence interval [CI]: 76% - 89%), 90% (95% CI: 82% - 95%), and 0.92 (95% CI: 0.90 - 0.94), respectively. The Spearman correlation coefficient was-0.244 (p=0.4). Meta-regression and subgroup analysis revealed that use of blinding, mean patients' age, female proportion, presence of Hashimoto's thyroiditis, number of lymph nodes included in the study, and slice thickness were sources of heterogeneity for the NIC in the arterial phase. No significant publication bias was observed among the studies. DECT, a noninvasive technique, can be used to distinguish metastatic from nonmetastatic cervical lymph nodes in patients with PTC by measuring quantitative lymph node parameters.

Technical Note: An optimized protocol for standard unenhanced whole-body post-mortem Photon Counting CT imaging

In recent years, Photon-counting detector CT (PCD CT) has emerged as a new and groundbreaking technology in clinical radiology. While clinical research and practical applications of PCD-CT are constantly evolving, it has not yet been integrated into post-mortem CT (PMCT) imaging. Documented research into the potential applications of PCD CT in the field of post-mortem human forensic pathology and anatomical pathology is scarce in literature. This is despite the fact that PCD CT shows promise in expanding PMCT imaging diagnostic due to features such as ultra-high resolution and intrinsic spectral multienergy imaging. The authors have recently started scanning forensic corpses with a PCD CT to explore its possibilities and limits in the post-mortem field. In this technical note, the PCD CT acquisition and reconstruction parameters that resulted in excellent image quality in terms of noise and contrast for a slice thickness up to 0.2mm in unenhanced whole-body examinations are presented.

Robustness of radiomics within photon-counting detector CT: impact of acquisition and reconstruction factors.

To assess the impact of acquisition and reconstruction factors on the robustness of radiomics within photon-counting detector CT (PCD-CT). A phantom with twenty-eight texture materials was scanned with different acquisition and reconstruction factors including reposition, scan mode (standard vs high-pitch), tube voltage (120 kVp vs 140 kVp), slice thickness (1.0 mm vs 0.4 mm), radiation dose level (0.5 mGy, 1.0 mGy, 3.0 mGy, 5.0 mGy, vs 10.0 mGy), quantum iterative reconstruction level (0/4, 2/4, vs 4/4), and reconstruction kernel (Qr40, Qr44, vs Qr48). Thirteen sets of virtual monochromatic images at 70-keV were reconstructed. The regions of interest were drawn with rigid registrations. Ninety-three radiomics features were extracted from each material. The reproducibility of radiomics features was evaluated using the intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC). The variability of radiomics features was assessed by coefficient of variation (CV) and quartile coefficient of dispersion (QCD). The percentage of features with ICC > 0.90 and CCC > 0.90 were high when repositioned (88.2% and 88.2%) and tube voltage was changed (87.1% and 87.1%), but none of the features with ICC > 0.90 and CCC > 0.90 when high-pitch scan and different slice thickness were used. The percentage of features with CV < 10% and QCD < 10% were high when repositioned (47.3% and 68.8%) and tube voltage was changed (64.2% and 71.0%), but that with CV < 10% and QCD < 10% were low between standard and high-pitch scans (16.1% and 26.9%) and slice thickness (19.4% and 29.0%). The PCD-CT radiomics was robust to tube voltage, radiation dose, reconstruction strength level, and kernel, but brittle to high-pitch scan and slice thickness. Question The stability of radiomics features against acquisition and reconstruction factors within PCD-CT should be fully determined before academic research and clinical application. Findings The radiomics features are robust against tube voltage, radiation dose, reconstruction strength level, and kernel within PCD-CT but brittle to high-pitch scan and slice thickness. Clinical relevance The high-pitch scan and slice thickness that influence voxel size should be set with careful attention within PCD-CT, to allow a higher robustness of radiomics features before the implementation of radiomics analysis in clinical routine.

The potential of photon-counting CT for the improved precision of lung nodule radiomics

Objective.Lung nodule appearance may provide prognostic information, as the presence of spiculation increases the suspicion of a nodule being cancerous. Spiculations can be quantified using morphological radiomics features extracted from CT images. Radiomics features can be affected by the acquisition parameters and scanner technologies; thus, it is essential to identify imaging conditions that provide reliable measurements, particularly for emerging technologies like photon-counting CT (PCCT). This study aimed to systematically quantify the effect of imaging parameters on the radiomics measurements using a virtual imaging trial (VIT) platform, and further verify the findings with human clinical data.Approach.The VIT utilized nine virtual patients, each with three 6 mm nodules of varying spiculations. The virtual patients were run through a validated CT simulator (DukeSim) to acquire images at three dose levels (CTDIvol = 2.85, 5.69, and 11.38 mGy) with a clinical energy-integrating CT and a PCCT. The acquired projection images were reconstructed using multiple slice thicknesses, kernels, and matrix sizes. The reconstructed images were processed to extract morphological features using three segmentation methods. The features were clustered into three broad type categories. Features extracted from the acquired CT images were compared to their corresponding ground truth values, across all imaging conditions.Main results.Among all imaging conditions, slice thickness had the greatest effect on the radiomics measurements. When the thickest slices were used, the coefficient of variation increased by [1.19%-9.66%] in the energy integrating CT images, and [3.94%-24.43%] in the PCCT images. For both scanners, varying the kernel sharpness and dose affected the radiomics measurements insignificantly, while pixel size and segmentation method were observed to have stronger effects. Under varying imaging conditions, the trends and magnitude of radiomics features measurements were coherent with virtual trial results.Significance.The findings stress the importance of choosing optimal reconstruction settings for radiomics extraction to achieve precise feature quantifications.

Impact of Deep Learning 3D CT Super-Resolution on AI-Based Pulmonary Nodule Characterization

Background/Objectives: Correct pulmonary nodule volumetry and categorization is paramount for accurate diagnosis in lung cancer screening programs. CT scanners with slice thicknesses of multiple millimetres are still common worldwide, and slice thickness has an adverse effect on the accuracy of the pulmonary nodule volumetry. Methods: We propose a deep learning based super-resolution technique to generate thin-slice CT images from thick-slice CT images. Analysis of the lung nodule volumetry and categorization accuracy was performed using commercially available AI-based lung cancer screening software. Results: The accuracy of pulmonary nodule categorization increased from 72.7 percent to 94.5 percent when thick-slice CT images were converted to generated-thin-slice CT images. Conclusions: Applying the super-resolution-based slice generation on thick-slice CT images prior to automatic nodule evaluation significantly increases the accuracy of pulmonary nodule volumetry and corresponding pulmonary nodule category.

Optimizing CT Scan Parameters for Dry Archaeological Bones: A Qualitative Study as a First Step Towards Standardizing CT Acquisition Protocols

ABSTRACTEven though the use of CT scan examinations is often required in paleopathology, the method for performing a CT scan on archaeological dry bones has received little attention. Eight different CT acquisition parameters and positions on the CT table were evaluated using five healthy tibiae (including three immature bones), four healthy vertebrae (including three immature bones), and four pathological mature bones, all in a good state of preservation. The images obtained were blindly evaluated in a psychophysical and subjective manner by four evaluators with varying levels of experience in radiology. The evaluators preferred a tube voltage of 100 kV or less, or expressed no preference, in 90.4% of cases (p &lt; 0.001). For tube current, no preference was noted in 57.7% of cases (p &lt; 0.001), but when a preference was given, a value between 100 and 200 mAs was chosen in 95.5% of cases. The thinnest slices and centered positioning within the gantry, both vertically and laterally, were favored in 100% of cases (p &lt; 0.001). There was no preference for the size of the field of view in 42.3% of cases. The positioning of the bone in the headrest was preferred in 71.2% of cases (p &lt; 0.001), particularly for immature bones. Preferences regarding the elevation of the bone using a cardboard box were not significant (p = 0.07). We therefore recommend using a tube voltage of 80 kV, a tube current between 100 and 200 mAs, the thinnest possible slice thickness, and a field of view minimized according to the CT scanner's capabilities. Bones should be positioned in the headrest, perfectly centered both vertically and laterally within the gantry. However, these conclusions are based on a limited number of bones and types of bones, all in a good state of preservation, highlighting the need for further research.

THE EFFECT OF SLICE THICKNESS VARIATION ON SIGNAL TO NOISE RATIO (SNR) IN CT-SCAN THORAX EXAMINATION WITH CLINICAL TUMORS IN THE RADIOLOGY INSTALLATION

Slice thickness is the thickness of the slice on the image that is determined during reconstruction using Multiplanar Reconstruction (MPR). Choosing the right slice thickness according to the purpose of the examination will produce accurate diagnostic information. One of the parameters that determines the quality of the results of an image is the Signal to Noise Ratio (SNR). Signal to Noise Ratio (SNR) is the comparison between the amplitude of a signal and the amplitude of noise. Tumors are one type of pathology in the thorax caused by cells that divide and grow uncontrollably. The purpose of this study was to determine the effect of slice thickness variations on the Signal to Noise Ratio (SNR) on CT-Scan thorax at the Radiology Installation of Andalas University Hospital Padang and the highest SNR value. This study is a type of quantitative research with experimental methods, data analysis and testing. The slice thickness variations used in this study were 2 mm, 3 mm and 4 mm. The sample of this study was 3 patients. Each sample was performed ROI on tumor tissue, tumor border, healthy tissue and background. This study was conducted at the Radiology Installation of Andalas University Hospital, Padang from April to June 2024. The results showed that in this study (ρ Value

Breast ultrasound imaging systems performance evaluation using novel Contrast-Detail (C-D) and Anechoic-Target (A-T) phantoms.

C-D and A-T phantoms were imaged using a range of clinical breast ultrasound systems and imaging modes. A novel sensitive imaging performance metric, the Detectability Score (DS), was proposed which encompasses the Lesion Contrast to Noise Ratio (LCNR) weighted by the lesion depth and diameter. A geometry-based theoretical model comparing LCNR measured using spherical and cylindrical phantom anechoic/lesion targets was developed to investigate the influence of slice thickness on focal lesion detectability. LCNR and DS metrics derived from phantom image measurments were capable of differentiating the imaging performance of a range of ultrasound systems and advanced imaging modes, with the -2 dB contrast lesion targets offered as the most challenging to resolve. The geometry-based theoretical model, validated against phantom measurements, demonstrated the significant influence of slice thickness on focal lesion detectability, highlighting the need for increased availability of low contrast resolution spherical target phantoms for clinically realistic performance evaluation. The performance metrics coupled with the -1 dB contrast targets provide scope for evaluating future technological improvements in ultrasound systems. Given the high dependence of breast cancer care on high quality ultrasound imaging techniques, there is a need for evaluating imaging performance using clinically relevant test objects.

COMPUTED TOMOGRAPHIC ANGIOGRAPHY DATA SET CONTAINING ABDOMINAL AORTIC SEGMENTATION

BACKGROUND: Artificial Intelligence (AI) is widely actively in radiology. The effectiveness of AI algorithms essentially depends on the availability of relevant and representative training and test datasets. Currently, such datasets are highly demanded in open access, particularly CT angiographic (CTA) studies of the abdominal aorta containing not only pathology classification but also vessel segmentation. The disadvantages of existing solutions include small sample volume, narrow specialization, and disparate data preparation methodology. AIM – Design of a CTA dataset containing abdominal aortic segmentation for cases of normal, dilatation, thrombosis, and calcinosis. METHODS: In accordance with the methodology of AI-algorithms testing, the terms of reference for datasets preparation were developed, the necessary sample volume was calculated and approval of the independent ethical committee was obtained. Previously designed original algorithm of semi-automatic segmentation of abdominal aorta on CTA-studies using open access software Slicer 3D was used. Inclusion criteria: CTA studies, or abdominal CT studies with contrast enhancement; presence of arterial phase of the scan; slice thickness not more than 3 mm. Exclusion criteria: presence of any foreign objects in the aortic lumen, aortic dissection. The algorithm was tested on patient data obtained from the Unified Radiologic Information System. Expert evaluation of the compliance of the obtained results with the formed requirements, as well as the assessment of time costs when using the developed segmentation algorithm was carried out. RESULTS: The calculated sample size was 100 CTA studies with a slice thickness ≤ 1.2 mm. Population data: the number of unique patients was 100, the proportion of female patients was 51%; the median age was 62 years ranged from 18 to 84 years. The proportion of pathologic studies was 61%, of which (including combined pathology): 60 cases contained calcification, both by 18 cases with aortic dilatation and thrombosed lumen. Different non-overlapping masks were used for each object. The dataset is presented in the public domain. The average processing time is 0.8 hours per 100 CT-images. CONCLUSION: The public dataset containing 100 CTA studies of segmented abdominal aorta for normal, dilated, thrombotic and calcified cases was created. Results are valuable for AI-algorithms design and anthropomorphic 3D-modeling.

A Low-Field MRI Dataset For Spatiotemporal Analysis of Developing Brain

Recently, imaging investigation of brain development has increasingly captured the attention of researchers and clinicians in an attempt to understand the link between the brain and behavioral changes. Although high-field MR imaging of infants is feasible, the necessary customizations have limited its accessibility, affordability, and reproducibility. Low-field MR, as an emerging solution for scrutinizing developing brain, has exhibited its unique advantages in safety, portability, and cost-effectiveness. The presented low-field infant structural MR data aims to manifest the feasibility of using low-field MR image to exam brain structural changes during early life in infants. The dataset comprises 100 T2 weighed MR images from infants with in-plane resolution of ~0.85 mm and ~6 mm slice thickness. To demonstrate the potential utility, we conducted atlas-based whole brain segmentations and volumetric quantifications to analyze brain development features in first 10 week in postnatal life. This dataset addresses the scarcity of a large, extended-span infant brain dataset that restricts the further tracking of infant brain development trajectories and the development of routine low-field MR imaging pipelines.

Individual Differences in the Structure of the Pterygopalatine Fossa of the Adult Skull

The use of endoscopic microsurgical techniques in a number of surgical interventions on deep anatomical structures of the face requires detailed knowledge on the shape and individual variability of the size of the pterygopalatine fossa, containing vascular and nerve structures that provide blood supply and innervation of the upper face, including the pterygopalatine ganglion. The aim was to study individual differences in the shape and size of the pterygopalatine fossa of the adult human skull. Material and methods. The study included 62 archival series of anonymous CT scans (37 men and 25 women), performed with slice thickness of 0.5 mm. On axial and frontal scans, the X and Y coordinates were determined relative to the upper left corner of the scan of the opening of the greater palatine canal, which later serves as the zero point. On subsequent sections, a point with the coordinates of the opening of the greater palatine canal and the distance from this point to another point of interest along the X and Y axes were determined. The difference between the slice numbers multiplied by the thickness of the slice is the distance between two points along the Z axis. Based on the obtained coordinates, a 3- D image of the pterygopalatine fossa was constructed in the isometry system. On axial, frontal and sagittal scans, the width of the medial, anterior and posterior walls of the pterygopalatine fossa, its depth, height and other dimensions characterizing the relative location of the openings passing nerves were measured. The right and left sides of the scans, which had no pathology in this area, were examined. Results. It was stated that in the cavity of the pterygopalatine fossa, one should distinguish between the most bulk main (central) region, adjacent on the lateral side to the sphenopalatine foramen, and narrower regions which are directed downwards (vestibule of the greater palatine canal); backward (vestibule of the pterygoid canal); and laterally (vestibule of the pterygomaxillary fissure). New information has also been obtained characterizing the variability of the size of the pterygopalatine fossa. Conclusion. This study has been shown that the pterygopalatine fossa has a more complex shape than a narrow slit or pyramid, and the presence of the vestibule of the pterygoid canal in its cavity suggests a different position of the pterygoid ganglion in the pterygopalatine fossa and its external structure.

Biomechanics of flail chest injuries: tidal volume and respiratory work changes in multiple segmental rib fractures

BackgroundFlail chest (FC) injuries are segmental osseous injuries of the thorax that typically result from high-energy blunt trauma and regularly occur in multiple trauma (MT) patients. FC injuries are associated with paradoxical chest wall movements and, thus, have a high risk of respiratory insufficiency or even death. An increasing number of studies recommend an early surgical stabilization of FC injuries, but a definite trigger that would indicate surgery has, thus far, not been identified.MethodsBased on real-world injury computed tomography (CT) data, this study aimed to establish a finite elements (FE) model of a thorax simulating spontaneous breathing. The model is based on a 0.625 mm slice thickness CT data set. In this FE model, various FC injury patterns were implemented to examine the impact of an increasingly large flail segment on tidal volume and respiratory work. The impact of the segmental defect sizes on the outcome measures mentioned above was examined using correlation analyses.ResultsThe FE model in this study reliably simulated the spontaneous breathing patterns of an actively breathing patient in an uninjured setting as a reference and showed clinically realistic movements of the flail segments for various injury settings. Correlation analysis showed a significant negative correlation between the FC size and tidal volume (R2 = 0.852, p = 0.003), while absolute (R2 = 0.845, p = 0.0096) and relative loss (R2 = 0.844, p = 0.0096) of tidal volume concerning the intact model and the compensatory respiratory work required (R2 = 0.816, p = 0.0136) were positively correlated with FC size.ConclusionThis study presents an FE model of the thorax of a patient who presented to our clinic as an MT patient with an FC injury. The FE model fulfills physiologic active breathing patterns and simulates an FC injury’s paradoxical movement, realistically depicting clinical observations. The FE model showed that the number of consecutive ribs involved in the flail segment and the length of the flail segment significantly impacted active breathing concerning tidal volumes and respiratory work. With this, we have made the first step to define a trigger for surgery.

Characterization of jugular bulb position on computed tomography (CT) with implications for excision of vestibular schwannomas.

To describe the distribution of jugular bulb position and pneumatization of posterior lip of internal auditory meatus (IAM) in patients with vestibular schwannoma (VS). This retrospective study included 43 patients who had a thin slice (< 2mm) CT temporal bone for preoperative planning of retrosigmoid approach for excision of VS between March 2011 and March 2021. On computed tomography (CT), high riding jugular bulb was defined by its relationship to IAM and correlated with type of jugular bulb according to Manjila et al. classification. The most common position of the jugular bulb was type 2a on the side of the tumor (26/43, 60.5%) and contralateral to the side of the tumor (28/43, 65.1%). High riding jugular bulb was noted in 9 (20.9%) patients. Seven among the 9 (77.9%) patients with high riding jugular bulb had Manjila et al. type 4 jugular bulb. Pneumatization of posterior lip of IAM was noted in 8 (18.6%) patients. Avoidance of drilling of the IAM in the subgroup of 23 patients who underwent total excision of the tumor was significantly associated with Manjila et al. type 4 jugular bulb (3/4, 75%, p = 0.04) and pneumatization of posterior lip (3/4, 75%, p = 0.04). Ideally all patients with VS should undergo petrous bone CT of < 2mm slice thickness as it can help in qualifying the jugular bulb position and recognizing pneumatization of the IAM. The presence of Manjila et al. type 4 jugular bulb or pneumatization of the posterior lip in patients with VS should alert the surgeon to anticipate and prevent complications related to drilling the posterior lip of the IAM.

Finding Reproducible and Prognostic Radiomic Features in Variable Slice Thickness Contrast Enhanced CT of Colorectal Liver Metastases

Establishing the reproducibility of radiomic signatures is a critical step in the path to clinical adoption of quantitative imaging biomarkers; however, radiomic signatures must also be meaningfully related to an outcome of clinical importance to be of value for per- sonalized medicine. In this study, we analyze both the reproducibility and prognostic value of radiomic features extracted from the liver parenchyma and largest liver metastases in contrast enhanced CT scans of patients with colorectal liver metastases (CRLM). A prospective cohort of 81 patients from two major US cancer centers was used to establish the reproducibility of radiomic features extracted from images reconstructed with different slice thicknesses. A publicly available, single-center cohort of 197 preoperative scans from patients who underwent hepatic resection for treatment of CRLM was used to evaluate the prognostic value of features and models to predict overall survival. A standard set of 93 features was extracted from all images using pyradiomics, with a set of eight different extractor settings. Our results show that the feature extraction settings producing the most reproducible, as well as the most prognostically discriminative feature values are highly dependent on both the region of interest and the specific feature in question. While the best overall predictive model was produced using features extracted with a particular setting, without accounting for reproducibility, (C-index = 0.630 (0.603–0.649)) an equivalent-performing model (C-index = 0.629 (0.605–0.645)) was produced by pooling features from all extraction settings, and thresholding features with low reproducibility (CCC ≥ 0.85), prior to feature selection. Our findings support a data-driven approach to feature extraction and selection, preferring the inclusion of many features, and narrowing feature selection based on feature reproducibility when relevant reproducibility data is available. Further research is needed to determine how to select reproducible feature sets when reproducibility data is not available.

Predictive Modeling Is a Reliable Indicator in Determining Excessive Renal Mobility Single-Center Randomized Study.

Purpose: Excessive kidney mobility is an underestimating challenge for surgeons during retrograde intrarenal surgery (RIRS) and extracorporeal shock wave lithotripsy (ESL). There is no technique approved as a gold standard procedure for reducing excessive kidney mobility. The study aimed to uncover predictive factors for determining excessive renal mobility by utilizing clinicodemographic characteristics and noncontrast computed tomography (NCCT) data. Materials and Methods: The patients were categorized into two groups based on the presence of excessive renal mobility. Patients were scanned with a 16-channel, multislice NCCT, and images were captured utilizing a 16 × 1.25 mm collimation, 5 mm slice thickness. Many parameters including the origin angle of the renal artery, renal artery, vein length, diameter, the area and length of the psoas muscle, and perirenal and pararenal fatty tissue were measured on the images and analyzed. The data were analyzed using multivariate logistic regression, and the receiver operating characteristic curve model and we used predictive modeling based on three significant parameters. Results: Between May 2023 and May 2024, a total of 140 patients with and without excessive renal mobility enrolled into study. After multivariate analysis, increasing renal vein length and renal artery origin angle results in higher renal motility (odds ratio [OR]: 0.982; 95% confidence interval [CI]: 0.966-0.998; p = 0.030 and OR: 0.973; 95% CI: 0.948-0.999; p = 0.044; respectively). It also observed that an increase in tidal volume led to a reduction in renal mobility (OR: 1.015; 95% CI: 1.007-1.024; p = 0.001). Predictive modeling was designed based on these outcomes. This predictive modeling accurately estimates the presence of excessive renal mobility with improved 59% specificity and 65% sensitivity (p < 0.001, area under the curve 0.757; CI: 0.671-0.843). Conclusion: Physicians may predict the presence of excessive renal mobility via the predictive modeling mentioned in the current article. They may perform manipulations to reduce kidney mobility prior to ESL and RIRS.

AGE ESTIMATION USING STERNAL END OF CLAVICLE OSSIFICATION ON COMPUTED TOMOGRAPHY (CT SCAN): A POPULATION-BASED STUDY

Background: Age estimation plays a critical role in forensic and clinical medicine, particularly in legal and medico-legal contexts where determining chronological age is essential for criminal responsibility, immigration cases, and unidentified human remains. Skeletal maturation assessments using clavicular ossification have gained prominence due to their reliability beyond adolescence. The medial clavicular epiphysis is one of the last skeletal sites to fuse, making it a crucial anatomical structure for age estimation. Computed tomography (CT) imaging provides high-resolution assessment of ossification stages, reducing interpretative errors associated with conventional radiography. Objective: This study aimed to evaluate the correlation between medial clavicular ossification stages and chronological age using CT imaging and to develop regression models for age estimation in a defined population. Methods: A cross-sectional, population-based study was conducted at Hayatabad Medical Complex Peshawar and Khyber Girls Medical College Peshawar between January 2024 and July 2024. A total of 142 individuals (84 males, 58 females) aged 8–30 years were included. High-resolution CT scans with a slice thickness of 1–2 mm were used to assess the sternal end of the clavicle. Ossification stages were classified using a standardized five-stage system. Intra- and inter-examiner reliability was evaluated using the Kappa coefficient. Statistical analyses included t-tests, Spearman’s correlation, and multivariate logistic regression to predict chronological age based on clavicular ossification. Results: The mean age of participants was 21.46 ± 4.97 years. Intra-examiner and inter-examiner reliability assessments yielded Kappa values of 0.854 and 0.753, respectively. Developmental differences between right and left clavicles were not statistically significant in males (p = 0.08) or females (p = 0.41). Stage 1 ossification was observed as early as 8 years in females and 15–17 years in males. Stage 2 was present between 15 and 20 years in males and between 16 and 18 years in females. Stage 3 occurred within 15–23 years for both sexes. Stage 4 was noted from 19–30 years in females and 20–30 years in males. Complete fusion (Stage 5) appeared at 20–30 years in males and 22–30 years in females. Regression models demonstrated a high coefficient of determination (R² = 0.98), confirming the predictive accuracy of clavicular ossification for age estimation. Conclusion: CT imaging proved to be an effective tool for age estimation by providing precise visualization of clavicular ossification stages. The findings support the reliability of medial clavicular fusion as a forensic age marker, emphasizing the need for population-specific reference data. Future studies should incorporate larger sample sizes, particularly younger individuals, to further refine age estimation models for forensic and medico-legal applications.