Axial Computed Tomography Images Research Articles

Endotracheal tube cuff position in relationship to the walls of the trachea: A retrospective computed tomography-based analysis

Background: The use of cuffed endotracheal tubes (ETTs) has become the standard of care in pediatric practice. The rationale for the use of a cuffed ETT is to minimize pressure around the cricoid while providing an effective airway seal. However, safe care requires that the cuff lie distal to the cricoid ring following endotracheal intubation. The current study demonstrates the capability of computed tomography (CT) imaging in identifying the position of the cuff of the ETT in intubated patients. Methods: The study included patients ranging in age from 1 month to 10 years who underwent neck and chest CT imaging that required general anesthesia and endotracheal intubation. The location of the ETT and of the cuff within the airway was determined from axial CT images at three levels (proximal, middle, and distal). Anatomical orientations were tabulated, and percent chances of each orientation were determined for the ETT and the cuff. Results: The study cohort included 42 patients ranging in age from 1 to 114 months. An ETT with a polyvinylchloride cuff was used in 24 patients, and an ETT with a polyurethane cuff was used in 18 patients. The ETT was located near the posterior wall of the trachea in approximately 24–38% of patients, being most likely to be centrally located at the proximal end and at its mid-portion. The middle part of the cuff was most likely to be positioned in the mid-portion of the trachea but tended to skew anteriorly at both the proximal and distal ends. Conclusion: This is the first study using CT imaging to identify the uniformity of cuff inflation within the trachea in children. With commonly used cuffed ETTs, cuff inflation and the final position of ETT cuff within the tracheal lumen were not uniform. Future investigations are needed to determine the reasons for this asymmetry and its clinical implications.

#400 A new notable compression source of left renal vein entrapment: the Right Renal Artery

Abstract Background and Aims Clinically, left renal vein (LRV) entrapment is almost equivalent to the nutcracker phenomenon (NCP). However, there is still much uncertainty and debate about the prevalence of NCP and its diagnostic criteria. As a particular type of LRV entrapment, the LRV compression by the right renal artery (RRA) was primarily reported as case reports. The study was designed to investigate the RRA-sourced LRV compression in two selected patient cohorts. Method The cross-sectional study consecutively selected 38 hospitalized kidney patients diagnosed with membranous nephropathy (Renal group) and 305 peripheral vascular inpatients or outpatients (Non-renal group) in the Second Affiliated Hospital of Harbin Medical University in China from November 2018 to March 2023. The patients with computed tomography (CT) of renal veins or abdominal aorta were included in both groups if axial CT imaging could visualize the renal vessels and was with regular and adequate layer thinness to perform multiplanar reconstruction analysis. Any potential situations that might cause positional or course changes in proximal RRA or LRV due to pathological reasons were excluded from the study. The CT data of LRV compression by different anatomical sources, including but not limited to RRA, was analyzed. Results With other anatomical compression sources excluded, there were 22.58% (7/31) and 20.00% (5/25) LRVs compressed by the RRAs in the Renal and Non-renal groups, respectively, with no significant difference (p = 1.0). The distal segments of the LRVs compressed by RRAs have a significantly larger lumen area than those of non-compressed veins (p < 0.01 in both groups). The overall incidence of NCP was calculated as 10.71% (6/56). Complex compressions, namely those LRV compressions by another adjacent structure besides RRA, coincided in 7.14% of the total cases (4/56). Conclusion Our study showed that it was not rare for the proximal RRA to compress the end of LRV. The detected incidence of RRA-sourced LRV compression was twice that of the entrapment related to the superior mesenteric artery, the mainstay of NCP. Though this finding came from two relatively small subject populations, it challenged the present connotation of LRV entrapment. Further repetitive studies are needed to test if such a phenomenon prevails in different populations, including healthy individuals. Legends for all figures: Green thick arrows, RRA; green arrowheads, superior mesenteric artery (SMA); red-edged white arrows, left renal artery (LRA); white short-shafted arrows, LRV; white long-shafted arrows, inferior vena cava (IVC); transparent or white arrowheads, compressed sites.

Investigation of Skull Cortical Thickness Changes in Healthy Population and Patients With Schizophrenia on Computed Tomography Images.

Cortical bone thickness is essential for the mechanical function of bone. Some factors including aging, sex, body size, hormone levels, behavior, and genetics lead to changes in cranial cortical robusticity. Moreover, the skull is one of the hardest and most durable structures in the human body. Schizophrenia is defined as a psychiatric disease characterized by delusions and hallucinations, and these patients have reduced brain volume; however, there is no study including cortical bone structure. For this reason, the aim of this study was to determine whether there is a difference in the skull cortical thickness of patients with schizophrenia and, compare it with healthy subjects. The cranial length, cranial width, anterior cortical thickness, right and left anterior cortical thickness, right and left lateral cortical thickness, right and left posterior lateral thickness, and posterior cortical thickness were measured with axial computed tomography images of 30 patients with schizophrenia and 132 healthy individuals aged between 18 and 69years. A statistically significant difference was found between the two groups in the measurements of right and left posterior lateral thickness, and posterior cortical thickness ( P = 0.006, P = 0.001, and P = 0.047, respectively). The sexes were compared, and it was found that the cranial width, anterior thickness, left anterior thickness, and right and left posterior thickness measurements of patients with schizophrenia showed a statistically significant difference compared with the control group ( P < 0.001, P = 0.003, P = 0.001, P < 0.001 and P < 0.001, respectively). The authors observed that skull cortical thickness may be different in schizophrenia. The results obtained from this study may be beneficial for evaluating these structures for clinical and pathological processes. Furthermore, knowledge about the skull cortical thickness in planning surgical procedures will increase the reliability and effectiveness of the surgical method, and this will minimize the risk of complications.

Deep Learning Prediction of Axillary Lymph Node Metastasis in Breast Cancer Patients Using Clinical Implication-Applied Preprocessed CT Images.

Background: Accurate detection of axillary lymph node (ALN) metastases in breast cancer is crucial for clinical staging and treatment planning. This study aims to develop a deep learning model using clinical implication-applied preprocessed computed tomography (CT) images to enhance the prediction of ALN metastasis in breast cancer patients. Methods: A total of 1128 axial CT images of ALN (538 malignant and 590 benign lymph nodes) were collected from 523 breast cancer patients who underwent preoperative CT scans between January 2012 and July 2022 at Hallym University Medical Center. To develop an optimal deep learning model for distinguishing metastatic ALN from benign ALN, a CT image preprocessing protocol with clinical implications and two different cropping methods (fixed size crop [FSC] method and adjustable square crop [ASC] method) were employed. The images were analyzed using three different convolutional neural network (CNN) architectures (ResNet, DenseNet, and EfficientNet). Ensemble methods involving and combining the selection of the two best-performing CNN architectures from each cropping method were applied to generate the final result. Results: For the two different cropping methods, DenseNet consistently outperformed ResNet and EfficientNet. The area under the receiver operating characteristic curve (AUROC) for DenseNet, using the FSC and ASC methods, was 0.934 and 0.939, respectively. The ensemble model, which combines the performance of the DenseNet121 architecture for both cropping methods, delivered outstanding results with an AUROC of 0.968, an accuracy of 0.938, a sensitivity of 0.980, and a specificity of 0.903. Furthermore, distinct trends observed in gradient-weighted class activation mapping images with the two cropping methods suggest that our deep learning model not only evaluates the lymph node itself, but also distinguishes subtler changes in lymph node margin and adjacent soft tissue, which often elude human interpretation. Conclusions: This research demonstrates the promising performance of a deep learning model in accurately detecting malignant ALNs in breast cancer patients using CT images. The integration of clinical considerations into image processing and the utilization of ensemble methods further improved diagnostic precision.

Percutaneous kyphoplasty through unilateral puncture on the convex side for the treatment of painful osteoporotic vertebral compression fracture with scoliosis

PurposeTo assess the clinical safety, accuracy, and efficacy of percutaneous kyphoplasty (PKP) surgery using an enhanced method of unilateral puncture on the convex side for the treatment of painful osteoporotic vertebral compression fractures (P-OVCF) with scoliosis.MethodsClinical and radiographic data of P-OVCF patients with scoliosis who underwent PKP via unilateral puncture on the convex side from January 2018 to December 2021 were retrospectively analyzed. This technique’s detailed surgical steps and tips were described. The local kyphosis angle (LKA), scoliosis Cobb angle (SCA), and local scoliosis Cobb angle (LSCA) were measured using X-ray and compared at pre-operation, post-operation, and the last follow-up. The width of pedicle (POW), inner inclination angle (IIA), lateral distance (LD), and puncture course length (PCL) were measured on the axial computed tomography image and compared between two sides. Postoperative computed tomography was employed to evaluate the condition of cement distribution and puncture. Clinical outcomes were evaluated using the Oswestry Disability Index (ODI) and Visual Analog Scale (VAS) for back pain (BP).ResultsThirty-six patients, 23 women and 13 men, with an average age of 76.31 ± 6.28 years were monitored for 17.69 ± 4.70 months. The median surgical duration of single vertebrae was 35 min. The volume of bone cement for single vertebrae was 3.81 ± 0.87 ml and the proportion of sufficient cement distribution of the patients was 97.22. LKA was considerably improved from pre-operation to post-operation and sustained at the last follow-up. SCA and LSCA were not significantly modified between these three-time points. IIA, PCL, and LD were lower on the convex side than on the concave side. POW was considerably wider on the convex side. The ODI and VAS-BP scores were significantly improved after surgery and sustained during the follow-up.ConclusionsCombining with the proper assessment of the pre-injured life status of patients, PKP surgery using unilateral puncture on the convex side for the treatment of P-OVCF with scoliosis can achieve safe, excellent clinical, and radiographic outcomes.

An Evaluation of Renal Sinus Fat Accumulation Using the Anteroposterior Diameter of the Renal Sinus on a Computed Tomography Axial Image.

Backgrounds and objectives Renal sinus fat (RSF) is an indicator of obesity-related complications. However, the measurement and imaging process are complicated. For a simple measurement of RSF, we focused on the kidney's shape change caused by RSF accumulation. Thus, this study aimed to investigate whether the anteroposterior diameter of the renal sinus (APDRS) on a computed tomography (CT) axial image is useful for evaluating RSF accumulation. Materials and methods The correlation between APDRS and RSF was investigated in 98 outpatients who underwent abdominal CT. In addition, the correlation between APDRS or RSF and obesity indicators (estimated glomerular filtration rate from serum creatinine levels (eGFRcreat), body mass index (BMI), and visceral adipose tissue (VAT)) was also investigated. We classified patients based on the presence or absence of at least one underlying disease (chronic kidney disease (CKD), cardiovascular diseases (CVD), hypertension, and type 2 diabetes (T2D)) and investigated significant differences between the two groups at APDRS and RSF. The intraclass correlation coefficient (ICC) was also calculated for APDRS. Results There was a strong positive correlation between RSF and APDRS (r = 0.802, P < 0.01). The obesity indicators (eGFRcreat, BMI, and VAT) were correlated with RSF and APDRS (P < 0.01). Out of 98 outpatients, 48 had at least one underlying disease. There were statistically significant differences in APDRS and RSF between the patients with and without at least one of the underlying diseases caused by obesity (P < 0.01). The inter-reader ICC for the measurement of the APDRS was 0.98. Conclusions APDRS on a CT axial image may be useful for the evaluation of RSF accumulation.

Abdominal Arterial Translation in Lower Lumbar Spine Level Due to Positional Change: A Clinical Survey Using Intraoperative Computed Tomography.

Background: Abdominal vascular injury, a fatal complication of lumbar disc surgery, should concern spine surgeons. This study aimed to compare the position of the abdominal arteries in the supine and prone positions and the factors involved. Thirty patients who underwent lumbar surgery by posterior approach were included. Methods: All patients underwent computed tomography (CT) preoperatively in the supine position and intraoperatively in the prone position. In the CT axial image, at the L4, L4/5 disc, L5, and L5/S1 disc level, we measured the shortest distance between the abdominal arteries and the vertebral body (SDA: shortest distance to the aorta), and the amount of abdominal arterial translation, defined as "SDA on intraoperative CT" minus "SDA on preoperative CT". Additionally, the preoperative CT axial images were evaluated for the presence of aortic calcification. Results: No significant difference in SDA values based on patients' positions was observed at each level. In males, the supine position brought the abdominal artery significantly closer to the spine at the left side of the L5/S level (p = 0.037), and, in cases of calcification of the abdominal artery, the abdominal artery was found to be closer to the spine at the left side of the L4/5 level (p = 0.026). Conclusions: It is important to confirm preoperative images correctly to prevent great vessel injuries in lumbar spine surgery using a posterior approach.

Racial differences in body composition and survival among older adults with gastrointestinal malignancies

IntroductionMuscle and adipose tissue measures can be quantified from routinely obtained computed tomography (CT) images and are predictors of chemotherapy-related toxicities and survival among patients with gastrointestinal (GI) malignancies. Most studies to date have consisted of predominantly White patients, and the role of body composition among minoritized racial groups is unknown. We examined racial differences in body composition and survival among patients with GI malignancies. Materials and MethodsThis was a prospective cohort study of patients with GI malignancies. Single slices of axial CT images from L3 segments were analyzed using Slice-O-Matic software. The skeletal muscle area (cm2) was divided by height to obtain the skeletal muscle index (SMI, cm2/m2). Skeletal muscle radiodensity (SMD) in Hounsfield units (HU) was used for muscle composition. We compared body composition parameters between non-Hispanic (NH)-White and NH-Black participants. Cox models were used to examine the impact of body composition on survival. We proposed new race-specific cutoffs for body composition using optimal stratification. ResultsFive hundred forty patients were included, of which 24% were NH-Black. In Cox models stratified by race, each 5 cm2/m2 decrease in SMI was associated with increase in risk of all-cause mortality in NH-Black patients (hazard ratio [HR] 1.25; 95% confidence interval [CI] 1.04–1.49 p = 0.02). With the existing cut points, neither sarcopenia nor myosteatosis was associated with worse survival. Using a new cutoff for sarcopenia in NH-Black patients, NH-Black patients with sarcopenia (HR 2.31 95%CI 1.10–4.88 p = 0.03) and myosteatosis (HR 2.63 95% CI 1.25–5.53 p = 0.01) had worse survival. DiscussionNH-Black older patients with GI cancers and sarcopenia or myosteatosis have worse overall survival.

Body composition measurements and clinical outcomes in patients with resectable pancreatic adenocarcinoma – analysis from SWOG S1505

Sarcopenic obesity and muscle attenuation have been associated with survival in patients with borderline resectable and advanced pancreatic ductal adenocarcinoma (PDA); however, these relationships are unknown for patients with resectable PDA. This study examined the associations between skeletal muscle and adipose tissue as measured on baseline computed tomography (CT) and the overall survival (OS) of participants with resectable PDA in a secondary analysis of the Southwest Oncology Group S1505 clinical trial (identifier: NCT02562716). The S1505 phase II clinical trial enrolled patients with resectable PDA who were randomized to receive modified FOLFIRINOX or gemcitabine and nab-paclitaxel as perioperative chemotherapy, followed by surgical resection. Baseline axial CT images at the L3 level were analyzed with externally validated software, and measurements were recorded for skeletal muscle area and skeletal muscle density, visceral adipose tissue area (VATA) and density, and subcutaneous adipose tissue area and density. The relationships between CT metrics and OS were analyzed using Cox regression models, with adjustment for baseline participant characteristics. Of 98 eligible participants with available baseline abdominal CT, 8 were excluded because of imaging quality (eg, orthopedic hardware), resulting in 90 evaluable cases: 51 men (57.0%; mean age, 63.2 years [SD, 8.5]; mean body mass index [BMI], 29.3kg/m2 [SD, 6.4]), 80 White (89.0%), 6 Black (7.0%), and 4 unknown race (4.0%). Sarcopenia was present in 32 participants (35.9%), and sarcopenic obesity was present in 10 participants (11.2%). Univariable analyses for the 6 variables of interest indicated that the standardized mean difference (hazard ratio [HR], 0.75; 95% CI, 0.57-0.98; P=.04) was statistically significantly associated with OS. In models adjusted for sex, race, age, BMI, performance score, contrast use, sarcopenia, and sarcopenic obesity, VATA was statistically significantly associated with OS (HR, 1.58; 95% CI, 1.00-2.51; P=.05). No difference was observed in OS between participants according to sarcopenic obesity or sarcopenia categories. The median OS estimates were 25.1 months for participants without sarcopenic obesity, 18.6 months for participants with sarcopenic obesity, 23.6 months for participants without sarcopenia, and 27.9 months for participants with sarcopenia. This was the first study to systematically evaluate body composition parameters in a prospective multicenter trial of patients with resectable PDA who received perioperative chemotherapy. Visceral adipose tissue was associated with survival; however, there was no association between OS and sarcopenia or sarcopenic obesity. Further studies should evaluate these findings in more detail.

Development of a Novel Artificial Intelligence Tool to Measure Psoas Volumes in Patients with Diffuse Large B Cell Lymphoma

Introduction Sarcopenia is associated with poor outcomes in cancer patients. However, it is poorly defined, and its clinical assessment can be tedious. Studies have shown psoas muscle volume (PV), measured on computed tomography (CT) scans, correlate with validated measures of frailty and clinical outcomes (Yamada Y., et al. 2023), with better predictive value than another frequently used radiological surrogate - the psoas muscle area measured on a single axial cut at the L3 vertebral level. The labor-intensive nature of PV measurement, lack of validated reference ranges, and inter-observer variability has limited its adoption as a marker of sarcopenia. We hence aim to investigate if an artificial intelligence (AI) model can be developed and trained to automate the measurement of PV in patients with diffuse large B cell lymphoma (DLBCL). Methods This was a retrospective cohort study. Consecutive patients with DLBCL treated at our center from 2010 to 2018 were included. For inclusion, patients had to have at least one contrast-enhanced CT scan performed after diagnosis. Patients who only had positron electron tomography (PET) scans were excluded. The CT scan temporally closest to diagnosis was selected for segmentation. Manual full PV segmentation (Figure 1) was performed on axial CT images using a cloud-based annotation tool (https://darwin.v7labs.com/) by two radiologists, encompassing the entire muscle from origin to insertion. The segmentation data from the first 10 patients (650 images) were then used to train an AI model (Ultralytics YOLOv8) to automatically segment the psoas muscles (Figure 1). Segmented psoas muscles on CT imaging were converted to volume measurements using a code. This was calculated for every patient using the metadata of pixel area and slice thickness contained within each unique CT image. Muscle volumes for the entire patient cohort were generated using this machine learning model and correlated with patient age, height, weight, body mass index (BMI), lean body weight (LBW) (Janmahasatian S., et al. 2005) and body surface area (BSA) determined by the Mosteller formula. Correlation was determined using Pearson's correlation coefficient. Results Data from 123 patients were available for analysis. The median age was 62 years (IQR 53.0 - 70.0), with 89 (72.4%) males. 83 (67.5%) patients were Chinese and 27 (22.0%) were Malay. 111 (90.2%) patients had an Eastern Cooperative Oncology Group (ECOG) performance status of ≤1, and 9 (7.3%) patients had a body mass index (BMI) &amp;lt;18kg/m 2. The median weight was 62.6kg (IQR 54.1 - 72.8), median BMI 23.5kg/m 2 (IQR 20.8 - 26.1), median LBW 48.5kg (IQR 40.2 - 54.3) and median BSA 1.69m 2 (IQR 1.53 - 1.83). 7 (7.4%), 18 (19.1%), 8 (8.5%) and 61 (64.9%) patients were stages 1, 2, 3 and 4 at diagnosis, respectively. 56 (45.6%) of patients had an International Prognostic Index (IPI) of ≥3. Psoas volumes for our population were successfully generated using our deep learning model. The model was able to accurately identify the psoas muscle and distinguish it from other intra-abdominal and intra-pelvic tissue, across a range of body and psoas muscle sizes. It was also able to distinguish the psoas from the iliacus within the pelvis. The median PV was 158.27ml (IQR 105.10 -190.71). There were positive correlations between PV and all physical measures analyzed including height (r = 0.60, p &amp;lt; 0.001), weight (r = 0.47, p &amp;lt; 0.001), BMI (r = 0.28, p 0.002), LBW (r = 0.66, p &amp;lt; 0.001), and BSA (r = 0.55, p = &amp;lt;0.001), and a negative correlation between PV and age (r = -0.22, p = 0.015). Conclusion We have developed a novel AI tool that can identify and distinguish the psoas muscle from other tissue on CT scans. The volumes measured by our AI correlate, as expected, positively with all physical indices analyzed, and negatively with age. Further work is required to determine the accuracy and quantify the efficiency of the AI model compared with trained radiologists, as well as to assess if AI-measured PV changes temporally or predicts clinical outcome.

Metaphyseal Fracture Displacement is Predictive of Intra-articular Diastasis in Adolescent Triplane Ankle Fractures.

Triplane fractures are rare enough that large homogeneous series to support management decisions are lacking. During initial evaluation, the addition of computed tomography (CT) to conventional X-rays (XR) does not always alter the patient's clinical course. Therefore, routine use of CT is controversial. This study aims to: (1) clarify quantitative relationships between articular displacement measured on XR versus CT and (2) identify whether metaphyseal displacement on the lateral XR predicts clinically relevant articular displacement on a CT scan. A 10-year retrospective review of consecutive triplane fractures was performed at a level 1 pediatric trauma center. Maximum articular and metaphyseal displacement were recorded from XR and CT. Quantitative relationships between XR and CT measurements were compared among imaging modalities and radiographically operative versus nonoperative fractures. Eighty-seven patients met the inclusion criteria. XR underestimated articular displacement by 229% in the sagittal plane (1 mm on XR vs 3.3 mm on CT; P < 0.05) and 17% in the coronal plane (2.3 mm on XR vs 2.7 mm on CT; P < 0.05). XR underestimated articular step-off by 184% in the coronal plane and 177% in the sagittal plane ( P < 0.05). CT measurements more often differentiated patients who did or did not undergo surgery at our institution. Metaphyseal displacement was significantly higher in patients with traditionally operative articular displacement (≥2.5 mm on CT) versus those with articular displacement below traditionally operative thresholds (2.4 vs 0.9 mm, P = 0.001). Sixty patients had metaphyseal displacement >1 mm on the lateral XR, of whom 56 had surgical-magnitude articular displacement (≥2.5 mm) on CT (positive predictive value = 94%). Conventional radiographs underestimate the true articular displacement of triplane fractures. Surgical-magnitude articular step-off is rare, and the largest articular gap is usually visualized on the axial CT image. Metaphyseal displacement >1 mm, which is easily measured on a lateral XR, is strongly predictive of clinically relevant articular displacement on CT. This radiographic finding should prompt advanced imaging before proceeding with nonoperative management. Level III.

Morphological Analysis of Intraarticular Fragments in AO/OTA 44 Category Posterior Malleolar Fractures

Category: Ankle; Trauma Introduction/Purpose: Intraarticular fragments (IAFs) associated with posterior malleolar fractures are a major obstacle in the treatment of ankle fractures. However, their frequency, location, and morphology, as well as their relationship with the classification of ankle posterior malleolar fractures, are poorly understood and unresolved. The Purpose of this study is to clarify the frequency and morphology of IAFs in posterior malleolar ankle fractures. Methods: This study was conducted at a single institution and included 104 consecutive patients with trimalleolar ankle fractures treated between 2015 and 2022. The inclusion criteria were 1) acute fracture within 2 weeks after injury and 2) cases with computed tomography (CT) images at the time of injury. The exclusion criteria were 1) previous ipsilateral ankle fracture, 2) pathological fracture, and 3) younger age with open physis. CT images at the time of injury were reviewed and each posterior malleolar fracture was classified using the Mason classification. Frequency of occurrence, size (long diameter × short diameter), and angle (the angle between the long diameter and fracture surface of the posterior malleolar fracture) of the IAF. The location of the IAF was described from CT axial images The dislocated distance of the IAF from the articular surface was measured on the sagittal CT view. Results: The patient’s mean age was 54.6 years. 46 cases were Type 1, 32 cases were Type 2A, 9 cases were Type 2B, and 17 cases were Type 3 according to the Mason’s classification. In Mason Type 2 and 3 cases, the IAF was present in 32 (78.0%) and 12 (70.6%) cases, respectively. The IAF was more frequently observed laterally in type 2 (22 cases) and medially in type 3 (7 cases). The long × short diameter of the IAF averaged 11.2 × 4.9 mm and 9.0 × 3.7 mm for Types 2 and 3, respectively. The angle of IAF was 10.5 ± 13.4° and 8.5 ± 7.8°, the distance of displacement was 3.0 ± 2.6 mm and 2.4 ± 1.2 mm, respectively. Conclusion: This study revealed a high incidence of IAFs in posterior malleolar ankle fractures. The IAF has a long medial to lateral shape, as well as the direction of the posterior malleolus fracture, occurs more often laterally in Mason Type 2 and medially in type 3. These findings suggest a pathophysiology in which the axial force causes secondary intraarticular impingement after the main fracture of the posterior malleolus. resulting in the development of an IAF. Handling IAFs is one of the keys in the treatment of posterior malleolar fractures and the surgical approach should be also selected based on the IAF.

Quantitative Analysis of Lumbar Disc Bulging in Patients with Lumbar Spinal Stenosis: Implication for Surgical Outcomes of Decompression Surgery.

This study aimed to quantitatively assess disc bulging using computed tomography (CT) in patients with lumbar spinal stenosis (LSS) and to examine whether disc bulging affects the surgical outcomes of patients with LSS after posterior decompression surgery. Sixty-three patients who underwent posterior decompression surgery for LSS were included. The extent of disc bulging was evaluated as the percentage of the extended area of the disc against the endplate area (%EAD) on axial CT images. The participants completed the following clinical outcome assessments (COAs) preoperatively and 12 months postoperatively: the JOA Back Pain Evaluation Questionnaire (JOABPEQ), Oswestry Disability Index (ODI), and Roland-Morris Disability Questionnaire (RDQ). The mean %EAD of 315 intervertebral discs was 18.9 ± 8.0. The %EAD was highest at L4/L5, followed by L3/L4, L2/L3, L1/L2, and L5/S1. The %EAD of the surgical level showed no significant correlation with all the preoperative COAs, but it had significant correlation with lumbar function, walking ability, social function domains of the JOABPEQ, ODI score, and RDQ score 12 months postoperatively. %EAD was significantly associated with the postoperative score in the walking ability domain of the JOABPEQ. %EAD affects postoperative clinical outcomes, including low back pain-related quality of life after decompression surgery.

Muscle Reference Values From Thoracic and Abdominal CT for Sarcopenia Assessment: The Framingham Heart Study.

Loss of muscle mass is a known feature of sarcopenia and predicts poor clinical outcomes. Although muscle metrics can be derived from routine computed tomography (CT) images, sex-specific reference values at multiple vertebral levels over a wide age range are lacking. The aim of this study was to provide reference values for skeletal muscle mass and attenuation on thoracic and abdominal CT scans in the community-based Framingham Heart Study cohort to aid in the identification of sarcopenia. This secondary analysis of a prospective trial describes muscle metrics by age and sex for participants from the Framingham Heart Study without prior history of cancer who underwent at least 1 CT scan between 2002 and 2011. Using 2 previously validated machine learning algorithms followed by human quality assurance, skeletal muscle was analyzed on a single axial CT image per level at the 5th, 8th, 10th thoracic, and 3rd lumbar vertebral body (T5, T8, T10, L3). Cross-sectional muscle area (cm 2 ), mean skeletal muscle radioattenuation (SMRA, in Hounsfield units), skeletal muscle index (SMI, in cm 2 /m 2 ), and skeletal muscle gauge (SMRA·SMI) were calculated. Measurements were summarized by age group (<45, 45-54, 55-64, 65-74, ≥75 years), sex, and vertebral level. Models enabling the calculation of age-, sex-, and vertebral-level-specific reference values were created and embedded into an open access online Web application. The cohort consisted of 3804 participants (1917 [50.4%] males; mean age, 55.6 ± 11.8 years; range, 33-92 years) and 7162 CT scans. Muscle metrics qualitatively decreased with increasing age and female sex. This study established age- and sex-specific reference values for CT-based muscle metrics at thoracic and lumbar vertebral levels. These values may be used in future research investigating the role of muscle mass and attenuation in health and disease, and to identify sarcopenia.

Center-Center Surgical Technique With Dynamic Syndesmosis Fixation: A Cadaveric Pilot Study

The objective of this cadaveric biomechanical study was to evaluate if the center-center surgical technique is a reliable and repeatable method of achieving proper syndesmotic reduction when using dynamic syndesmotic fixation. Nine fresh frozen above-knee cadaveric lower extremities were used. Computerized tomography (CT) scans were first obtained for each intact specimen as the baseline for comparison. A simulated complete syndesmotic disruption was created by transection of all deltoid and syndesmotic ligaments. Instability of the ankle was confirmed with stress imaging using fluoroscopy. Each unstable specimen was repaired using the center-center surgical technique with dynamic syndesmosis fixation. A series of measurements from the axial CT images of intact and repaired specimens were used to determine the anatomic distal tibiofibular relationships for comparison of changes from intact to postfixation. All radiographic measurements were performed by 4 independent foot and ankle surgeons. The level of inter-rater reliability for all the measurements was found to be "moderate" to "excellent" agreement (ICC value: 0.865-0.983, 95% confidence interval: 0.634-0.996). There was no statistical difference found between rotational alignment of native and postfixation (a/b: p=.843; b-a: p=.125; θ: p=.062). There was a statistical difference detected for lateral alignment at the center of fibularis incisura between native and postfixation (average: -0.6 ± 0.8 mm, range: -2.3 to 1.2 mm, p < .001). There was no statistical difference found for the anteroposterior translation alignment between native and postfixation (d/e: p=.251; f: p=.377). This study demonstrated the use of the center-center surgical technique as a viable and repeatable method for achieving anatomical reduction of the tibiofibular syndesmosis when used with dynamic fixation modalities.

Giant middle mediastinal lesions: when tumor size correlates with mesenchymal origin-a retrospective single-center analysis.

The International Thymic Malignancy Interest Group (ITMIG) proposed an internationally accepted division of the mediastinum into three compartments based on computed tomography (CT): anterior (prevascular), middle (visceral) and posterior (paravertebral) compartment. There is no generally accepted definition for the term "giant" when applied to middle mediastinal lesions. We defined the term "giant" and described our surgical experience in treating patients with giant lesions of the middle mediastinum. CT imaging of patients operated in our center from January 2016 to August 2021 for mediastinal lesions was reviewed. Lesions were categorized to one of the ITMIG-defined compartments. Lesion size at diagnosis was measured at its largest diameter on axial CT imaging. Giant middle mediastinal lesions were defined as lesions having a size ≥90th percentile of our middle mediastinal lesion cohort. Patients with giant middle mediastinal lesions were further analyzed. Thirty-six patients (23%) had lesions located in the middle mediastinal compartment. Most common diagnoses were mediastinal cysts (n=10, 28%), metastatic lesions (n=6, 17%), lymphomas (n=5, 14%), and sarcomas (n=3, 8%). Ninetieth percentile lesion size was 73 mm. As per definition, four patients had giant middle mediastinal lesions. All these four lesions were of mesenchymal origin including oesophageal leiomyoma, synovial sarcoma, leiomyosarcoma and undifferentiated round cell sarcoma. Resection was performed through posterolateral thoracotomy or sternotomy, with or without cardiopulmonary bypass. The term "giant" could be defined as a mass larger or equal to 73 mm. This definition selected specifically lesions with mesenchymal origin and may therefore guide diagnostic algorithm and patient management.

Artificial Intelligence Automation of Proptosis Measurement: An Indicator for Pediatric Orbital Abscess Surgery.

To evaluate the ability of artificial intelligence (AI) software to quantify proptosis for identifying patients who need surgical drainage. We pursued a retrospective study including 56 subjects with a clinical diagnosis of subperiosteal orbital abscess (SPOA) secondary to sinusitis at a tertiary pediatric hospital from 2002 to 2016. AI computer software was developed to perform 3D visualization and quantitative assessment of proptosis from computed tomography (CT) images acquired at the time of hospital admission. The AI software automatically computed linear and volume metrics of proptosis to provide more practice-consistent and informative measures. Two experienced physicians independently measured proptosis using the interzygomatic line method on axial CT images. The AI software and physician proptosis assessments were evaluated for association with eventual treatment procedures as standalone markers and in combination with the standard predictors. To treat the SPOA, 31 of 56 (55%) children underwent surgical intervention, including 18 early surgeries (performed within 24h of admission), and 25 (45%) were managed medically. The physician measurements of proptosis were strongly correlated (Spearman r = 0.89, 95%CI 0.82-0.93) with 95% limits of agreement of ± 1.8mm. The AI linear measurement was on average 1.2mm larger (p = 0.007) and only moderately correlated with the average physicians' measurements (r = 0.53, 95%CI 0.31-0.69). Increased proptosis of both AI volumetric and linear measurements were moderately predictive of surgery (AUCs of 0.79, 95%CI 0.68-0.91, and 0.78, 95%CI 0.65-0.90, respectively) with the average physician measurement being poorly to fairly predictive (AUC of 0.70, 95%CI 0.56-0.84). The AI proptosis measures were also significantly greater in the early as compared to the late surgery groups (p = 0.02, and p = 0.04, respectively). The surgical and medical groups showed a substantial difference in the abscess volume (p < 0.001). AI proptosis measures significantly differed from physician assessments and showed a good overall ability to predict the eventual treatment. The volumetric AI proptosis measurement significantly improved the ability to predict the likelihood of surgery compared to abscess volume alone. Further studies are needed to better characterize and incorporate the AI proptosis measurements for assisting in clinical decision-making.

The radiomic biomarker in non-small cell lung cancer: 18F-FDG PET/CT characterisation of programmed death-ligand 1 status

To present an integrated 2-[18F]-fluoro-2-deoxy-d-glucose (18F-FDG) positron-emission tomography (PET)/computed tomography (CT) radiomic characterisation of programmed death-ligand 1 (PD-L1) status in non-small-cell lung cancer (NSCLC). In this retrospective study, 18F-FDG PET/CT images and clinical data of 394 eligible patients were divided into training (n=275) and test sets (n=119). Next, the corresponding nodule of interest was segmented manually on the axial CT images by radiologists. After which, the spatial position matching method was used to match the image positions of CT and PET, and radiomic features of the CT and PET images were extracted. Radiomic models were built using five different machine-learning classifiers and the performance of the radiomic models were further evaluated. Finally, a radiomic signature was established to predict the PD-L1 status in patients with NSCLC using the features in the best performing radiomic model. The radiomic model based on the PET intranodular region determined using the logistic regression classifier preformed best, yielding an area under the receiver operating characteristics curve (AUC) of 0.813 (95% CI: 0.812, 0.821) on the test set. The clinical features did not improve the test set AUC (0.806, 95% CI: 0.801, 0.810). The final radiomic signature for PD-L1 status was consisted of three PET radiomic features. This study showed that an 18F-FDG PET/CT-based radiomic signature could be used as a non-invasive biomarker to discriminate PD-L1-positive from PD-L1-negative in patients with NSCLC.

Segmentation of acute pulmonary embolism in computed tomography pulmonary angiography using the deep learning method

Pulmonary embolism is a type of thromboembolism seen in the main pulmonary artery and its branches. This study aimed to diagnose acute pulmonary embolism using the deep learning method in computed tomographic pulmonary angiography (CTPA) and perform the segmentation of pulmonary embolism data. The CTPA images of patients diagnosed with pulmonary embolism who underwent scheduled imaging were retrospectively evaluated. After data collection, the areas that were diagnosed as embolisms in the axial section images were segmented. The dataset was divided into three parts: training, validation, and testing. The results were calculated by selecting 50% as the cut-off value for the intersection over the union. Images were obtained from 1.550 patients. The mean age of the patients was 64.23 ± 15.45 years. A total of 2.339 axial computed tomography images obtained from the 1.550 patients were used. The PyTorch U-Net was used to train 400 epochs, and the best model, epoch 178, was recorded. In the testing group, the number of true positives was determined as 471, the number of false positives as 35, and 27 cases were not detected. The sensitivity of CTPA segmentation was 0.95, the precision value was 0.93, and the F1 score value was 0.94. The area under the curve value obtained in the receiver operating characteristic analysis was calculated as 0.88. In this study, the deep learning method was successfully employed for the segmentation of acute pulmonary embolism in CTPA, yielding positive outcomes.

Deep-learning reconstruction for the evaluation of lumbar spinal stenosis in computed tomography.

To compare the quality and interobserver agreement in the evaluation of lumbar spinal stenosis (LSS) on computed tomography (CT) images between deep-learning reconstruction (DLR) and hybrid iterative reconstruction (hybrid IR). This retrospective study included 30 patients (age, 71.5 ± 12.5 years; 20 men) who underwent unenhanced lumbar CT. Axial and sagittal CT images were reconstructed using hybrid IR and DLR. In the quantitative analysis, a radiologist placed regions of interest within the aorta and recorded the standard deviation of the CT attenuation (i.e., quantitative image noise). In the qualitative analysis, 2 other blinded radiologists evaluated the subjective image noise, depictions of structures, overall image quality, and degree of LSS. The quantitative image noise in DLR (14.8 ± 1.9/14.2 ± 1.8 in axial/sagittal images) was significantly lower than that in hybrid IR (21.4 ± 4.4/20.6 ± 4.0) (P < .0001 for both, paired t test). Subjective image noise, depictions of structures, and overall image quality were significantly better with DLR than with hybrid IR (P < .006, Wilcoxon signed-rank test). Interobserver agreements in the evaluation of LSS (with 95% confidence interval) were 0.732 (0.712-0.751) and 0.794 (0.781-0.807) for hybrid IR and DLR, respectively. DLR provided images with improved quality and higher interobserver agreement in the evaluation of LSS in lumbar CT than hybrid IR.