We depict a unique case of a 39-year-old woman who presented to the emergency department with complaints of right upper quadrant pain. Work-up and a computed tomography (CT) scan revealed acute cholecystitis and the patient underwent laparoscopic cholecystectomy without complication. At this time, an incidental mass was discovered in the subcutaneous fat adjacent to the abdominal wall. The patient returned six months later with progressive, cyclic abdominal pain since her last hospital admission. Initial admission lab work was within normal limits and a urine pregnancy test was negative. Physical exam revealed tenderness around her previous cesarean section scar. Repeat CT revealed an enlarging, spiculated mass adherent to the abdominal wall. After imaging confirmation, the patient underwent complete open surgical excision for the removal of the mass. Post-surgical biopsy confirmed endometrial gland and stroma consistent with abdominal wall endometrioma. The patient was discharged with adjuvant therapy and recommended follow-up with the surgeon and her obstetrician-gynecologist. The radiological diagnosis, guidelines, and decision-making for initiating interventional treatment are discussed in this report. Our purpose in documenting this case is to present a rare diagnosis of an atypical location for an endometrioma on the abdominal wall, in a patient with prior cesarean delivery. Although this patient was treated with open excision, different interventional radiology treatments from radiofrequency ablation and focused ultrasound were discussed. In doing so, we hope to contribute to the systematic literature review on surgical excision as a treatment option for Pfannenstiel incision endometrioma.

BACKGROUND: Inflammatory bowel disease (IBD) is a progressive and debilitating inflammatory disease of the gastrointestinal tract (GIT). Despite recent advances, precise treatment and noninvasive monitoring remain challenging.
METHODS: Herein, we developed orally-administered, colitis-targeting and hyaluronic acid (HA)-modified, core-shell curcumin (Cur)- and cerium oxide (CeO2)-loaded nanoprobes (Cur@PC-HA/CeO2 NPs) for computed tomography (CT) imaging-guided treatment and monitoring of IBD in living mice.
RESULTS: Following oral administration, high-molecular-weight HA maintains integrity with little absorption in the upper GIT, and then actively accumulates at local colitis sites owing to its colitis-targeting ability, leading to specific CT enhancement lasting for 24 h. The retained NPs are further degraded by hyaluronidase in the colon to release Cur and CeO2, thereby exerting anti-inflammatory and antioxidant effects. Combined with the ability of NPs to regulate intestinal flora, the oral NPs result in substantial relief in symptoms. Following multiple treatments, the gradually decreasing range of the colon with high CT attenuation correlates with the change in the clinical biomarkers, indicating the feasibility of treatment response and remission.
CONCLUSIONS: This study provides a proof-of-concept for the design of a novel theranostic integration strategy for concomitant IBD treatment and the real-time monitoring of treatment responses.

OBJECTIVE: This study aims to investigate the anatomical structure of the C6 pedicle and lateral mass in children aged 0-14 years using CT imaging, providing detailed insights into their growth and development.
METHODS: We conducted a comprehensive measurement of C6. Measurements included width, length, and height of the pedicles, as well as the length, width, and thickness of the lateral masses, and several angular metrics. Regression analysis was performed to understand the growth trends, and statistical analyses were carried out to identify differences between age groups, genders, and sides.
RESULTS: In children younger than four years, the pedicle width exceeds its height, influencing the diameter of the pedicle screws. By age two to three, the pedicle height and lateral mass thickness reaches 3.0 mm, allowing for the use of 3.0 mm diameter screws. The pedicle transverse angle remains stable. Most parameters showed no significant differences between the left and right sides. Size parameters exhibited significant larger in males than females at ages 0-1, 3-7, and 10-12 years. Regression analysis revealed that the growth trends of size parameters follow cubic or polynomial curves. Most angular metrics follow cubic fitting curves without a clear trend of change with age.
CONCLUSIONS: This study provides a detailed analysis of the anatomical development of the C6 pedicle and lateral masses in children, offering valuable insights for pediatric cervical spine surgeries. The findings highlight the importance of considering age-specific anatomical variations when planning posterior surgical fixation, specifically at C6. It is necessary for us to perform thin-layer CT scans on children and carefully measure various indicators before surgery.

X-ray computed tomography (CT) imaging technology has become an indispensable diagnostic tool in clinical examination. However, it poses a risk of ionizing radiation, making the reduction of radiation dose one of the current research hotspots in CT imaging. Sparse-view imaging, as one of the main methods for reducing radiation dose, has made significant progress in recent years. In particular, sparse-view reconstruction methods based on deep learning have shown promising results. Nevertheless, efficiently recovering image details under ultra-sparse conditions remains a challenge. To address this challenge, this paper proposes a high-frequency enhanced and attention-guided learning Network (HEAL). HEAL includes three optimization strategies to achieve detail enhancement: Firstly, we introduce a dual-domain progressive enhancement module, which leverages fidelity constraints within each domain and consistency constraints across domains to effectively narrow the solution space. Secondly, we incorporate both channel and spatial attention mechanisms to improve the network\'s feature-scaling process. Finally, we propose a high-frequency component enhancement regularization term that integrates residual learning with direction-weighted total variation, utilizing directional cues to effectively distinguish between noise and textures. The HEAL network is trained, validated and tested under different ultra-sparse configurations of 60 views and 30 views, demonstrating its advantages in reconstruction accuracy and detail enhancement.

Several lung diseases lead to alterations in regional lung mechanics, including ventilator- and radiation-induced lung injuries. Such alterations can lead to localized underventilation of the affected areas, resulting in the overdistension of the surrounding healthy regions. Thus, there has been growing interest in quantifying the dynamics of the lung parenchyma using regional biomechanical markers. Image registration through dynamic imaging has emerged as a powerful tool to assess lung parenchyma\'s kinematic and deformation behaviors during respiration. However, the difficulty in validating the image registration estimation of lung deformation, primarily due to the lack of ground-truth deformation data, has limited its use in clinical settings. To address this barrier, we developed a method to convert a finite-element (FE) mesh of the lung into a phantom computed tomography (CT) image, advantageously possessing ground-truth information included in the FE model. The phantom CT images generated from the FE mesh replicated the geometry of the lung and large airways that were included in the FE model. Using spatial frequency response, we investigated the effect of \" imaging parameters\" such as voxel size (resolution) and proximity threshold values on image quality. A series of high-quality phantom images generated from the FE model simulating the respiratory cycle will allow for the validation and evaluation of image registration-based estimations of lung deformation. In addition, the present method could be used to generate synthetic data needed to train machine-learning models to estimate kinematic biomarkers from medical images that could serve as important diagnostic tools to assess heterogeneous lung injuries.

We present an adult patient, a 39-year-old female, with chief complaints of pain in the umbilical region. The patient was further evaluated by radiological investigations and was diagnosed with small bowel intussusception caused by submucosal lipoma as the lead point. She had undergone ileal resection and anastomosis of the affected segment. The postoperative period was uncomplicated, and the patient continued with regular oral intake. The histopathological analysis revealed it to be adipose tissue with no features of atypia. This case shows the rare presentation of small bowel intussusception due to a submucosal lipoma. It emphasizes the significance of diagnostic imaging tools for diagnosis and the need for surgery for proper administration.

OBJECTIVE: As osteoporosis progresses, the primary compressive trabeculae (PCT) in the proximal femur remains preserved and is deemed the principal load-bearing structure that links the femoral head with the femoral neck. This study aims to elucidate the distribution patterns of PCT within the proximal femur in the elderly population, and to assess its implications for the development and optimization of internal fixation devices used in hip fracture surgeries.
METHODS: This is a retrospective cohort study conducted from March 2022 to April 2023. A total of 125 patients who underwent bilateral hip joint CT scans in our hospital were enrolled. CT data of the unaffected side of the hip were analyzed. Key parameters regarding the PCT distribution in the proximal femur were measured, including the femoral head\'s radius (R), the neck-shaft angle (NSA), the angle between the PCT-axis and the head-neck axis (α), the distance from the femoral head center to the PCT-axis (δ), and the lengths of the PCT\'s bottom and top boundaries (L-bottom and L-top respectively). The impact of gender differences on PCT distribution patterns was also investigated. Student\'s t-test or Mann-Whitney U test were used to compare continuous variables between genders. The relationship between various variables was investigated through Pearson\'s correlation analysis.
RESULTS: PCT was the most prominent bone structure within the femoral head. The average NSA, α, and δ were 126.85 ± 5.85°, 37.33 ± 4.23°, and 0.39 ± 1.22 mm, respectively, showing no significant gender differences (p > 0.05). Pearson\'s correlation analysis revealed strong correlations between α and NSA (r = -0.689, p < 0.001), and R and L-top (r = 0.623, p < 0.001), with mild correlations observed between δ and NSA (r = -0.487, p < 0.001), and R and L-bottom (r = 0.427, p < 0.001). Importantly, our study establishes a method to accurately localize PCT distribution in true anteroposterior (AP) radiographs of the hip joint, facilitating precise screw placement in proximal femur fixation procedures.
CONCLUSIONS: Our study provided unprecedented insights into the distribution patterns of PCT in the proximal femur of the elderly population. The distribution of PCT in the proximal femur is predominantly influenced by anatomical and geometric factors, such as NSA and femoral head size, rather than demographic factors like gender. These insights have crucial implications for the design of internal fixation devices and surgical planning, offering objective guidance for the placement of screws in hip fracture treatments.

(1) Background: The assessment of muscle mass is crucial in the nutritional evaluation of patients with colorectal cancer (CRC), as decreased muscle mass is linked to increased complications and poorer prognosis. This study aims to evaluate the utility of AI-assisted L3 CT for assessing body composition and determining low muscle mass using both the Global Leadership Initiative on Malnutrition (GLIM) criteria for malnutrition and the European Working Group on Sarcopenia in Older People (EWGSOP2) criteria for sarcopenia in CRC patients prior to surgery. Additionally, we aim to establish cutoff points for muscle mass in men and women and propose their application in these diagnostic frameworks. (2) Methods: This retrospective observational study included CRC patients assessed by the Endocrinology and Nutrition services of the Regional University Hospitals of Malaga, Virgen de la Victoria of Malaga, and Vall d\'Hebrón of Barcelona from October 2018 to July 2023. A morphofunctional assessment, including anthropometry, bioimpedance analysis (BIA), and handgrip strength, was conducted to apply the GLIM criteria for malnutrition and the EWGSOP2 criteria for sarcopenia. Body composition evaluation was performed through AI-assisted analysis of CT images at the L3 level. ROC analysis was used to determine the predictive capacity of variables derived from the CT analysis regarding the diagnosis of low muscle mass and to describe cutoff points. (3) Results: A total of 586 patients were enrolled, with a mean age of 68.4 ± 10.2 years. Using the GLIM criteria, 245 patients (41.8%) were diagnosed with malnutrition. Applying the EWGSOP2 criteria, 56 patients (9.6%) were diagnosed with sarcopenia. ROC curve analysis for the skeletal muscle index (SMI) showed a strong discriminative capacity of muscle area to detect low fat-free mass index (FFMI) (AUC = 0.82, 95% CI 0.77-0.87, p < 0.001). The identified SMI cutoff for diagnosing low FFMI was 32.75 cm2/m2 (Sn 77%, Sp 64.3%; AUC = 0.79, 95% CI 0.70-0.87, p < 0.001) in women, and 39.9 cm2/m2 (Sn 77%, Sp 72.7%; AUC = 0.85, 95% CI 0.80-0.90, p < 0.001) in men. Additionally, skeletal muscle area (SMA) showed good discriminative capacity for detecting low appendicular skeletal muscle mass (ASMM) (AUC = 0.71, 95% CI 0.65-0.76, p < 0.001). The identified SMA cutoff points for diagnosing low ASMM were 83.2 cm2 (Sn 76.7%, Sp 55.3%; AUC = 0.77, 95% CI 0.69-0.84, p < 0.001) in women and 112.6 cm2 (Sn 82.3%, Sp 58.6%; AUC = 0.79, 95% CI 0.74-0.85, p < 0.001) in men. (4) Conclusions: AI-assisted body composition assessment using CT is a valuable tool in the morphofunctional evaluation of patients with colorectal cancer prior to surgery. CT provides quantitative data on muscle mass for the application of the GLIM criteria for malnutrition and the EWGSOP2 criteria for sarcopenia, with specific cutoff points established for diagnostic use.

Congenital facial teratomas in neonates pose diagnostic challenges, necessitating a multidisciplinary approach for accurate diagnosis and management. We present the case of a four-day-old female infant delivered via Lower Segment Cesarean Section (LSCS) with a protruding nasolabial mass noted since birth. CT brain plain revealed a soft tissue density opacification arising from the left maxilla with an underlying bony outgrowth, suggestive of a benign congenital developmental anomaly most likely teratoma. Further evaluation is warranted to delineate the exact nature and extent of the anomaly. This case underscores the importance of meticulous evaluation and interdisciplinary collaboration in managing congenital anomalies, with surgical intervention potentially required based on individual patient factors. Continued research and collaboration among medical specialities are essential to improve understanding and management strategies for congenital facial teratomas.

OBJECTIVE: Radiomics has been demonstrated to be strongly associated with TNM stage and patient prognosis. We aimed to develop a model for predicting lymph node metastasis (LNM) and survival.
METHODS: For radiomics texture selection, 3D Slicer 5.0.3 software and the least absolute shrinkage and selection operator (LASSO) algorithm were used. Subsequently, the radiomics model, computed tomography (CT) image, and clinical risk model were compared. The performance of the three models was evaluated using receiver operating characteristic (ROC) curves, decision curve analysis (DCA), calibration plots, and clinical impact curves (CICs).
RESULTS: For the LNM prediction model, 224 patients with LNM information were used to construct a model that was applied to predict LNM. According to the CT data and clinical characteristics, we constructed a radiomics model, CT imaging model and clinical model. The radiomics model for evaluating LNM status showed excellent calibration and discrimination in the training cohort (AUC = 0.926, 95% CI = 0.869-0.982) and the validation cohort (AUC = 0.872, 95% CI = 0.802-0.941). DeLong\'s test demonstrated that the difference among the three models was significant. Similarly, DCA and CIC showed that the radiomics model has better clinical utility than the CT imaging model and clinical model. Our model also exhibited good performance in predicting survival-in line with the findings of the model built with clinical risk factors.
CONCLUSIONS: CT radiomics models exhibited better predictive performance for LNM than models built based on clinical risk characteristics and CT imaging and had comparative clinical utility for predicting patient prognosis.
UNASSIGNED: The radiomics model showed excellent performance and discrimination for predicting LNM and survival of duodenal papillary carcinoma (DPC).
CONCLUSIONS: LNM status determines the most appropriate treatment for DPC. Our radiomics model for evaluating the LNM status of DPC performed excellently. The radiomics model had high sensitivity and specificity for predicting survival, exhibiting great clinical value.