Abdominal Computed Tomography Imaging Research Articles

Optimization of smoothing parameter for block matching and 3D filtering algorithm in low-dose chest and abdominal computed tomography images

Computed tomography (CT), known for its exceptionally high accuracy, is associated with a substantial dose of ionizing radiation. Low-dose protocols have been devised to address this issue; however, a reduction in the radiation dose can lead to a deficiency in the number of photons, resulting in quantum noise. Thus, the aim of this study was to optimize the smoothing parameter (σ-value) of the block matching and 3D filtering (BM3D) algorithm to effectively reduce noise in low-dose chest and abdominal CT images. Acquired images were subsequently analyze using quantitative evaluation metrics, including contrast to noise ratio (CNR), coefficient of variation (CV), and naturalness image quality evaluator (NIQE). Quantitative evaluation results demonstrated that the optimal σ-value for CNR, CV, and NIQE were 0.10, 0.11, and 0.09 in low-dose chest CT images respectively, whereas those in abdominal images were 0.12, 0.11, and 0.09, respectively. The average of the optimal σ-values, which produced the most improved results, was 0.10, considering both visual and quantitative evaluations. In conclusion, we demonstrated that the optimized BM3D algorithm with σ-value is effective for noise reduction in low-dose chest and abdominal CT images indicating its feasibility of in the clinical field.

Association of Psoas Muscle Mass at Intensive Care Unit Admission With Physical Function and Post-discharge Destination in Survivors of Critical Illness.

Survivors of critical illness may have physical impairments, known as post-intensive care syndrome (PICS). Early screening for the risk of PICS is recommended to prevent PICS. Skeletal muscle mass is a clinically important indicator associated with various outcomes. This study aimed to examine the association of psoas muscle mass at intensive care unit (ICU) admission with the destination and physical function at hospital discharge. In this single-center retrospective cohort study, we reviewed the medical records of adult patients who had required emergency ICU admission and who had been intubated and mechanically ventilated. Psoas major muscle was measured as an indicator of skeletal muscle mass from abdominal computed tomography images at ICU admission. Physical function was assessed using the functional status score for the ICU and ICU mobility scale at hospital discharge. Multinomial logistic and multivariable linear regression were used to analyze the associations of the psoas muscle mass with the discharge destination and physical function at discharge. We enrolled 124 patients (79 men and 45 women) with a median (interquartile range) age of 72.0 (62.0-80.0) years; 39 (31.5%) were discharged to home, 50 (40.3%) were transferred to rehabilitation wards, and 35 (28.2%) were transferred to long-term care settings.The psoas muscle area and volume were 16.9 (11.3-20.6) cm2 and228.3 (180.2-282.0) cm3in home discharge patients, 17.5 (11.5-21.5) cm2 and248.4 (162.0-311.4) cm3in rehabilitation ward patients, and 15.9 (10.3-19.5) cm2 and184.0 (137.0-251.1) cm3in long-term care patients. The areas and volumes of the psoas muscle were not significantly different in the three groups. Furthermore, psoas muscle mass was not significantly associated with the discharge destination and physical function. Discharge destination and physical function at hospital discharge were not significantly associated with psoas muscle mass at ICU admission.

Computed Tomography and Dual-Energy X-Ray Asorptiometry body composition parameter harmonisation to universalise adipose tissue measurements in a population-based cross-sectional study.

To harmonise computed tomography (CT) and dual-energy x-ray absorptiometry (DXA) body composition measurements allowing easy conversion in longitudinal assessments and across cohorts to assess cardiometabolic risk and disease. Retrospective cross-sectional observational study from 1996 to 2008 included participants in the Pennington Center Longitudinal Study (PCLS) (N = 1967; 571 African American/1396 White). Anthropometrics, whole-body DXA and abdominal CT images were obtained. Multi-layer segmentation techniques (Analyze; Rochester, MN) quantified visceral adipose tissue (VAT). Clinical biomarkers were obtained from routine blood samples. Linear models were used to predict CT-VAT from DXA-VAT and examine the effects of traditional biomarkers on cross-sectional-VAT. Predicted CT-VAT was highly associated with measured CT-VAT using ordinary least square linear regression analysis and random forest models (R2 = 0.84; 0.94, respectively, p < .0001). Model stratification effects showed low variability between races and sexes. Overall, associations between measured CT-VAT and DXA-predicted CT-VAT were good (R2 > 0.7) or excellent (R2 > 0.8) and improved for all stratification groups except African American men using random forest models. The clinical effects on measured CT-VAT and DXA-VAT showed no significant clinical difference in the measured adipose tissue areas (mean difference = 0.22 cm2). Random forest modelling seamlessly predicts CT-VAT from measured DXA-VAT to a degree of accuracy that falls within the bounds of universally accepted standard error.

The Importance of Lumbar Lordosis During Laparoscopic Trocar Entry

Study ObjectiveInvestigating the effect of lumbar lordosis on the relationship between abdominal trocar entry points and major vascular structures. DesignRetrospective cohort. SettingTertiary referral center. PatientsDistances between the skin and the aorta and inferior vena cava at the trocar entry points, both at the umbilicus and 3 cm and 5 cm superior to the umbilicus, were measured at entry angles of 90 and 45 degrees in 101 abdominal computer tomography images. InterventionsThe relationship of these values with lumbar lordosis was investigated concerning menopausal status, body mass index (BMI), and parity differences. To assess the isolated effect of lumbar lordosis, a simulated 30-degree increase in the lordosis angle was applied to the patients’ computed tomography images. The impact of this increased lumbar lordosis angle on the distances between the skin and major vessels was then evaluated at both the umbilical and supraumbilical trocar entry sites. Measurements and Main ResultsIn the tomographic images of all patients, the distances from the skin to vascular structures were measured at a 90-degree entry angle, resulting in measurements of 8.97 cm ± 2.81 at the umbilicus, 10.89 cm ± 3.02 at 3 cm above the umbilicus, and 11.36 cm ± 2.88 at 5 cm above the umbilicus. These distances exhibited significant differences between patients with BMI <30 and BMI ≥30, as well as between premenopausal and postmenopausal patients. However, at a 45-degree entry angle, vascular structures were observed in only a few patients during trocar projection, and no measurable values were determined. In the simulation, it was found that a 1-degree increase in lumbar lordosis angle resulted in a decrease of 0.272 mm ± 0.018 in the distance between the skin and vascular structures at the umbilicus, 0.425 mm ± 0.024 at 3 cm above the umbilicus, and 0.428 mm ± 0.024 at 5 cm above the umbilicus. ConclusionAn increase in the degree of lumbar lordosis reduces the distance between trocar entry points and major vascular structures. Along with other factors during Veress and trocar entry, lumbar lordosis should be carefully considered.

Myosteatosis is associated with coronary artery calcification in patients with type 2 diabetes.

Myosteatosis, rather than low muscle mass, is the primary etiologic factor of sarcopenia in patients with type 2 diabetes mellitus (T2DM). Myosteatosis may lead to a series of metabolic dysfunctions, such as insulin resistance, systematic inflammation, and oxidative stress, and all these dysfunctions are closely associated with the acceleration of T2DM and atherosclerosis. To investigate the association between myosteatosis and coronary artery calcification (CAC) in patients with T2DM. Patients with T2DM, who had not experienced major cardiovascular events and had undergone both abdominal and thoracic computed tomography (CT) scans, were included. The mean skeletal muscle attenuation was assessed using abdominal CT images at the L3 level. The CAC score was determined from thoracic CT images using the Agatston scoring method. Myosteatosis was diagnosed according to Martin's criteria. Severe CAC (SCAC) was defined when the CAC score exceeded 300. Logistic regression and decision tree analyses were performed. A total of 652 patients with T2DM were enrolled. Among them, 167 (25.6%) patients had SCAC. Logistic regression analysis demonstrated that myosteatosis, age, duration of diabetes, cigarette smoking, and alcohol consumption were independent risk factors of SCAC. Myosteatosis was significantly associated with an increased risk of SCAC (OR = 2.381, P = 0.003). The association between myosteatosis and SCAC was significant in the younger patients (OR = 2.672, 95%CI: 1.477-4.834, P = 0.002), but not the older patients (OR = 1.456, 95%CI: 0.863-2.455, P = 0.188), and was more prominent in the population with lower risks of atherosclerosis. The decision tree analyses prioritized older age as the primary variable for SCAC. In older patients, cigarette smoking was the main contributing factor for SCAC, while in younger patients, it was myosteatosis. Myosteatosis is a novel risk factor for atherosclerosis in patients with T2DM, especially in the population with younger ages and fewer traditional risk factors.

Radiomics-Based Classification of Tumor and Healthy Liver on Computed Tomography Images.

Liver malignancies, particularly hepatocellular carcinoma and metastasis, stand as prominent contributors to cancer mortality. Much of the data from abdominal computed tomography images remain underused by radiologists. This study explores the application of machine learning in differentiating tumor tissue from healthy liver tissue using radiomics features. Preoperative contrast-enhanced images of 94 patients were used. A total of 1686 features classified as first-order, second-order, higher-order, and shape statistics were extracted from the regions of interest of each patient's imaging data. Then, the variance threshold, the selection of statistically significant variables using the Student's t-test, and lasso regression were used for feature selection. Six classifiers were used to identify tumor and non-tumor liver tissue, including random forest, support vector machines, naive Bayes, adaptive boosting, extreme gradient boosting, and logistic regression. Grid search was used as a hyperparameter tuning technique, and a 10-fold cross-validation procedure was applied. The area under the receiver operating curve (AUROC) assessed the performance. The AUROC scores varied from 0.5929 to 0.9268, with naive Bayes achieving the best score. The radiomics features extracted were classified with a good score, and the radiomics signature enabled a prognostic biomarker for hepatic tumor screening.

Computed tomography-based body composition parameters can predict short-term prognosis in ulcerative colitis patients.

Emerging evidence suggests a potential relationship between body composition and short-term prognosis of ulcerative colitis (UC). Early and accurate assessment of rapid remission based on conventional therapy via abdominal computed tomography (CT) images has rarely been investigated. This study aimed to build a prediction model using CT-based body composition parameters for UC risk stratification. In total, 138 patients with abdominal CT images were enrolled. Eleven quantitative parameters related to body composition involving skeletal muscle mass, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) were measured and calculated using a semi-automated segmentation method. A prediction model was established with significant parameters using a multivariable logistic regression. The receiver operating characteristic (ROC) curve was plotted to evaluate prediction performance. Subgroup analyses were implemented to evaluate the diagnostic efficiency of the prediction model between different disease locations, centers, and CT scanners. The Delong test was used for statistical comparison of ROC curves. VAT density, SAT density, gender, and visceral obesity were significantly statistically different between remission and invalidation groups (all p < 0.05). The accuracy, sensitivity, specificity, and area under the ROC curve (AUC) of the prediction model were 82.61%, 95.45%, 69.89%, and 0.855 (0.792-0.917), respectively. The positive predictive value and negative predictive value were 70.79% and 93.88%, respectively. No significant differences in the AUC of the prediction model were found in different subgroups (all p > 0.05). The predicting model constructed with CT-based body composition parameters is a potential non-invasive approach for short-term prognosis identification and risk stratification. Additionally, VAT density was an independent predictor for escalating therapeutic regimens in UC cohorts. The CT images were used for evaluating body composition and risk stratification of ulcerative colitis patients, and a potential non-invasive prediction model was constructed to identify non-responders with conventional therapy for making therapeutic regimens timely and accurately. • CT-based prediction models help divide patients into invalidation and remission groups in UC. • Results of the subgroup analysis confirmed the stability of the prediction model with a high AUC (all > 0.820). • The visceral adipose tissue density was an independent predictor of bad short-term prognosis in UC.

Oblique lateral interbody fusion at L5-S1: feasibility, surgical approach window, incision line, and influencing factors.

The primary aim of this study was to describe the feasibility, surgical approach window (SAW), and incision line (IL) for oblique lateral interbody fusion at L5-S1 (OLIF51) using computed tomography (CT). A secondary aim was to identify associations among approach characteristics and demographic and anthropometric factors. We performed a radiographic study of 50 male and 50 female subjects who received abdominal CT imaging. SAW was measured as the distance from the midline to the medial border of the iliac vessel. IL was measured at the skin surface corresponding to the distance between the center of the disc space and SAW lateral margin. OLIF51 feasibility was defined as the existence of at least a 1-cm SAW without retraction of soft tissues. For the left side, the OLIF51 SAW and IL were 12.1 ± 4.6 and 175.1 ± 55.3mm. For the right side, these measures were 10.0 ± 4.3 and 185.0 ± 52.5mm. Correlations of r = 0.648 (p < 0.001) and r = 0.656 (p < 0.001) were observed between weight and IL on the left and right sides, respectively. OLIF51 was not feasible 23% of the time. To our knowledge, this is the largest CT study to determine the feasibility of performing an OLIF51. Without the use of retraction, OLIF51 is not feasible 23% of the time. Left-sided OLIF51 allows for a larger surgical approach window and smaller incision compared to the right side. Larger incisions are required for adequate surgical exposure in patients with higher weight.

Sd-net: a semi-supervised double-cooperative network for liver segmentation from computed tomography (CT) images

IntroductionThe automatic segmentation of the liver is a crucial step in obtaining quantitative biomarkers for accurate clinical diagnosis and computer-aided decision support systems. This task is challenging due to the frequent presence of noise and sampling artifacts in computerized tomography (CT) images, as well as the complex background, variable shapes, and blurry boundaries of the liver. Standard segmentation of medical images based on full-supervised convolutional networks demands accurate dense annotations. Such a learning framework is built on laborious manual annotation with strict requirements for expertise, leading to insufficient high-quality labels. MethodsTo overcome such limitation and exploit massive weakly labeled data, we relaxed the rigid labeling requirement and developed a semi-supervised double-cooperative network (SD- Net). SD-Net is trained to segment the complete liver volume from preoperative abdominal CT images by using limited labeled datasets and large-scale unlabeled datasets. Specifically, to enrich the diversity of unsupervised information, we construct SD-Net consisting of two collaborative network models. Within the supervised training module, we introduce an adaptive mask refinement approach. First, each of the two network models predicts the labeled dataset, after which adaptive mask refinement of the difference predictions is implemented to obtain more accurate liver segmentation results. In the unsupervised training module, a dynamic pseudo-label generation strategy is proposed. First each of the two models predicts unlabeled data and the better prediction is considered as pseudo-labeling before training. Results and discussionBased on the experimental findings, the proposed method achieves a dice score exceeding 94%, indicating its high level of accuracy and its suitability for everyday clinical use.

P644 Body composition does not predict clinical course in patients with acute severe ulcerative colitis

Abstract Background Acute Severe Ulcerative Colitis (ASUC) is a life-threatening complication of UC. Previous research has shown that body composition parameters, including sarcopaenia, are associated with outcomes in IBD. However, the relationship between body composition and the clinical outcomes of patients hospitalised with ASUC has not yet been clearly defined. We sought to further evaluate the prognostic role of body composition and further explore predictors of clinical outcome in ASUC. Methods We performed a cohort study of hospitalised ASUC patients. Body composition was assessed using fat and muscle segmentation, at the level of the L3 vertebral body, in patients who underwent abdominal computed tomography (CT) during hospitalisation. We defined sarcopenia according to skeletal muscle index (SMI) &amp;lt; 38 cm2/m2 in females and &amp;lt; 42 cm2/m2 in males. Clinical endpoints included length of hospitalisation, need for rescue medical therapy or colectomy. Between group comparisons were performed and logistic regression was used for risk factor analysis. Results We studied 116 patients with ASUC, 51 of whom underwent abdominal CT imaging during their hospitalisation. Median age was 32 years and 64% of patients were female. Sixty-two patients (53.5%) required rescue medical therapy. Rescue medical therapy was successful in 48 patients (77.4%) and 14 patients (22.6%) required an inpatient colectomy. Patients who underwent CT imaging during admission required increased rescue medical therapy (66.7% vs 43.1%, p=0.02) and were hospitalised for longer (11 vs 6 days, p&amp;lt;0.001). Compared to non-sarcopaenic patients, sarcopaenic patients did not require increased rescue medical therapy (60.7 % vs 79 %, p= 0.22) nor longer median hospitalisation (10.5 vs 11.4 days, p=0.69). We observed a trend towards increased rescue therapy failure in patients with sarcopaenia (52.9% vs 33.3%, p=0.31). Higher Mayo score at presentation was associated with increased need for rescue medical therapy (OR 2.18, 95%CI: 1.43-3.33, p&amp;lt;0.001) and an increasing C-reactive protein (CRP) to albumin ratio predicted prolonged length of stay (OR 1.44, 95%CI: 1.18-1.77, p=&amp;lt;0.001). Conclusion Sarcopaenia did not predict ASUC outcomes in this cohort. Higher Mayo score and increased CRP to albumin ratio at admission predicted prolonged hospitalisation and need for rescue medical therapy.

Effects of postoperative oral elemental nutritional supplement on skeletal muscle loss after gastrectomy for gastric cancer.

We previously showed that daily nutritional intervention with an oral elemental diet (ED) at 300kcal/day for 6-8weeks postoperatively decreased the percentage of body weight loss (%BWL), and that the effect was maintained for 1year. This post hoc analysis aimed to determine whether this intervention decreased skeletal muscle mass loss 1-year post-gastrectomy. Data from consecutive, untreated patients with histopathologically confirmed stage I-III gastric adenocarcinoma who planned to undergo total gastrectomy (TG) or distal gastrectomy (DG) and were enrolled in a previously published randomized trial were used. The primary endpoint was the percentage of skeletal muscle mass index (%SMI) loss from baseline at 1year postoperatively, based on abdominal computed tomography images obtained preoperatively and at 1year postoperatively. The overall median %SMI loss was lower in the ED versus control group, but the difference was not significant. The difference in %SMI loss in the ED and control groups was greater in patients with TG (10.1 vs. 13.0; P = 0.12) than in those with DG (5.5 vs. 6.8; P = 0.69). A correlation was observed between %BWL and %SMI loss in both groups (ED group, coefficient 0.591; control group, coefficient 0.644; P < 0.001 for both). Type of gastrectomy (coefficient 7.38; P = 0.001) and disease stage (coefficient - 6.43; P = 0.04) were independent predictors of postoperative skeletal muscle mass loss. ED administration for 6-8weeks following gastrectomy had no inhibitory effect on skeletal muscle loss at 1year postoperatively. UMIN000023455.

Does a collecting system injury with grade iv renal blunt trauma always need urinary intervention?

This study aimed to identify the characteristics associated with the need for urinary intervention for a blunt renal injury with collection system involvement using a computed tomography (CT) protocol for trauma. Abdominal CT images of patients with blunt renal injuries from 2016 to 2020 were reviewed. Patients with low-grade renal trauma, non-collecting system involvement, American Association for the Surgery of Trauma grade V shattered kidney, and emergent nephrectomy were excluded. The largest perinephric mass thickness was measured in the axial view using CT, and a cutoff value was obtained using a receiver-operating characteristic curve analysis. Risk factors for further urinary intervention were analyzed. Among the 70 patients included in this study, those with perinephric mass thicknesses < 25mm (n = 36) had a significantly lower rate of urinary intervention than those with perinephric mass thicknesses ≥ 25mm (0 vs. 5; p = 0.023). There was no significant difference in the follow-up durations of the groups (19days vs. 38days; p = 0.198). More than 90% of the perinephric mass in the < 25mm group resolved within a median follow-up duration of 38days, whereas nearly half of the ≥ 25mm group had a residual perinephric mass during a median follow-up duration of 19days. The initial CT protocol for trauma was useful for predicting the need for further urinary interventions for collecting system injuries. A perinephric mass thickness < 25mm is predictive of a low likelihood of requiring urinary intervention.

Opportunistic assessment of ischemic heart disease risk using abdominopelvic computed tomography and medical record data: a multimodal explainable artificial intelligence approach

Current risk scores using clinical risk factors for predicting ischemic heart disease (IHD) events—the leading cause of global mortality—have known limitations and may be improved by imaging biomarkers. While body composition (BC) imaging biomarkers derived from abdominopelvic computed tomography (CT) correlate with IHD risk, they are impractical to measure manually. Here, in a retrospective cohort of 8139 contrast-enhanced abdominopelvic CT examinations undergoing up to 5 years of follow-up, we developed multimodal opportunistic risk assessment models for IHD by automatically extracting BC features from abdominal CT images and integrating these with features from each patient’s electronic medical record (EMR). Our predictive methods match and, in some cases, outperform clinical risk scores currently used in IHD risk assessment. We provide clinical interpretability of our model using a new method of determining tissue-level contributions from CT along with weightings of EMR features contributing to IHD risk. We conclude that such a multimodal approach, which automatically integrates BC biomarkers and EMR data, can enhance IHD risk assessment and aid primary prevention efforts for IHD. To further promote research, we release the Opportunistic L3 Ischemic heart disease (OL3I) dataset, the first public multimodal dataset for opportunistic CT prediction of IHD.

Cardio–Splenic Relationship in Patients Receiving Trans-Catheter Aortic Valve Replacement

Background: The spleen seems to be a significant buffer of the effective circulating blood volume by changing its size dramatically according to hemodynamics. The cardio–splenic relationship has been recently proposed in the literature regarding heart failure cohorts, and the splenic size has been proposed as a prognostic factor in these cohorts. However, the clinical implication of the splenic size in patients receiving trans-catheter aortic valve replacement (TAVR) remains unknown. Methods: Patients who underwent TAVR at our institute between 2015 and 2022 were eligible. Of these, the patients whose abdominal computed tomography imaging was obtained before TAVR were included. The volume of the spleen was measured in all the participants. The prognostic impact of the indexed splenic volume (SVI) on the 2-year cardiac death or heart failure readmissions was evaluated. Results: A total of 343 patients (86 years, 98 males) were included. The median value of the peak velocity at the aortic valve was 4.4 (4.0, 4.8) m/s and the median SVI was 65.5 (48.9, 86.9) mL/m2. A lower SVI tended to be associated with a lower cardiac output, whereas a higher SVI was associated with a higher plasma volume. The SVI was independently associated with the 2-year cardiac death or heart failure readmission after TAVR with a hazard ratio of 1.09 (95% confidence interval 1.01–1.18, p = 0.041), adjusted for potential confounders. A calculated cutoff of SVI was 70.2 mL/m2, which significantly stratified the cumulative incidence of the primary outcome (10% versus 4%, p = 0.033). Conclusion: A high baseline SVI, which was associated with systemic congestion, was associated with a higher incidence of cardiac death or heart failure readmission after TAVR. Further studies are warranted to clarify the detailed cardio–splenic relationship and implication of measuring the SVI in this cohort.

Noninvasive Computed Tomography-Based Deep Learning Model Predicts In Vitro Chemosensitivity Assay Results in Pancreatic Cancer.

We aimed to predict in vitro chemosensitivity assay results from computed tomography (CT) images by applying deep learning (DL) to optimize chemotherapy for pancreatic ductal adenocarcinoma (PDAC). Preoperative enhanced abdominal CT images and the histoculture drug response assay (HDRA) results were collected from 33 PDAC patients undergoing surgery. Deep learning was performed using CT images of both the HDRA-positive and HDRA-negative groups. We trimmed small patches from the entire tumor area. We established various prediction labels for HDRA results with 5-fluorouracil (FU), gemcitabine (GEM), and paclitaxel (PTX). We built a predictive model using a residual convolutional neural network and used 3-fold cross-validation. Of the 33 patients, effective response to FU, GEM, and PTX by HDRA was observed in 19 (57.6%), 11 (33.3%), and 23 (88.5%) patients, respectively. The average accuracy and the area under the receiver operating characteristic curve (AUC) of the model for predicting the effective response to FU were 93.4% and 0.979, respectively. In the prediction of GEM, the models demonstrated high accuracy (92.8%) and AUC (0.969). Likewise, the model for predicting response to PTX had a high performance (accuracy, 95.9%; AUC, 0.979). Our CT patch-based DL model exhibited high predictive performance in projecting HDRA results. Our study suggests that the DL approach could possibly provide a noninvasive means for the optimization of chemotherapy.

Association of sex-specific abdominal adipose tissue with WHO/ISUP grade in clear cell renal cell carcinoma

ObjectivesTo explore the association between computed tomography (CT)-measured sex-specific abdominal adipose tissue and the pathological grade of clear cell renal cell carcinoma (ccRCC).MethodsThis retrospective study comprised 560 patients (394 males and 166 females) with pathologically proven ccRCC (467 low- and 93 high-grade). Abdominal CT images were used to assess the adipose tissue in the subcutaneous, visceral, and intermuscular regions. Subcutaneous fat index (SFI), visceral fat index (VFI), intermuscular fat index (IFI), total fat index (TFI), and relative visceral adipose tissue (rVAT) were calculated. Univariate and multivariate logistic regression analyses were performed according to sex to identify the associations between fat-related parameters and pathological grade.ResultsIFI was significantly higher in high-grade ccRCC patients than in low-grade patients for both men and women. For male patients with high-grade tumors, the SFI, VFI, TFI, and rVAT were significantly lower, but not for female patients. In both univariate and multivariate studies, the IFI continued to be a reliable and independent predictor of high-grade ccRCC, regardless of sex.ConclusionsIntermuscular fat index proved to be a valuable biomarker for the pathological grade of ccRCC and could be used as a reliable independent predictor of high-grade ccRCC for both males and females.Critical relevance statementSex-specific fat adipose tissue can be used as a new biomarker to provide a new dimension for renal tumor-related research and may provide new perspectives for personalized tumor management decision-making approaches.Key points• There are sex differences in distribution of subcutaneous fat and visceral fat.• The SFI, VFI, TFI, and rVAT were significantly lower in high-grade ccRCC male patients, but not for female patients.• Intermuscular fat index can be used as a reliable independent predictor of high-grade ccRCC for both males and females.Graphical

Recurrent early-stage squamous cell carcinoma cervical cancer presenting with isolated ovary metastasis: a rare case report

Introduction: Ovarian metastatic squamous carcinoma of the cervix is rare, accounting for about 0.4%. This study reports a single case of metastatic recurrent cervical cancer in the ovary. Case presentation: A 46-year-old patient with a history of cervical cancer T1b2N0M0 underwent a radical hysterectomy, bilateral pelvic lymph node dissection, and ovarian preservation. One year later, the patient was admitted to the hospital because of abdominal pain in the left iliac fossa; the abdominal computed tomography image showed a left ovarian tumour. The patient underwent laparoscopic left oophorectomy. Postoperative histopathology confirmed ovarian squamous cell carcinoma. From this case, we would like to review the literature on epidemiology, diagnosis, treatment, and prognosis. Clinical discussion: Ovarian preservation during surgery in patients with cervical cancer offers many benefits, but careful patient selection is required. However, it should be selected carefully and closely monitored. Conclusions: Clinicians should be aware of this situation of ovarian metastasis in patients with early cervical cancer undergoing ovarian-conserving surgery.

A novel imaging index for predicting adverse progression in acute-on-chronic liver failure related to hepatitis B virus: the low erector spine index

BackgroundIt is widely known that muscle mass influences the outcomes of many chronic diseases. Erector spine mass is a convenient parameter obtained from routine abdominal computed tomography (CT). The clinical application value of erector spine mass, and whether erector spine mass could predict the outcome of disease has not been studied.AimTo evaluate the role of the erector spine index (ESI) calculated based on abdominal CT imaging in the progression of acute-on-chronic liver failure related to the hepatitis B virus (HBV-ACLF).MethodsWe performed a retrospective study of 118 HBV-ACLF patients and calculated the ESI (the total erector spine area normalized for height2 in meters) for each patient through abdominal CT. The findings were analyzed regarding the progression of HBV-ACLF and the ESI at baseline, including mortality and the development of complications.ResultsThe ESI level was associated with mortality and the development of complications. During the 90-day follow-up period, patients with a low ESI (<12.05 cm2/m2) had higher mortality than those with a high ESI (≥ 12.05 cm2/m2) (51.7% vs. 26.7%), and the cumulative survival rates were 71.0%±4.6 and 85.8%±3.9, respectively (log-rank P = 0.003). The hazard ratios (HRs) calculated using univariable and multivariable analyses were 2.23(95% confidence interval (CI): 1.25–4.21, P = 0.005) and 2.52 (95% CI: 1.34–9.24, P = 0.011), respectively. Patients with a low ESI (<12.05 cm2/m2) had higher incidences of kidney dysfunction (43.5% vs. 23.2%, P = 0.029; log-rank P = 0.017) and hepatic encephalopathy (39.6% vs. 14.0%, P = 0.003; log-rank P = 0.010) than those with a high ESI. A low ESI was an independent risk factor for kidney dysfunction (adjusted HR = 1.36, 95% CI: 1.05–2.93, P = 0.043) and the development of hepatic encephalopathy (adjusted HR = 2.26; 95% CI: 2.05–3.13, P = 0.036). In addition, the presence of hepatic encephalopathy (the odds ratio (OR) = 2.26, 95% CI: 2.05–3.18, P = 0.006), spontaneous bacterial peritonitis (OR = 3.95, 95% CI: 1.01–5.46, P = 0.037), and kidney dysfunction (OR = 4.47, 95% CI: 1.02–9.64, P = 0.032) was independently associated with a low ESI in patients.ConclusionA low ESI is an independent risk factor for mortality in patients with HBV-ACLF, as well as the development of kidney dysfunction and hepatic encephalopathy.

Impact of surgical treatment on lipid metabolism in patients with lumbar spinal disorders: Prospective observational study

PurposeIt is still unclear how lumbar spinal surgery affects the lipid metabolism of patients with lumbar spinal disorders (LSDs) such as lumbar spinal canal stenosis and lumbar disk herniation. The present study aimed to assess the impact of lumbar spinal surgery on lipid metabolism in patients with LSDs and clarify the factors associated with changes in visceral fat (VF) accumulation before and after lumbar spinal surgery.MethodsConsecutive patients with lumbar spinal surgery for LSDs were prospectively included. Abdominal computed tomography images and blood examination of the participants were evaluated before surgery and at 6 months and 1 year after surgery. The cross-sectional VF area (VFA) was measured at the level of the navel using computed tomography images. Blood examination items included triglycerides and high-density lipoprotein (HDL).ResultsThe study enrolled a total of 138 patients. Female patients with LSDs had significantly increased VFA and serum triglyceride levels after lumbar spinal surgery. On multivariable analysis, the group with > 100 cm2 of preoperative VFA and a postoperative decrease in VFA had a significantly worse preoperative walking ability based on the Japanese Orthopaedic Association Back Pain Evaluation Questionnaire (relative risk 2.1; 95% confidence intervals 1.1–4.1).ConclusionsThe present study demonstrated that patients with LSDs did not necessarily improve their lipid metabolism after lumbar spinal surgery. Instead, female patients with LSDs had significantly deteriorated lipid metabolism after lumbar spinal surgery. Finally, a worse preoperative walking ability was associated with the improvement in excess VF accumulation after lumbar spinal surgery.

Clinico-radiological study of the pancreatic tail in relation to the splenic hilum

Introduction: Splenectomy is one of the most commonly performed surgical procedures worldwide. The splenic hilum is closely related to adjacent organs like the tail of the pancreas, stomach, splenic flexure of colon, and left kidney. One of the morbid complications of splenectomy is injury to the tail of pancreas. The objective of this study was to assess the anatomical details of the pancreatic tail with respect to the splenic hilum by assessing patient’s abdominal computed tomography (CT) imaging. Methods: A total of 150 patients’ abdominal CT imaging was taken for evaluation in this study. The distance between the pancreatic tail and the splenic hilum was measured. The level of location of the pancreatic tail in relation to the splenic hilum was also noted for each patient. Results: The pancreatic tail was inferior to the level of the splenic hilum in 59.3 percent (n =89) of the patients, superior to the level of the splenic hilum in 2.0 percent (n =3) of the patients, and at the level of the hilum in 38.7 percent (n = 58) of the patients. The mean distance from the pancreatic tail to the splenic hilum was 13.1 ± 5.2 mm. Conclusion: Abdominal CT imaging will provide a road map regarding the location of the pancreatic tail and the distance between the pancreatic tail and the splenic hilum. With the preoperative CT imaging details and efficient surgical dissection as close as possible to the splenic hilum, the potential injury to the pancreatic tail can be prevented. Keywords: splenectomy; pancreatic tail injury; splenic hilum; pancreatic fistula