Rol de las imágenes en la evaluación de la invaginación intestinal del adulto: un estudio retrospectivo de 10 años / Role of imaging in the evaluation of intussusception in adults: a 10-year retrospective study

Introducción: La invaginación intestinal es la introducción de un segmento de asas intestinales en otro segmento adyacente. A diferencia de la población pediátrica, cuya etiología es principalmente idiopática, en el adulto se asocia con mayor frecuencia a patologías graves. El uso cada vez mayor de estudios imagenológicos en la evaluación abdominal ha llevado a mayor detección de invaginaciones intestinales sin enfermedad subyacente, en las que no es posible determinar una causa de base. El objetivo de este estudio fue revisar la presentación clínica, estudio y tratamiento en pacientes con diagnóstico imagenológico de invaginación intestinal en ecografía o tomografía computarizada de abdomen. Método: Se realizó un estudio descriptivo retrospectivo a partir de los informes radiológicos de ecografías y tomografías computarizadas de abdomen obtenidas en un periodo de 10 años en una institución hospitalaria. Resultados: Se obtuvieron 40 casos. En el 10% de ellos, la invaginación intestinal fue un hallazgo incidental en un estudio por otra causa. En el 68% de los casos no se identificó una causa subyacente, demostrándose resolución espontánea en el 75% de los casos con estudio posterior. El síntoma más frecuente fue el dolor abdominal, presente en el 60% de los pacientes. La ubicación más habitual fue entero-enteral en el 90% de los casos. Solo en el 8% de los casos la invaginación intestinal se atribuyó a una causa maligna. Hubo resolución quirúrgica en 7 pacientes. Conclusión: El aumento en el uso de imágenes para el estudio abdominal ha demostrado que existe un porcentaje importante de invaginaciones intestinales que son idiopáticas y que presentarán resolución espontánea.(AU)

Introduction: Intussusception is the insertion of a bowel loop segment into an adjacent segment. Unlike in children, where the condition is mainly idiopathic, intussusception in adults is more often associated with severe disease. The growing use of imaging studies to evaluate the abdomen has resulted in a higher rate of detection of cases of intussusception without underlying disease in which it is not possible to determine the cause. This study aimed to review the clinical presentation, evaluation, and treatment of patients in whom abdominal ultrasonography or computed tomography diagnosed intussusception. Method: We retrospectively reviewed radiology reports of abdominal ultrasound and computed tomography studies done at our hospital in a 10-year period. Results: In the 40 cases found, intussusception was an incidental finding in 10%. No underlying cause was identified in 68%, and posterior imaging studies showed spontaneous resolution in 75%. The most common symptom was abdominal pain, being present in 60%. Intussusception affected only the small bowel in 90% of cases (entero-enteric intussusception). Intussusception was attributed to malignancy in only 8% of cases. In 7 patients, intussusception was resolved surgically. Conclusion: The increased use of abdominal imaging has shown that a significant proportion of cases of intussusception are idiopathic and resolve spontaneously.(AU)

Sustaining the gains: Reducing unnecessary computed tomography scans in pediatric trauma patients.

BACKGROUND/PURPOSE: "Pan-scanning" pediatric blunt trauma patients leads to exposure to harmful radiation and increased healthcare costs without improving outcomes. We aimed to reduce computed tomography (CT) scans that are not indicated (NI) by imaging guidelines for injured children. METHODS: In July 2017, our Pediatric Trauma Center prospectively implemented validated imaging guidelines to direct CT imaging for trauma activations and consultations for children younger than 16 years old with blunt traumatic injuries. Patients with suspected physical abuse, CT imaging prior to arrival, penetrating mechanism, and instability precluding CT imaging were excluded. We compared CT scanning rates for pre-implementation (01/2016-06/2017) and post-implementation (07/2017-08/2021) time periods. Guideline compliance was evaluated by chart review and sustained through iterative process improvement cycles. RESULTS: During the pre-implementation era, 61 patients underwent 171 CT scans of which 87 (51%) scans were not indicated by guidelines. Post-implementation, 363 patients had 531 scans and only 134 (25%) CTs were not indicated. Total CTs performed declined after initiation of guidelines (2.80 vs 1.46 scans/patient, p<0.0001). Total NI CTs declined (1.41 vs 0.37 NI scans/patient, p<0.0001) reflected in significant reductions in all anatomic regions: head, cervical spine, chest, and abdomen/pelvis. Charges related to NI scans decreased from $1,490.31/patient to $408.21/patient, saving $218,000 in charges. Based on prior utilization, 146 children were spared excessive radiation with no clinically significant missed injuries since guideline implementation. CONCLUSIONS: Quality improvement and implementation science methodologies to enhance compliance with imaging guidelines for children with blunt injuries can significantly reduce unnecessary CT scanning without compromising care. This practice reduces harmful radiation exposure in a sensitive patient population and may save healthcare systems money and resources.

Computed tomography rates in pediatric trauma patients among emergency medicine and pediatric emergency medicine physicians.

BACKGROUND: Pediatric trauma patients undergo fewer computed tomography (CT) scans when evaluated at pediatric trauma centers (PTC) versus adult trauma centers (ATC) with no change in clinical outcome. Factors contributing to this difference are unclear. We sought to identify whether the training background of physicians, specifically emergency medicine (EM) versus pediatric emergency medicine (PEM), affected the CT rate of pediatric trauma patients within one institution. METHODS: A single-center retrospective study of CT utilization based on attending physicians' training in trauma patients <18 years between November 2018 and November 2020. Attendings were categorized into two groups: EM residency with no PEM fellowship, or pediatrics/EM residency with PEM fellowship. Primary outcomes measured were the proportion of patients receiving a CT and CT positivity rate. RESULTS: Of 463 study patients, CTs were obtained in 145/228 (64%) patients by EM, and 130/235 (55%) by PEM (p=.07). CT positivity rate was 21% and 19% in EM and PEM, respectively (p=.46). The mean number of CTs per patient in EM was 2.8 compared to 2.1 in PEM (p<.01), and for patients with an injury severity score (ISS) >15, mean number of CTs per patient increased to 4.9 in EM versus 2.4 in PEM (p=.01). CONCLUSIONS: The mean number of CTs ordered per patient was statistically higher for EM attendings. The differences between CT rates highlight future opportunities for ongoing development of pediatric trauma imaging guidelines and radiation exposure reduction. LEVELS OF EVIDENCE: Retrospective Study, Level III.

Categorización y revisión de reevaluaciones en tomografía computada en una unidad de telerradiología de urgencia / Categorization and review of reevaluations in computed tomography in an emergency teleradiology unit

INTRODUCCIÓN La telerradiología se basa en el despliegue de radiólogos a distancia para evaluar estudios de dicha especialidad. Actualmente hay evidencia limitada sobre las tasas de error de evaluaciones en telerradiología. Este estudio corresponde a una revisión de las discrepancias entre los informes preliminares y finales de tomografía computada (TC) de una unidad de urgencia telerradiológica. OBJETIVO Determinar las discrepancias de las reevaluaciones (addendum) en los informes radiológicos de TC en una unidad de telerradiología de urgencia. MATERIALES Y MÉTODOS La recolección de datos se planificó a modo de tabla de cotejo, en la cual se tabularon casos de reevaluaciones de urgencia desde el mes de enero hasta mayo del año 2021, en base a la categorización Agrawal. RESULTADOS De una total de 111.599, 836 informes presentaron addendum, que corresponden al 0,74% del total informado, La categoría Agrawal 0 agrupó la mayor cantidad de casos y los exámenes de TC especialidad de cuerpo se encuentran los segmentos con mayores requerimientos de reevaluación. Discusión: Los valores obtenidos permiten establecer una baja incidencia de reevaluaciones y de la gravedad de estas, apuntando a errores asociados a canales de comunicación, redacción y elaboración de informes con especial énfasis en estudios TC Tórax y Abdomen/Pelvis. CONCLUSIÓN El porcentaje de cumplimiento de un 99,26% de exactitud en los informes permite concluir la alta confiabilidad y la calidad del servicio de telerradiología de la empresa en cuestión durante el periodo evaluado y el empleo de medidas correctivas basadas en organización, gestión e instrumentalización tecnológica

Variation in Positivity Rates of Computed Tomography Pulmonary Angiograms for the Evaluation of Acute Pulmonary Embolism Among Emergency Department Physicians.

Computed tomography pulmonary angiography (CTPA) is an imaging study for which there is substantial evidence for its overuse in the evaluation of acute pulmonary embolism (PE). Prior literature has reported low positive PE rates, but the variability in positive rates among the ordering physicians has not been as well studied. The purpose of this study was to evaluate variation in ordering and positive rates among physicians in an emergency department (ED) within an integrated health care system.This study was based in a single ED that is part of a geographically isolated integrated health care system. We reviewed the patient records for all patients who underwent a CTPA for the evaluation for acute PE in the ED between January 1, 2018, and December 31, 2019. For each CTPA examination, we recorded the ordering ED physician, serum d-dimer value (mcg/mL), if any, and the results of the CTPA.Review of CTPAs over the 2-year period revealed 1380 CTPAs ordered by 23 ED physicians with a range of 25-141 studies per physician (mean of 60 + 31 CTPAs). The overall positive rate for PE was 6.9%. Individual ED physician positivity rates showed wide variability ranging from 0% to 18.4% (mean positive rate 7.6 + 4.4%). The results of this study confirm the need for greater adherence to existing guidelines using clinical decision rules and d-dimer testing when appropriate among all ED physicians but especially those who order a greater number of studies and have low rates for positive PE.

Reconstruction Algorithm-Based Computed Tomography Image Feature for Evaluating the Effect of Internal Administration and Medicated Bath of Liangxue Xiaoyin Decoction on Psoriasis Vulgaris.

Skin computed tomography (CT) image based on improved marching cubes (MC) algorithm was explored to evaluate the therapeutic effect of internal administration of Liangxue Xiaoyin decoction combined with medicated bath in the treatment of psoriasis vulgaris. 712 patients with psoriasis vulgaris blood heat syndrome in hospital were recruited as the research object, which were randomly divided into observation group (TCM oral therapy combined with medicinal bath) and control group (TCM oral therapy), each with 356 cases. Psoriasis area and severity index (PASI), pruritus degree, and clinical treatment effect were compared. The results showed that the reconstruction time of median method was greatly shorter, and the algorithm efficiency was improved by 40.6290%. After treatment, the psoriasis area and severity index (PASI) score of the observation group was 5.61 ± 1.15, ΔPASI = (22.64 ± 2.15). ΔPASI% = 80.14%, which were greatly higher than the control group ((9.41 + 1.56) points, ΔPASI = (18.84 + 1.65) points, ΔPASI% = 66.69%) (P < 0.05). After treatment, the itching degree of the observation group was 3.03 ± 1.01 points, which was lower than that of the control group ((3.71 ± 1.06) points), and the itching degree of the observation group was greater than that of the control group, with substantial difference (P < 0.05). The total effective rate of observation group (88.76%) was higher than that of control group (71.07%) (P < 0.05). Therefore, skin CT image based on the improved MC algorithm can evaluate the therapeutic effect of internal administration of Liangxue Xiaoyin decoction combined with medicated bath in the treatment of psoriasis vulgaris. The internal administration of Liangxue Xiaoyin decoction combined with medicated bath had a good effect on the treatment of psoriasis vulgaris and was of certain clinical application value.

Effect Evaluation of Platelet-Rich Plasma Combined with Vacuum Sealing Drainage on Serum Inflammatory Factors in Patients with Pressure Ulcer by Intelligent Algorithm-Based CT Image.

This work was to explore the efficacy of intelligent algorithm-based computed tomography (CT) to evaluate platelet-rich plasma (PRP) combined with vacuum sealing drainage (VSD) in the treatment of patients with pressure ulcers. Based on the u-net network structure, an image denoising algorithm based on double residual convolution neural network (Dr-CNN) was proposed to denoise the CT images. A total of 84 patients who were hospitalized in hospital were randomly divided into group A (without any intervention), group B (PRP treatment), group C (VSD treatment), and group D (PRP+VSD treatment). Procalcitonin (PCT) was detected by enzyme-linked immunosorbent assay (ELISA) combined with immunofluorescence method, C-reactive protein (CRP) was detected by rate reflectance turbidimetry (RRT), and interleukin-6 (IL-6) was detected by electrochemiluminescence method. The results showed that after treatment, 44 cases (52.38%) of pressure ulcers patients recovered, 24 cases (28.57%) had no change in stage, and 16 cases (19.04%) developed pressure ulcers. The pain scores of group D at 1 week (3.35 ± 0.56 points) and 2 weeks (2.76 ± 0.55 points) after treatment were significantly lower than those in group C (7.77 ± 0.58 points and 6.34 ± 0.44 points, respectively). The time of complete wound healing in group D (24.5 ± 2.32) was obviously lower in contrast to that in groups A, B, and C (35.54 ± 3.22 days, 30.23 ± 2 days, and 29.34 ± 2.15 days, respectively). In addition, the medical satisfaction of group D (8.74 ± 0.69) was significantly higher than that of groups A, B, and C (4.69 ± 0.85, 5.22 ± 0.31, and 5.18 ± 0.59, respectively). The levels of IL-6 and PCT in group D were lower than those in groups A, B, and C, and the differences were statistically significant (P < 0.01). The average values of peak signal to noise ratio (PSNR) and structural similarity index measure (SSIM) of the Dr-CNN network model were 37.21 ± 1.09 dB and 0.925 ± 0.01, respectively, which were higher than other algorithms. The mean values of root mean square error (MSE) and normalized mean absolute distance (NMAD) of the Dr-CNN network model were 0.022 ± 0.002 and 0.126 ± 0.012, respectively, which were significantly lower than other algorithms (P < 0.05). The experimental results showed that PrP combined with VSD could significantly reduce the inflammatory response of patients with pressure ulcers. PRP combined with VSD could significantly reduce the pain of dressing change for patients. Moreover, the performance model of image denoising algorithm based on double residual convolutional neural network was better than other algorithms.

Classification of Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on Radiomic Analysis.

INTRODUCTION: Considering the narrow window of surgery, early diagnosis of liver cancer is still a fundamental issue to explore. Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICCA) are considered as two different types of liver cancer because of their distinct pathogenesis, pathological features, prognosis, and responses to adjuvant therapies. Qualitative analysis of image is not enough to make a discrimination of liver cancer, especially early-stage HCC or ICCA. METHODS: This retrospective study developed a radiomic-based model in a training cohort of 122 patients. Radiomic features were extracted from computed tomography (CT) scans. Feature selection was operated with the least absolute shrinkage and operator (LASSO) logistic method. The support vector machine (SVM) was selected to build a model. An internal validation was conducted in 89 patients. RESULTS: In the training set, the AUC of the evaluation of the radiomics was 0.855 higher than for radiologists at 0.689. In the valuation cohorts, the AUC of the evaluation was 0.847 and the validation was 0.659, which indicated that the established model has a significantly better performance in distinguishing the HCC from ICCA. CONCLUSION: We developed a radiomic diagnosis model based on CT image that can quickly distinguish HCC from ICCA, which may facilitate the differential diagnosis of HCC and ICCA in the future.

Postoperative Curative Effect of Cardiac Surgery Diagnosed by Compressed Sensing Algorithm-Based E-Health CT Image Information and Effect of Baduanjin Exercise on Cardiac Autonomic Nerve Function of Patients.

This research was aimed at exploring the effect of CT images reconstructed by optimized compressed sensing algorithm on postoperative diagnosis of patients with hypertensive heart disease and the influence of Baduanjin on cardiac autonomic nerve function. Based on the compressed sensing algorithm, the maximum likelihood expectation maximization algorithm was introduced to optimize it, and the optimization algorithm was established. The optimized algorithm and filtered back projection algorithm (FBP) were compared regarding the root mean squared error (RMSE), peak signal-to-noise ratio (PSNR), and structural similar image metric (SSIM). A total of 126 patients with hypertensive heart disease who underwent CT examination in the hospital were selected as study subjects. According to whether Baduanjin intervention was adopted, patients were divided into observation group (conventional treatment +Baduanjin) and control group (conventional treatment), with 63 patients in each group. The effect of CT examination on postoperative diagnosis was analyzed. Systolic blood pressure (SBP), diastolic blood pressure (DBP), differential pressure (DP), respiratory rate and heart rate (HR), very low-frequency (VLF) power, low-frequency (LF) power, high-frequency (HF) power, total power (TP) of HR variability, and changes in LF/HF of patients before and after treatment were compared. The RMSE of the compressed sensing optimization algorithm (3.28 ± 0.36) was significantly lower than that of the FBP algorithm (9.25 ± 1.03) (P < 0.05). The SSIM and PNSR of the compressed sensing optimization algorithm were (0.87 ± 0.10) and (21.22 ± 1.60) dB, respectively. The SSIM was significantly higher than the FBP algorithm (P < 0.01), and the PNSR was also higher than the FBP algorithm (P < 0.05). The detection rate of CT for pleural effusion was 16 cases (25.40%) higher than 5 cases (7.94%) with TTE (P < 0.01). After treatment, SBP, DBP, HR, LF, VLF, LF/HF, and DP values in the observation group were lower than those in the control group (P < 0.05), and TP and HF were higher than those in the control group (P < 0.05). It suggested that a novel algorithm was established based on compressed sensing algorithm to improve image quality. CT image had important guiding significance for postoperative diagnosis of heart. Baduanjin intervention could improve the integrated function of patient's autonomic nervous system and the regulation ability of the vagus nerve.

Artificial Intelligence Algorithm-Based Computed Tomography Image of Both Kidneys in Diagnosis of Renal Dysplasia.

The objective of this study was to explore the accuracy of low-dosage computed tomography (CT) images based on the expectation maximization algorithm denoising algorithm (EM algorithm) in the detection and diagnosis of renal dysplasia, so as to provide reasonable research basis for accuracy improvement of clinical diagnosis of renal dysplasia. 120 patients with renal dysplasia in hospital were randomly selected as the research objects, and they were divided into two groups by random number method, with 60 patients in each group. The low-dosage CT images of patients in the control group were not processed (nonalgorithm group), and the low-dosage CT images of patients in the observation group were denoised using the EM algorithm (algorithm group). In addition, it was compared with the results of the comprehensive diagnosis (gold standard) to analyze the accuracy of the diagnosis of the two groups of patients and the consistency with the results of the pathological diagnosis. The results were compared with those of the comprehensive diagnosis (gold standard) to analyze the accuracy of the diagnosis of the two groups of patients. The results showed that the peak signal-to-noise ratio (PSNR) (15.9 dB) of the EM algorithm was higher than the regularized adaptive matching pursuit (RAMP) algorithm (1.69 dB) and the mean filter (4.3 dB) (P < 0.05). The time consumption of EM algorithm (21 s) was shorter than that of PWLS algorithm (34 s) and MS-PWLS algorithm (39 s) (P < 0.05). The diagnosis accuracy of dysplasia of single kidney, absence of single kidney, horseshoe kidney, and duplex kidney was obviously higher in the algorithm group than the control group (P < 0.05), which were 66.67% vs. 90%, 60% vs. 88.89%, 71.42% vs. 100%, and 60% vs. 88.89%, respectively. The incidence of hypertension in patients with autosomal dominant polycystic kidney disease (ADPKD) (56.77%) was much higher than that of the other diseases (P < 0.05). After denoising by the EM algorithm, low-dosage CT image could improve the diagnostic accuracy of several types of renal dysplasia except ADPKD, showing certain clinical application value. In addition, ADPKD was easy to cause hypertension.

Three-Dimensional Skin CT Based on Intelligent Algorithm in the Analysis of Skin Lesion Sites Features in Children with Psoriasis.

This research was to explore the application value of three-dimensional computed tomography (CT) based on artificial intelligent algorithm in analyzing the characteristics of skin lesions in children with psoriasis. In this study, 15 children with psoriasis were selected as the observation group, and 15 children with other skin diseases were selected as the control group. The CT images were optimized, and the feature selection was carried out based on artificial intelligent algorithm. Firstly, the results were compared with the results of simple skin three-dimensional CT to determine the effectiveness. Then, the two groups of three-dimensional skin CT image features of skin psoriasis-like hyperplasia, Munro microabscess, dermal papillary vascular dilation, and squamous epithelium based on intelligent algorithms were compared. After comparison, the detection rate of psoriasis-like hyperplasia, Munro microabscess, dermal papillary vascular dilation, and squamous epithelium in the observation group was higher than that in the control group, with significant difference and statistical significance (P < 0.05). In addition, the sensitivity of psoriasis-like hyperplasia, Munro microabscess, dermal papilla vascular dilatation, and squamous epithelium in children with psoriasis was 80.0%, 86.7%, 80.0%, and 93.3%, respectively. The specificity of psoriasis-like hyperplasia, Munro microabscess, dermal papilla vascular dilatation, and squamous epithelium in children with psoriasis was 86.7%, 93.3%, 60.0%, and 73.3%, respectively. The results showed that Munro microabscess and psoriasis-like hyperplasia had high sensitivity and specificity in all diagnostic items, which could be used as important features of skin lesion sites in the diagnosis of psoriasis in children. The research provides a basis for the clinical diagnosis of psoriasis in children, which is worthy of clinical promotion.

Sarcopenia as a novel prognostic factor in the patients of primary localized gastrointestinal stromal tumor.

BACKGROUND: Sarcopenia predicts poor prognosis of a variety of gastrointestinal malignancies. However, there is a lack of study on the association between skeletal muscle index (SMI) and the prognosis of gastrointestinal stromal tumor (GIST). The aim of this study is to develop a novel nomogram based on sarcopenia for GIST patients to predict overall survival (OS). METHODS: SMI was measured by computed tomography scan of 107 patients who underwent resection for primary localized gastrointestinal stromal tumor (GIST). Sarcopenia was defined by cutoff values for SMI as 40.1 cm2/m2 and 39.8 cm2/m2 using optimum stratification for males and females respectively. Factors were included in the nomogram were specified by univariate and multiple Cox proportional hazard analysis. Concordance index (C-index) and calibration curves were conducted to measure the discrimination and accuracy of the nomogram. The utility of the nomogram was assessed by the decision curve analysis (DCA). RESULTS: Twenty-eight (26.2%) of 107 patients were sarcopenic. Sarcopenia was correlated significantly with body mass index, albumin, female sex, resection style, mitotic index, rupture status, survival. Sarcopenia was significantly related to decreased overall survival (p = 0.003).The nomogram including sarcopenia status, resection style and mitotic index had an excellent discrimination with C-index 0.794. The calibration curves represented a good accordance between the actual observation and nomogram prediction for overall survival. Decision curve analysis illustrated that the nomogram was helpful in clinic. CONCLUSIONS: We developed a nomogram based on sarcopenia to predict overall survival after resection of GISTs which is an effective and favorable prognostication tool.

The additional value of lung cancer screening program in identifying unrecognized diseases.

BACKGROUND: A systematic examination of low-dose CT (LDCT) scan, beside lung nodules, may disclose the presence of undiagnosed diseases, improving the efficacy and the cost/efficacy of these programs. The study was aimed at evaluating the association between LDCT scan findings and non-oncologic and oncologic diseases. METHODS: The LDCT scan of participants to the "Un Respiro per la vita"® lung cancer screening program were checked and abnormal findings, beside lung nodules, recorded. First admission to the acute care because of cardiovascular (CD), respiratory (RD) and oncological diseases (OD) in the following three years were retrieved. The association of LDCT scan abnormal findings with CD, RD and OD was assessed through univariable and multivariable logistic regression models. RESULTS: Mean age of 746 participants was 62 years (SD:5), 62% were male. 11 (1.5%) received a diagnosis of lung cancer. 16.1% participants were admitted to the acute care in the following three years: 8.6% for CD, 4.3% for RD and 5.2% for OD. Valve calcification (OR 2.02, p:0.02) and mucus plugs (OR 3.37, p:0.04) were positively associated with CD, while sub-pleural fibrosis had a protective role (OR 0.47, p:0.01). Lung nodules > 8 mm (OR 5.54, p: < 0.01), tracheal deviation (OR 6.04, p:0.01) and mucus plugs (OR 4.00, p:0.04) were positively associated with OD admissions. Centrilobular emphysema OR for RD admissions was 1.97 (p:0.06). CONCLUSIONS: The observed association between selected LDCT findings and ensuing CD, RD and OD suggests that the information potential of LCDT goes beyond the screening of lung cancer.

3D-Slicer Software-Assisted Neuroendoscopic Surgery in the Treatment of Hypertensive Cerebral Hemorrhage.

OBJECTIVE: To explore the 3D-slicer software-assisted endoscopic treatment for patients with hypertensive cerebral hemorrhage. METHODS: A total of 120 patients with hypertensive cerebral hemorrhage were selected and randomly divided into control group and 3D-slicer group with 60 cases each. Patients in the control group underwent traditional imaging positioning craniotomy, and patients in the 3D-slicer group underwent 3D-slicer followed by precision puncture treatment. In this paper, we evaluate the hematoma clearance rate, nerve function, ability of daily living, complication rate, and prognosis. RESULTS: The 3D-slicer group is better than the control group in various indicators. Compared with the control group, the 3D-slicer group has lower complications, slightly higher hematoma clearance rate, and better recovery of nerve function and daily living ability before and after surgery. The incidence of poor prognosis is low. CONCLUSION: The 3D-slicer software-assisted endoscopic treatment for patients with hypertensive intracerebral hemorrhage has a better hematoma clearance effect, which is beneficial to the patient's early recovery and reduces the damage to the brain nerve of the patient.

Compound W-Net with Fully Accumulative Residual Connections for Liver Segmentation Using CT Images.

Computed tomography (CT) is a common modality for liver diagnosis, treatment, and follow-up process. Providing accurate liver segmentation using CT images is a crucial step towards those tasks. In this paper, we propose a stacked 2-U-Nets model with three different types of skip connections. The proposed connections work to recover the loss of high-level features on the convolutional path of the first U-Net due to the pooling and the loss of low-level features during the upsampling path of the first U-Net. The skip connections concatenate all the features that are generated at the same level from the previous paths to the inputs of the convolutional layers in both paths of the second U-Net in a densely connected manner. We implement two versions of the model with different number of filters at each level of each U-Net by maximising the Dice similarity between the predicted liver region and that of the ground truth. The proposed models were trained with 3Dircadb public dataset that were released for Sliver and 3D liver and tumour segmentation challenges during MICCAI 2007-2008 challenge. The experimental results show that the proposed model outperformed the original U-Net and 2-U-Nets variants, and is comparable to the state-of-the-art mU-Net, DC U-Net, and Cascaded UNET.

Artificial Intelligence Algorithm-Based MRI in Evaluating the Treatment Effect of Acute Cerebral Infarction.

The study is aimed at exploring the application of artificial intelligence algorithm-based magnetic resonance imaging (MRI) in the diagnosis of acute cerebral infarction, expected to provide a reference for diagnosis and effect evaluation of acute cerebral infarction. In this study, 80 patients diagnosed with suspected acute cerebral infarction per Diagnostic Criteria for Cerebral Infarction were selected as the research subjects. MRI images were reconstructed by deep dictionary learning to improve their recognition ability. At the same time, the same diagnostic operation was performed by Computed Tomography (CT) images to compare with MRI. The results of the interalgorithm comparison showed the image reconstruction effect of the deep dictionary learning model is significantly better than SAE reconstruction, single-layer dictionary reconstruction model, and KAVD reconstruction. After comparison, the results of MRI based on artificial intelligence algorithm and CT evaluation were statistically significant (P < 0.05). In the lesion image, the diameter of MRI lesions (3.81 ± 0.77 cm) based on artificial intelligence algorithm and the diameter of lesions in CT (3.66 ± 1.65 cm) also had significant statistical significance (P < 0.05). The results showed that MRI based on deep learning was more sensitive than CT imaging for diagnosis and evaluation of patients with acute cerebral infarction, with only 1 case misdiagnosed. The rate of disease detection and lesion image quality had a higher improvement. The results can provide effective support for the clinical application of MRI based on artificial intelligence algorithm in the diagnosis of acute cerebral infarction.

Defining reference values for low skeletal muscle index at the L3 vertebra level based on computed tomography in healthy adults: A multicentre study.

BACKGROUND & AIMS: Skeletal muscle mass loss is an important aspect of malnutrition and is closely related to adverse clinical outcomes. Computed tomography (CT) is the gold standard for analysing muscle mass, and the skeletal muscle index at the third lumbar vertebra (L3-SMI), measured using CT, is an important indicator to evaluate total skeletal tissue. The aims of this study were to establish reference values for low L3-SMI in Northern China, and to investigate the correlation between L3-SMI and age, and the correlation between L3-SMI and body mass index (BMI). METHODS: This was a multicentre, retrospective, cross-sectional study. A search of abdominal CT imaging reports, using specific keywords, was conducted in four representative cities in northern China, from January 2016 to March 2021. Transverse CT images at the level of the third lumbar vertebra (L3) were identified, exported from the Radiology Information System, and measured using the analysis software SliceOmatic. Statistical analyses were performed using SPSS 24.0, and significance level was set at p < 0.05. Mean, standard deviations (SD) and percentiles (p5, p10, p25, p50, p75, p90, p95) were used to describe the distribution of L3-SMI in the study population. Low skeletal muscle index was defined as a 5% percentile, or two standard deviations below the mean value of younger healthy individuals (age 20-39 years). RESULTS: The study included 1787 healthy individuals, with a median age of 45 (25) years (range 20-88 years), and a median BMI of 23.1 (4.1) kg/m2 (range 18.5-38.7 kg/m2). Among them, 700 healthy individuals (39.1%) were aged 20-39 years. L3-SMI had a negative linear correlation with age, and a positive linear correlation with BMI. The L3-SMI reference values used to define low skeletal muscle mass loss in the Northern Chinese population, using the 5% percentile, were 40.2 cm2/m2 in men, and 31.6 cm2/m2 in women. Using the mean minus two standard deviations protocol, the reference values were 37.9 cm2/m2 and 28.6 cm2/m2 in men and women, respectively. CONCLUSIONS: This study analysed the human body composition of 1787 healthy people in four cities in northern China, using CT, and established diagnostic thresholds of skeletal muscle mass depletion based on 700 younger healthy adults, using the 5% percentile and mean-2SD methods. These reference values can be used to diagnose malnutrition in patients and may aide clinicians in predicting prognosis and improving nutritional therapy. Further research is warranted to determine the prognostic role of reference values against clinical outcomes in different disease populations.

Clinical impact of allergy and pre-medication in CT studies with low-osmolality intravenous iodinated contrast media.

AIM: To evaluate the occurrence and severity of allergic reactions to iodinated contrast media (ICM), including associated risk factors and the impact of pre-medication. MATERIALS AND METHODS: Data on patients who had experienced allergic reactions during outpatient computed tomography (CT) examinations between January 2014 and September 2018 were analysed retrospectively. Response severity was assessed according to validated criteria. A control group was selected among individuals who underwent CT during the study period and did not experience allergic reactions. RESULTS: Screening of 36,920 CT studies revealed 74 (0.2%) individuals with systemic reactions to ICM. No significant differences in patient characteristics were found among patients who experienced mild (n=54), moderate (n=17), or severe (n=4) reactions. Previous ICM allergy was reported in 10 patients (13.3%). Patients with a history of ICM allergy had mild (9/10) or moderate (1/10) reactions, with one individual showing decreased intensity of the allergic response compared to a previous event. Within the control group, four patients (4%) had previous ICM allergy. In these individuals, lack of allergic reactions could not be attributed to pre-medication. All patients with severe reactions did not have a prior history of ICM allergy. CONCLUSION: Severe allergic reactions to ICM are rare, lack significant risk factors, and do not appear to be impacted by pre-medication. The findings presented herein highlight the need for prospective work that will re-evaluate the yield of pre-medication protocols.

Deep Learning-Based Chest CT Image Features in Diagnosis of Lung Cancer.

This study was to evaluate the diagnostic value of deep learning-optimized chest CT in the patients with lung cancer. 90 patients who were diagnosed with lung cancer by surgery or puncture in hospital were selected as the research subjects. The Mask Region Convolutional Neural Network (Mask-RCNN) model was a typical end-to-end image segmentation model, and Dual Path Network (DPN) was used in nodule detection. The results showed that the accuracy of DPN algorithm model in detecting lung lesions in lung cancer patients was 88.74%, the accuracy of CT diagnosis of lung cancer was 88.37%, the sensitivity was 82.91%, and the specificity was 87.43%. Deep learning-based CT examination combined with serum tumor detection, factoring into Neurospecific enolase (N S E), cytokeratin 19 fragment (CYFRA21), Carcinoembryonic antigen (CEA), and squamous cell carcinoma (SCC) antigen, improved the accuracy to 97.94%, the sensitivity to 98.12%, and the specificity to 100%, all showing significant differences (P < 0.05). In conclusion, this study provides a scientific basis for improving the diagnostic efficiency of CT imaging in lung cancer and theoretical support for subsequent lung cancer diagnosis and treatment.

Detecting COVID-19 Pneumonia over Fuzzy Image Enhancement on Computed Tomography Images.

COVID-19 is the worst pandemic that has hit the globe in recent history, causing an increase in deaths. As a result of this pandemic, a number of research interests emerged in several fields such as medicine, health informatics, medical imaging, artificial intelligence and social sciences. Lung infection or pneumonia is the regular complication of COVID-19, and Reverse Transcription Polymerase Chain Reaction (RT-PCR) and computed tomography (CT) have played important roles to diagnose the disease. This research proposes an image enhancement method employing fuzzy expected value to improve the quality of the image for the detection of COVID-19 pneumonia. The principal objective of this research is to detect COVID-19 in patients using CT scan images collected from different sources, which include patients suffering from pneumonia and healthy people. The method is based on fuzzy histogram equalization and is organized with the improvement of the image contrast using fuzzy normalized histogram of the image. The effectiveness of the algorithm has been justified over several experiments on different features of CT images of lung for COVID-19 patients, like Ground-Glass Opacity (GGO), crazy paving, and consolidation. Experimental investigations indicate that among the 254 patients, 81.89% had features on both lungs; 9.5% on the left lung; and 10.24% on the right lung. The predominantly affected lobe was the right lower lobe (79.53%).