Computed Tomography Features Research Articles

CT Characteristics and Clinical Findings of Bronchopneumonia Caused by Pepper Aspiration.

To explore the computed tomography (CT) features of bronchopneumonia caused by pepper aspiration to improve the diagnosis. 28 adult patients diagnosed with obstructive pneumonia caused by pepper aspiration from January 2016 to September 2022 were enrolled. The CT characteristics of bronchial changes and pulmonary lesions caused by pepper were analyzed and summarized. Among 28 patients, the most common symptom was cough (26, 92.9%), followed by expectoration (23, 82.1%). Bronchoscopy revealed that peppers were mainly found in the bronchus of the right lower lobe (n = 18, 64.3%), followed by the bronchus of the left lower lobe (n = 5, 17.9%). In combination with bronchoscopy results, the pepper in the bronchus manifested as circular or V/U-shaped high-density, localized soft tissue, and flocculent opacification in 8 (28.6%), 16 (57.1%), and 3 (10.7%) cases on CT images, respectively. The bronchial wall around the pepper was thickened with localized occlusion (n = 19, 67.9%) and stenosis (n = 9, 32.1%). Regarding adjacent bronchi without peppers, extensive wall thickening with stenosis and/or occlusion was found in 23 (82.1%) cases. Distal pulmonary lesions frequently involved two or three segments (21, 75.0%) and mainly presented as patchy consolidation or atelectasis (24, 85.7%). In combination to a history of eating peppers and clinical symptoms, bronchopneumonia caused by pepper should be highly suspected if U/V-shaped and annular high-density or localized soft tissue density is detected in the bronchi of the lower lobes, accompanied by extensive bronchial wall thickening, stenosis, or occlusion, and consolidation or atelectasis in multiple distal lung segments.

Comparison of Computed Tomography and Clinical Features Between Patients Infected with the SARS-CoV-2 Omicron Variant and the Original Strain.

To investigate potential differences in clinical and computed tomography (CT) features between patients with the SARS-CoV-2 Omicron variant and the original strain. This retrospective study included 69 hospitalized patients infected with Omicron variant from November to December 2022, and 96 hospitalized patients infected with the original strain from February to March 2020 in Chongqing, China. The clinical features, CT manifestations, degrees of lung involvement in different stages on CT, and imaging changes after the reverse-transcription polymerase chain reaction (RT-PCR) results turned negative were compared between the two groups. For clinical features, patients with Omicron were predominantly old people and females, without manifestation of any clinical symptoms, who had low serum levels of C-reactive protein and procalcitonin. Shorter interval from symptoms onset to initial CT scan was observed in Omicron patients compared to patients with the original strain (all P < 0.05). For CT features, patients with Omicron were more likely to present with round-like opacities and tree-in-bud pattern (all P < 0.05), but less likely to exhibit a diffuse distribution, patchy and linear opacities, as well as vascular enlargement pattern (all P < 0.05). The Omicron group was more susceptible to exhibiting lower CT involvement scores in each stage (all P < 0.05) and imaging progression after the RT-PCR results turned negative (P < 0.001). Patients infected with the Omicron variant exhibited less severe changes on chest CT compared to those infected with the original strain. Furthermore, imaging progression under low viral load conditions was more common in patients with Omicron than in those with the original strain.

A Case of Sarcoidosis and Galaxy Sign: Diagnostic Dilemma

The galaxy sign was first reported in pulmonary sarcoidosis. From those reports sign became known as one of the characteristic computed tomography (CT) findings of sarcoidosis. Notable feature of Galaxy sign is dense central portions surrounded by partially discrete small nodules. These nodules contain caseating or non‐caseating granulomas. Galaxy sign is considered useful signs indicative of pulmonary sarcoidosis. However, pulmonary tuberculosis may also show this finding. We report a patient who mimic pulmonary tuberculosis in our case. Clinicians should be aware to differentiate and evaluate further before starting treatment for pulmonary tuberculosis in these patients.

Use of Computed Tomography-Based Texture Analysis to Differentiate Benign From Malignant Salivary Gland Lesions.

Salivary gland lesions show overlapping morphological findings and types of time/intensity curves. This research aimed to evaluate the role of 2-phase multislice spiral computed tomography (MSCT) texture analysis in differentiating between benign and malignant salivary gland lesions. In this prospective study, MSCT was carried out on 90 patients. Each lesion was segmented on axial computed tomography (CT) images manually, and 33 texture features and morphological CT features were assessed. Logistic regression analysis was used to confirm predictors of malignancy ( P < 0.05 was considered to be statistically significant), followed by receiver operating characteristics analysis to assess the diagnostic performance. Univariate logistic regression analysis revealed that morphological CT features (shape, size, and invasion of adjacent tissues) and 17 CT texture parameters had significant differences between benign and malignant lesions ( P < 0.05). Multivariate binary logistic regression demonstrated that shape, invasion of adjacent tissues, entropy, and inverse difference moment were independent factors for malignant tumors. The diagnostic accuracy values of multivariate binary logistic models based on morphological parameters, CT texture features, and a combination of both were 87.8%, 90%, and 93.3%, respectively. Two-phase MSCT texture analysis was conducive to differentiating between malignant and benign neoplasms in the salivary gland, especially when combined with morphological CT features.

Subtle pulmonary interstitial emphysema in attempted suicide by ingestion of a cleaning product: Computed Tomography features

AbstractPulmonary interstitial emphysema (PIE) is a rare condition most commonly encountered in mechanically ventilated patients, either infants or adults. This condition can also be diagnosed in blunt chest trauma or other conditions while performing Valsalva-like maneuvers and is often associated with pneumothorax and subcutaneous emphysema. We present the case of a patient with subtle PIE, subcutaneous emphysema and massive pneumomediastinum after protracted vomiting following a suicidal attempt by caustic ingestion. Radiologists should be aware of the potentially subtle Computed Tomography features of PIE in order to make the correct diagnosis and rule out other tracheobronchial and esophageal injuries.

Computed tomography and magnetic resonance imaging features of suspected transitional cell carcinoma lesions involving the bladder, prostate, and urethra in a dog: a case report

A 14-year-old, spayed female, poodle was presented with dysuria and hematuria. A mass that appeared hypoechoic on ultrasound and hypoattenuating on computed tomography (CT) extended from the bladder neck to the urethra. Magnetic resonance imaging (MRI) showed the mass invading the muscular layer of the bladder, urethra, and prostate with distinct margins. Transitional cell carcinoma (TCC) was confirmed with the CADET-BRAF test. This study describes the CT and MRI features of suspected TCC lesions involving the bladder, prostate, and urethra. MRI showed superior soft tissue contrast resolution, enabling evaluation of invasion of the muscular layer of the bladder and urethra.

Machine learning assisted feature identification and prediction of hemodynamic endpoints using computed tomography in patients with CTEPH.

Chronic thromboembolic pulmonary hypertension (CTEPH) is a rare but potentially curable cause of pulmonary hypertension (PH). Currently PH is diagnosed by right heart catheterisation. Computed tomography (CT) is used for ruling out other causes and operative planning. This study aims to evaluate importance of different quantitative/qualitative imaging features and develop a supervised machine learning (ML) model to predict hemodynamic risk groups. 127 Patients with diagnosed CTEPH who received preoperative right heart catheterization and thoracic CTA examinations (39 ECG-gated; 88 non-ECG gated) were included. 19 qualitative/quantitative imaging features and 3 hemodynamic parameters [mean pulmonary artery pressure, right atrial pressure (RAP), pulmonary artery oxygen saturation (PA SaO2)] were gathered. Diameter-based CT features were measured in axial and adjusted multiplane reconstructions (MPR). Univariate analysis was performed for qualitative and quantitative features. A random forest algorithm was trained on imaging features to predict hemodynamic risk groups. Feature importance was calculated for all models. Qualitative and quantitative parameters showed no significant differences between ECG and non-ECG gated CTs. Depending on reconstruction plane, five quantitative features were significantly different, but mean absolute difference between parameters (MPR vs. axial) was 0.3mm with no difference in correlation with hemodynamic parameters. Univariate analysis showed moderate to strong correlation for multiple imaging features with hemodynamic parameters. The model achieved an AUC score of 0.82 for the mPAP based risk stratification and 0.74 for the PA SaO2 risk stratification. Contrast agent retention in hepatic vein, mosaic attenuation pattern and the ratio right atrium/left ventricle were the most important features among other parameters. Quantitative and qualitative imaging features of reconstructions correlate with hemodynamic parameters in preoperative CTEPH patients-regardless of MPR adaption. Machine learning based analysis of preoperative imaging features can be used for non-invasive risk stratification. Qualitative features seem to be more important than previously anticipated.

Chest Computed Tomography Characteristics of Critically Ill COVID-19 Patients with Auto-antibodies Against Type I Interferons

PurposePatients with auto-antibodies neutralizing type I interferons (anti-IFN auto-Abs) are at risk of severe forms of coronavirus disease 19 (COVID-19). The chest computed tomography (CT) scan characteristics of critically ill COVID-19 patients harboring these auto-Abs have never been reported.MethodsBicentric ancillary study of the ANTICOV study (observational prospective cohort of severe COVID-19 patients admitted to the intensive care unit (ICU) for hypoxemic acute respiratory failure between March 2020 and May 2021) on chest CT scan characteristics (severity score, parenchymal, pleural, vascular patterns). Anti-IFN auto-Abs were detected using a luciferase neutralization reporting assay. Imaging data were collected through independent blinded reading of two thoracic radiologists of chest CT studies performed at ICU admission (± 72 h). The primary outcome measure was the evaluation of severity by the total severity score (TSS) and the CT severity score (CTSS) according to the presence or absence of anti-IFN auto-Abs.ResultsTwo hundred thirty-one critically ill COVID-19 patients were included in the study (mean age 59.5 ± 12.7 years; males 74.6%). Day 90 mortality was 29.5% (n = 72/244). There was a trend towards more severe radiological lesions in patients with anti-IFN auto-Abs than in others, not reaching statistical significance (median CTSS 27.5 (21.0–34.8) versus 24.0 (19.0–30.0), p = 0.052; median TSS 14.5 (10.2–17.0) versus 12.0 (9.0–15.0), p = 0.070). The extra-parenchymal evaluation found no difference in the proportion of patients with pleural effusion, mediastinal lymphadenopathy, or thymal abnormalities in the two populations. The prevalence of pulmonary embolism was not significantly different between groups (8.7% versus 5.3%, p = 0.623, n = 175).ConclusionThere was no significant difference in disease severity as evaluated by chest CT in severe COVID-19 patients admitted to the ICU for hypoxemic acute respiratory failure with or without anti-IFN auto-Abs.

CT findings in idiopathic myointimal hyperplasia of mesenteric veins (IMHMV) and comparison to other colitides.

The purpose of this study is to determine computed tomography (CT) findings that aid in differentiating idiopathic myointimal hyperplasia of mesenteric veins (IMHMV) from other colitides. Retrospective review of histiologic proven cases of IMHMV (n = 12) with contrast enhanced CT (n = 11) and/or computed tomography angiography (CTA) (n = 9) exams. Control groups comprised of CT of infectious colitis (n = 13), CT of inflammatory bowel disease (IBD) (n = 12), and CTA of other colitides (n = 13). CT exams reviewed by 2 blinded gastrointestinal radiologists for maximum bowel wall thickness, enhancement pattern, decreased bowel wall enhancement, submucosal attenuation value, presence and location of IMV occlusion, peripheral mesenteric venous occlusion, dilated pericolonic veins, subjective IMA dilation, maximum IMA diameter, maximum peripheral IMA branch diameter, ascites, and mesenteric edema. Presence of early filling veins was an additional finding evaluated on CTA exams. Statistically significant CT findings of IMHMV compared to control groups included greater maximum bowel wall thickness, decreased bowel enhancement, IMV occlusion, and peripheral mesenteric venous occlusion (p < 0.05). Dilated pericolonic veins were seen more frequently in IMHMV compared to the infectious colitis group (64% versus 15%, p = 0.02). Additional statistically significant finding on CTA included early filling veins in IMHMV compared to the CTA control group (100% versus 46%, p = 0.008). IMHMV is a rare chronic non-thrombotic ischemia predominantly involving the rectosigmoid colon. CT features that may aid in differentiating IMHMV from other causes of left-sided colitis include marked bowel wall thickening with decreased enhancement, IMV and peripheral mesenteric venous occlusion or tapering, and early filling of dilated veins on CTA.

Krukenberg Tumors in Young Women: Computed Tomography and Magnetic Resonance Imaging Diagnosis.

The purpose of this report was to present the computed tomography (CT) and magnetic resonance imaging (MRI) features of Krukenberg tumors and to review the pertinent clinical data about the rising incidence of this malignancy among young women. This series included 8 women who ranged in age from 24 to 44 years (mean, 36.3 years). They were diagnosed to have Krukenberg tumors during a 5-year period (2011-2016). All patients were evaluated by abdominal CT and pelvic or transvaginal sonography. Five of them also had MRI of the abdomen, and 3 had positron emission tomography scans. The primary cancer was located in the stomach of 7 patients and in the colon in 1. The initial presentation was due to large pelvic mass and abdominal distention by ascites in 3 patients, gastrointestinal symptoms in 4, and small bowel obstruction by carcinoma of the ascending colon in 1 woman. Ovarian metastases were demonstrated on the initial imaging examination of 5 patients and developed as metachronous lesion during follow-up in 3 cases. Six women died 3 to 23 months (mean, 11 months) after the diagnosis. One has survived for 6 years after extensive surgery, and 1 was lost to follow-up. Krukenberg tumors are being diagnosed with an increasing frequency because of well-documented rising incidence of gastric and colorectal carcinomas among young women. Therefore, those presenting with gastrointestinal cancer should have careful imaging of their ovaries for possible metastases, and conversely, the clinical or sonographic detection of bilateral ovarian masses would require evaluation by CT or MRI of the abdomen in search for a potential primary gastrointestinal cancer. This report highlights the CT and MRI features of this neoplastic process and reviews the current concepts about its development and management.

CT target scanning in the diagnosis of solid pseudopapillary tumor of the pancreas

ObjectiveTo discuss the value of computed tomography (CT) iterative reconstruction technique combined with target scanning in the diagnosis of solid pseudopapillary tumor of the pancreas (SPTP).MethodsThe clinical information and CT examination data of 27 patients with SPTP were retrospectively analyzed, and the general condition and CT performance of the patients were observed. The CT image reconstruction algorithm of all patients used iterative reconstruction technique combined with the application of target scanning technique.ResultsA total of 27 patients were included in this study, including 6 males and 21 females, aged 14–72 years with a mean age of 39.6 ± 13.6 years. SPTP was more common in young and middle-aged females, with a low level of tumor markers, dominated by cystic-solid tumors. The combination of CT iterative reconstruction technology and targeted scanning revealed the following: the capsule of SPTP was clear and complete, where calcifications were visible, solid components were progressively enhanced, and rare pancreatic and bile duct dilation was seen. Tumors were cystic-solid in 18 of 27 patients with SPTP, of which the solid components showed isodensity or slightly low-density, with calcifications. The solid components and cyst walls were mildly enhanced during the arterial phase, and were progressively enhanced during the parenchymal phase, portal vein phase, and delayed phase, with their enhancement degree lower than that of normal pancreatic parenchyma, and pancreatic and bile duct dilation was rare. There were no statistical differences in tumor location, morphology, growth pattern, integrity of capsule, cystic or solid, calcifications, and enhancement features between the male group and the female group (P > 0.05).ConclusionThe iterative reconstruction combined with target scanning clearly displayed the CT features of tumors, helping the diagnosis and clinical treatment of the disease.

Correlation between chest computed tomography findings and pulmonary function test results in the post-recovery phase of COVID-19.

The radiological and functional lung sequelae in COVID-19 survivors remain unclear. We compared the chest computed tomography findings of COVID-19 patients with normal and abnormal pulmonary function test results in the post-recovery phase. The data of consecutive patients who underwent pulmonary function tests and chest computed tomography within 14 days after recovery from COVID-19 at two medical centers between May and October 2020 were collected retrospectively. Two thoracic radiologists who were blinded to the clinical information and pulmonary function test results classified the patients according to the computed tomography features, evidence of fibrotic-like changes, and semi-quantitative quantification of the extent of pulmonary abnormalities. The clinical characteristics and computed tomography findings of patients with normal pulmonary function test results were compared with those of patients with abnormal results. A total of 101 COVID-19 survivors, comprising 48 ambulatory and 53 hospitalized patients, were included at a median of 95 days from initial symptom onset. Computed tomography revealed fibrotic-like changes in 10.9% of patients. A reduction in the diffusion capacity of carbon monoxide was the most common lung function abnormality (19.8%). Abnormal diffusion capacity of carbon monoxide was associated with the presence and extension of lung opacities on chest computed tomography scans and fibrotic pulmonary abnormalities. The sensitivity, specificity, and accuracy of reduced diffusion capacity of carbon monoxide for detecting fibrotic-like pulmonary changes on chest computed tomography scans were 72.7%, 87.8%, and 86.1%, respectively. Our study suggests that the presence of an abnormal diffusion capacity of carbon monoxide in the post-recovery phase of COVID-19 is associated with a greater risk of long-term parenchymal lung disease, as evidenced by the presence of fibrotic-like changes on chest computed tomography scans, such as traction bronchiectasis and architectural distortion.

Possibility of Using Conventional Computed Tomography Features and Histogram Texture Analysis Parameters as Imaging Biomarkers for Preoperative Prediction of High-Risk Gastrointestinal Stromal Tumors of the Stomach.

The objective of this study is to determine the morphological computed tomography features of the tumor and texture analysis parameters, which may be a useful diagnostic tool for the preoperative prediction of high-risk gastrointestinal stromal tumors (HR GISTs). This is a prospective cohort study that was carried out in the period from 2019 to 2022. The study included 79 patients who underwent CT examination, texture analysis, surgical resection of a lesion that was suspicious for GIST as well as pathohistological and immunohistochemical analysis. Textural analysis pointed out min norm (p = 0.032) as a histogram parameter that significantly differed between HR and LR GISTs, while min norm (p = 0.007), skewness (p = 0.035) and kurtosis (p = 0.003) showed significant differences between high-grade and low-grade tumors. Univariate regression analysis identified tumor diameter, margin appearance, growth pattern, lesion shape, structure, mucosal continuity, enlarged peri- and intra-tumoral feeding or draining vessel (EFDV) and max norm as significant predictive factors for HR GISTs. Interrupted mucosa (p < 0.001) and presence of EFDV (p < 0.001) were obtained by multivariate regression analysis as independent predictive factors of high-risk GISTs with an AUC of 0.878 (CI: 0.797-0.959), sensitivity of 94%, specificity of 77% and accuracy of 88%. This result shows that morphological CT features of GIST are of great importance in the prediction of non-invasive preoperative metastatic risk. The incorporation of texture analysis into basic imaging protocols may further improve the preoperative assessment of risk stratification.

Pulmonary extranodal natural killer/T-cell lymphoma: clinical presentation, CT characteristics, and patient outcomes.

Due to the extreme rarity of pulmonary extranodal natural killer/T-cell lymphoma (ENKTCL), studies on this lymphoma type are limited. We aimed to investigate the clinical presentations, computed tomography (CT) findings, CT dynamic changes, and outcomes of patients diagnosed with pulmonary ENKTCL. We conducted a retrospective cohort study on ENKTCL, nasal type, at West China Hospital, from January 2010 to January 2023. Out of 27 initial cases with pulmonary ENKTCL, we excluded 4 due to the lack of chest CT images, resulting in a final cohort of 23 patients. Our evaluation covered clinical features, laboratory findings, CT presentations, treatment strategies, and survival outcomes. Survival analyses were performed using the Kaplan-Meier method, with log-rank tests for survival curve comparisons. Given the small sample size, our interpretation of the data is mainly descriptive. The most common CT presentations in our institution was solitary or multiple nodules (7/23, 30.4%). The halo sign (78.3%) and floating vessels sign (83.3%) were commonly observed in pulmonary ENKTCL. Elevated lactate dehydrogenase (LDH) levels were observed in 20 (86.9%) patients. The median overall survival (OS) for pulmonary ENKTCL patients was 1 month; 3 cases displayed a favorable prognosis, maintaining complete remission (CR) status for 1.5-7 years after receiving chemotherapy. Chemotherapy led to improved prognosis, with a median survival of 5 months seen in patients who received chemotherapy. Patients with bilateral lung involvement had worse outcomes compared to those with unilateral lesions. Pulmonary ENKTCL is a rare and aggressive disease, often misdiagnosed due to nonspecific clinical and CT features. Laboratory tests, failure of antibiotic treatment, and "floating vessels sign" on enhanced CT scans may aid in diagnosis. Timely chemotherapy may improve survival, emphasizing the importance of early detection and prompt treatment.

Clinicopathological and computed tomography features associated with recurrence-free survival of patients with small-sized peripheral invasive lung adenocarcinoma after sublobectomy.

Sublobar resection is gradually becoming a standard treatment for small-sized (≤2 cm) peripheral non-small cell lung cancer (NSCLC), with lung adenocarcinoma (LADC) being the most frequent histologic subtype. However, the prognostic predictors for preoperatively determining whether sublobectomy is feasible for patients with early LADC have not yet been well identified. Therefore, this study aimed to investigate the clinicopathological and computed tomography (CT) features associated with the recurrence-free survival (RFS) of patients with small-sized invasive LADC (SILADC) after sublobar resection. This retrospective cohort study analyzed 107 patients with SILADC who underwent preoperative chest CT scan and sublobar resection from December 2012 to March 2019. The Kaplan-Meier survival was used to analyze the relationship between clinicopathological characteristics, preoperative chest CT findings, and RFS. The Cox proportional hazards regression was used to identify independent prognostic factors of poor RFS. For clinicopathological characteristics, RFS was shorter in patients aged ≥70 years, smokers, and those with micropapillary/solid-predominant adenocarcinomas (all P values <0.05). For preoperative CT features, RFS was shorter in patients with tumor size ≥1.4 cm, solid component size ≥1.1 cm, proportion of solid component ≥72%, solid density, spiculation, vascular convergence sign, peripheral fibrosis, and type II pleural tag (all P values <0.05). Multivariate analysis showed proportion of solid component ≥72% [hazard ratio (HR): 5.920; P=0.006; 95% confidence interval (CI): 1.686-20.794], spiculation (HR: 5.026; P=0.001; 95% CI: 2.008-12.581), and type II pleural tag (HR: 4.638; P=0.002; 95% CI: 1.773-12.136) were independent risk factors for poor prognosis in patients with SILADC after sub-lobectomy. Clinicopathological and CT characteristics are helpful for predicting the RFS of patients with SILADC after sublobar resection and can be used as an auxiliary tool for thoracic surgeons to choose the best surgical mode.

Transbronchial cryobiopsy using an ultrathin cryoprobe with a guide sheath for the diagnosis of pulmonary mucosa-associated lymphoid tissue lymphoma.

Pulmonary mucosa-associated lymphoid tissue (MALT) lymphoma is difficult to diagnose and relatively rare. Tissue sampling through transbronchial biopsy is often inadequate, necessitating surgical lung biopsy. However, a recently developed technique, transbronchial lung cryobiopsy (TBLC), has shown promise for obtaining larger specimens. A 1.1 mm cryoprobe has recently become available, and its usefulness has been increasingly reported. Use of a conventional cryoprobe for TBLC in diagnosing pulmonary MALT lymphoma has been previously reported; however, there are no reports on the use of a 1.1 mm ultrathin cryoprobe and guide sheath (GS). We aimed to assess the effectiveness and safety of using a 1.1 mm ultrathin cryoprobe in combination with a GS for diagnosing pulmonary MALT lymphoma using a simpler and safer method. We retrospectively analyzed the findings for four patients showing characteristic computed tomography (CT) findings of MALT lymphoma, including peripheral pulmonary lesions, air bronchogram nodules, and bronchiectasis, at our hospital. Each patient underwent endobronchial ultrasound (EBUS) with a GS, followed by TBLC using a 1.1 mm cryoprobe. Morphological diagnosis, immunohistochemical examination, and molecular testing were performed on the biopsy specimens to establish the diagnosis. Complications during the procedure were also monitored. We obtained 8-16 biopsy specimens in all four cases using a cryoprobe. Histopathological analysis of two cases revealed the infiltration of small lymphocytes with numerous lymphoepithelial lesions, confirming MALT lymphoma. Immunohistochemical examination further demonstrated B-cell lymphocyte proliferation and light-chain restriction, confirming monoclonality and providing a definitive diagnosis. In the remaining two cases, histopathological evidence of pulmonary MALT lymphoma was lacking. However, molecular testing using polymerase chain reaction to analyze immunoglobulin gene rearrangements revealed B-cell clonality, which supported the diagnosis. Molecular testing proved particularly useful when histopathological diagnosis alone was inconclusive. No complications such as pneumothorax or hemorrhage occurred during the procedure. The combination of a GS and EBUS facilitated specimen collection at the same location as EBUS, with the GS providing compression hemostasis and eliminating the need for an additional hemostatic device. Therefore, TBLC with a GS is a useful and safe method for diagnosing pulmonary MALT lymphomas and reproducibly yielded sufficient quantities of good-quality biopsy specimens.

Machine Learning Model with Computed Tomography Radiomics and Clinicobiochemical Characteristics Predict the Subtypes of Patients with Primary Aldosteronism

Adrenal venous sampling (AVS) is the primary method for differentiating between primary aldosterone (PA) subtypes. The aim of study is to develop prediction models for subtyping of patients with PA using computed tomography (CT) radiomics and clinicobiochemical characteristics associated with PA. This study retrospectively enrolled 158 patients with PA who underwent AVS between January 2014 and March 2021. Neural network machine learning models were developed using a two-stage analysis of triple-phase abdominal CT and clinicobiochemical characteristics. In the first stage, the models were constructed to classify unilateral or bilateral PA; in the second stage, they were designed to determine the predominant side in patients with unilateral PA. The final proposed model combined the best-performing models from both stages. The model's performance was evaluated using repeated stratified five-fold cross-validation. We employed paired t-tests to compare its performance with the conventional imaging evaluations made by radiologists, which categorize patients as either having bilateral PA or unilateral PA on one side. In the first stage, the integrated model that combines CT radiomic and clinicobiochemical characteristics exhibited the highest performance, surpassing both the radiomic-alone and clinicobiochemical-alone models. It achieved an accuracy and F1 score of 80.6%±3.0% and 74.8%±5.2% (area under the receiver operating curve [AUC] = 0.778±0.050). In the second stage, the accuracy and F1 score of the radiomic-based model were 88%±4.9% and 81.9%±6.2% (AUC=0.831±0.087). The proposed model achieved an accuracy and F1 score of 77.5%±3.9% and 70.5%±7.1% (AUC=0.771±0.046) in subtype diagnosis and lateralization, surpassing the accuracy and F1 score achieved by radiologists' evaluation (p<.05). The proposed machine learning model can predict the subtypes and lateralization of PA. It yields superior results compared toconventional imaging evaluation and has potential to supplement the diagnostic process in PA.

CT Findings of Stage IA Ovarian Cancer: Comparison between Borderline Tumor and Stage IC Ovarian Cancer.

Ovarian cancer is a common gynecological malignant tumor in women. Most patients have reached the advanced stage when they visit the hospital. In order to diagnose ovarian cancer at an early stage, treat it at an early stage, and improve the survival rate of patients, this study has used the imaging computed tomography (CT) method to diagnose stage IA ovarian cancer. The purpose of this work was to study CT features of stage IA ovarian cancer, and compare the borderline tumor and stage IC ovarian cancer at the same time so as to improve the CT diagnosis of early ovarian cancer. We retrospectively collected clinical and CT data of patients with stage I ovarian cancer and borderline ovarian tumor admitted to Nantong Tumor Hospital from 2013 to 2021. Altogether, 23 cases of patients (borderline ovarian tumor, 9 cases; stage IA ovarian cancer, 5 cases; stage IC ovarian cancer, 9 cases) were involved. CT characteristics of these patients were analyzed in terms of the tumor diameter, cystic solid structure, solid component, septation, enhancement, peritoneal thickening, ascites, and abdominal lymph nodes. CT features of stage IA ovarian cancer included large tumor size (average diameter: 15 cm), cystic solid structure (4/5; 80%), septation (4/5; 80%), and enhanced cystic wall, septum, or solid components of the tumor on contrast-enhanced CT (5/5; 100%) no peritoneal thickening (0/5; 0%), no ascites (0/5; 0%), and no abdominal lymph node enlargement (0/5; 0%). The tumor structure did not differ significantly between stage IA and IC ovarian cancers (p > 0.05), while intraperitoneal ascites did (χ2 = 0.031; p < 0.05). Stage IA and borderline ovarian tumors did not differ significantly in ovarian tumor structure (p > 0.05). CT features of stage IA ovarian cancer included large tumor size, cystic solid structure, septation, and enhanced cystic wall and solid parts in the tumors. No pelvic or abdominal metastasis was observed.

The role of computed tomography features in assessing response to neoadjuvant chemotherapy in locally advanced gastric cancer

ObjectiveTo compare the computed tomography (CT) images of patients with locally advanced gastric cancer (GC) before and after neoadjuvant chemotherapy (NAC) in order to identify CT features that could predict pathological response to NAC.MethodsWe included patients with locally advanced GC who underwent gastrectomy after NAC from September 2016 to September 2021. We retrieved and collected the patients’ clinicopathological characteristics and CT images before and after NAC. We analyzed CT features that could differentiate responders from non-responders and established a logistic regression equation based on these features.ResultsWe included 97 patients (69 [71.1%] men; median [range] age, 60 [26–75] years) in this study, including 66 (68.0%) responders and 31 (32.0%) non-responders. No clinicopathological variable prior to treatment was significantly associated with pathological response. Out of 16 features, three features (ratio of tumor thickness reduction, ratio of reduction of primary tumor attenuation in arterial phase, and ratio of reduction of largest lymph node attenuation in venous phase) on logistic regression analysis were used to establish a regression equation that demonstrated good discrimination performance in predicting pathological response (area under receiver operating characteristic curve 0.955; 95% CI, 0.911–0.998).ConclusionLogistic regression equation based on three CT features can help predict the pathological response of patients with locally advanced GC to NAC.

Development and validation of a radiomics nomogram for diagnosis of malignant pleural effusion

ObjectiveWe aimed to develop a radiomics nomogram based on computed tomography (CT) scan features and high-throughput radiomics features for diagnosis of malignant pleural effusion (MPE).MethodsIn this study, 507 eligible patients with PE (207 malignant and 300 benign) were collected retrospectively. Patients were divided into training (n = 355) and validation cohorts (n = 152). Radiomics features were extracted from initial unenhanced CT images. CT scan features of PE were also collected. We used the variance threshold algorithm and least absolute shrinkage and selection operator (LASSO) to select optimal features to build a radiomics model for predicting the nature of PE. Univariate and multivariable logistic regression analyzes were used to identify significant independent factors associated with MPE, which were then included in the radiomics nomogram.ResultsA total of four CT features were retained as significant independent factors, including massive PE, obstructive atelectasis or pneumonia, pleural thickening > 10 mm, and pulmonary nodules and/or masses. The radiomics nomogram constructed from 13 radiomics parameters and four CT features showed good predictive efficacy in training cohort [area under the curve (AUC) = 0.926, 95% CI 0.894, 0.951] and validation cohort (AUC = 0.916, 95% CI 0.860, 0.955). The calibration curve and decision curve analysis showed that the nomogram helped differentiate MPE from benign pleural effusion (BPE) in clinical practice.ConclusionThis study presents a nomogram model incorporating CT scan features and radiomics features to help physicians differentiate MPE from BPE.