Rim Enhancement on Contrast-Enhanced CT as a Predictor of Prognosis in Patients with Pancreatic Ductal Adenocarcinoma

This study investigated the utility of imaging features, such as rim enhancement on contrast-enhanced CT (CECT), in predicting the prognosis of pancreatic ductal adenocarcinoma (PDAC). This retrospective study included 158 patients (84 men; mean age, 68 years) with pathologically confirmed PDAC. The following imaging features were evaluated on CECT by two radiologists: tumor size, tumor attenuation, and the presence of rim enhancement. Cox proportional hazards analysis was performed to identify the imaging and clinicopathological features for predicting disease-free survival (DFS) and overall survival (OS). Pathological features were compared with the presence of rim enhancement. Among the 158 patients, 106 (67%) underwent curative surgery (surgery group) and 52 (33%) received conservative treatment (non-surgery group). Rim enhancement was observed more frequently in the non-surgery group than in the surgery group (44% vs. 20%; p < 0.001). Rim enhancement showed significant associations with shorter DFS and OS in the surgery group (hazard ratios (HRs), 3.03 and 2.99; p < 0.001 and p = 0.003, respectively), whereas tumor size showed significant associations with shorter OS (HR per 1 mm increase, 1.08; p < 0.001). PDACs with rim enhancement showed significant associations with higher histological tumor grades (p < 0.001). PDAC with rim enhancement on CECT could predict poorer prognosis and more aggressive tumor grades.

Abdominal computed tomography and exploratory laparotomy have high agreement in dogs with surgical disease

OBJECTIVE

To compare the results of abdominal CT with exploratory laparotomy in the dog.

ANIMALS

100 client-owned dogs from 1 academic institution.

METHODS

Medical records were searched for dogs that had undergone a preoperative abdominal CT scan read by a board-certified veterinary radiologist followed by an exploratory laparotomy. CT and surgical reports were compared.

RESULTS

The overall agreement between abdominal CT scan and exploratory laparotomy in all cases was 97%. Overall, there was no evidence that proportion agreement differed on the basis of body condition score, time interval between CT and surgery, or oncologic versus nononcologic disease.

CLINICAL RELEVANCE

Abdominal CT scan read by a board-certified diplomate is a sensitive presurgical diagnostic tool for surgical abdominal disease in the dog. When performing a specific abdominal surgery, it is acceptable for the surgeon to fully explore the abdomen or forego it for a smaller approach to the organ of interest if an abdominal CT was performed prior.

Regional assessment of aortic valve calcification using topographic maps in contrast-enhanced CT: in-vivo sex and severity-based differences in calcific presentation

Background

Procedural planning for transcatheter aortic valve replacement (TAVR) is routinely performed using contrast computed tomography (CT) in patients with severe aortic stenosis (AS). Despite its potential, little investigation has been done into the possibility of aortic valve calcification (AVC) scoring in contrast-enhanced CT. Contrast CT has superior spatial and contrast resolution compared to the non-contrast Agatston score protocol, which would allow for development of better pattern and distribution descriptors of calcific lesions in the aortic valve (AV).

Methods

We developed a new false positive rate (FPR) based method that can quantify leaflet calcification based on shape overlap metrics. We also introduce a novel regional scheme for quantifying the shape and structure of calcification using topographic maps. The study was designed to: (I) determine the feasibility of using a novel method based on FPR to detect AVC using contrast-enhanced CT images by assessing the volume scores measured using FPR versus non-contrast methods and alternative contrast methods for volume scoring based on fixed or dynamic HU thresholds. (II) Develop a new scheme for assessing calcific geometry and structure and evaluate patterns of calcification in the varied presentation of AS.

Results

Our results show a very strong correlation with non-contrast volume (r=0.919, P<0.001; n=178) and Agatston scores (r=0.913, P<0.001; n=178) that were evaluated using a standard calcium scoring technique. Finally, we analyzed the differences and similarities in the patterns of calcific deposition with respect to sex and degree of severity.

Conclusions

The FPR method demonstrates the best overall agreement with non-contrast scores across both low and high ends of calcific density compared to luminal attenuation methods. In addition, we showed that leaflet calcific deposition follows distinctive patterns across the belly of the leaflet, with the rate of calcific progression peaking at the non-coronary cusp (NCC) leaflet and lowest for the right-coronary cusp. Females experience significantly lower calcific deposition compared to males despite showing similar patterns and symptoms. Our findings suggest that precise regional assessment of calcific progression could be an important tool for monitoring AS development as well as predicting peri-procedural complications in TAVR.

Extensive Skeletal Muscle Metastases in Malignant Pleural Mesothelioma Detected by FDG PET/CT

Malignant pleural mesothelioma (MPM) is a rare but aggressive tumor originating from pleural mesothelial cells. Distant skeletal muscle metastasis is rare in MPM. A 54-year-old woman was diagnosed with epithelioid MPM and treated with surgery, chemotherapy, and radiotherapy 2 years ago. During follow-up, diffuse irregular pleural thickening with focal chest wall invasion in the right hemithorax and two small pleural thickenings in the left hemithorax were seen on control diagnostic contrast-enhanced computed tomography (CECT). Fluorine-18 fluorodeoxyglucose positron emission tomography/CT (FDG PET/CT) imaging was performed as part of restaging. PET showed diffusely increased FDG uptake in the recurrent right pleural tumor, and two hypermetabolic small metastatic foci in the contralateral pleura. In addition, multiple hypermetabolic areas of various sizes in various skeletal muscle localizations, suggestive of extensive muscle metastases were noted. Histopathologic study confirmed metastatic epithelioid MPM. FDG PET/CT revealed multiple muscle metastases which were not observed on earlier CECT and contributed to the visualization of more extensive metastatic involvements in the presented case with MPM. FDG PET/CT can detect rarely seen skeletal muscle metastases that are not visualized on diagnostic CT, and provides more accurate restaging of MPM.

Virtual unenhanced images derived from dual-energy computed tomography for assessing bone mineral density and detecting osteoporosis

Background

The early detection and treatment of osteoporosis can help prevent osteoporosis-related fractures, especially in patients who undergo enhanced computed tomography (CT) scans for disease diagnosis or evaluation of treatment outcomes. Although Hounsfield unit (HU) measurement of the vertebral body has been shown to have a strong positive correlation with bone mineral density (BMD), the contrast media will impact the CT value of the vertebral body and decrease the accuracy. This study is aimed to examine the distinctions in vertebral body CT attenuation measurement on true unenhanced (TUE) and virtual unenhanced (VUE) images generated from triphasic enhanced dual-energy CT (DECT) scans and to determine the feasibility of assessing BMD and detecting osteoporosis on VUE images as compared to quantitative CT (QCT).

Methods

A total of 235 patients underwent abdominal CT examinations that included unenhanced (with 120 kVp and Smart mA) and triphasic enhanced DECT scans. The BMD and CT attenuation values of the L1-L2 vertebrae were measured on TUE and VUE images reconstructed from the triphasic enhanced CT. The differences and associations between TUE and VUE generated from triphasic enhanced CT were analyzed. The diagnostic performances of HU measurements obtained from TUE and VUE images were evaluated using receiver operating characteristic curve.

Results

The BMD and HU measurements of the vertebrae showed good interobserver repeatability on both TUE and VUE images (all intercorrelation coefficients >0.92). The CT attenuation values of L1 and L2 and their average value showed no statistically significant difference among the triphasic VUE images (F=0.121, F=0.061, F=0.090; all P values >0.05) but were significantly lower than those obtained from the TUE images. HU measurements in both the TUE and triphasic VUE images, along with the reference BMD derived from QCT, demonstrated a strong positive correlation (rTUE =0.981, rVUEa =0.966, rVUEv =0.962, rVUEd =0.964; all P values <0.05), with excellent diagnostic performance for the diagnoses of osteoporosis and osteopenia (all areas under curve >0.95). The Bland-Altman scatter plot exhibited good agreement, as the deviations between the reference BMD and the calculated BMD were evenly distributed around 0.

Conclusions

Although the attenuation values of the vertebrae on the VUE images were underestimated compared to those on the TUE images, the HU measurement on VUE image was effective in assessing BMD and detecting osteoporosis and osteopenia with good diagnostic performance.

CT-based radiomics model to predict spread through air space in resectable lung cancer

BACKGROUND

Spread through air space (STAS) has been identified as a pathological pattern associated with lung cancer progression. Patients with STAS were related to a worse prognosis compared with patients without STAS. The objective of this study was to establish a radiomics model capable of forecasting STAS before surgery, which can assist surgeons in selecting the most appropriate operation type for patients with STAS.

METHOD

There were 537 eligible patients retrospectively included in this study. ROI segmentation was performed manually on all CT images to identify the region of interest. From each segmented lesion, a total of 1688 features were extracted. The tumor size, maximum tumor diameters, and tumor type were also recorded. Using Spearman's correlation coefficient to calculate the correlation and redundancy of elements, and redundant features less than 0.80 were removed. In order to reduce the level of overfitting and avoid statistical biases, a dimension reduction process of the dataset was conducted to decrease the number of features. Finally, a radiomics model included 44 features was established to predict STAS. To evaluate the performance of the model, the receiver operating characteristic (ROC) curve was used, and the area under the curve (AUC) was calculated, and the accuracy of the model was verified by 10-fold cross-validation.

RESULTS

The incidence of STAS was 38.2% (205/537). The tumor type, maximum tumor diameters, and consolidation tumor ratio were significantly different between STAS group and non-STAS group. The training group included 430 patients, while the test group was consisted with 107. The training group achieved an AUC of 0.825 (sensitivity, 0.875; specificity, 0.621; and accuracy, 0.749) and the test group had an AUC of 0.802 (sensitivity, 0.797; specificity,0.688; and accuracy, 0.748). The 10-fold cross-validation had an AUC of 0.834.

CONCLUSION

CT-based radiomic model can predict STAS effectively, which is of great importance to guide the selection of operation types before surgery.

Association between acute adverse reactions to iodinated contrast media and anxiety in patients undergoing contrast-enhanced CT examination

OBJECTIVES

As the use of iodinated contrast media has become more widely with advances in imaging, several guidelines have suggested that anxiety increases the risk of acute adverse reactions associated with iodinated contrast media. This study aims to evaluate the impact of anxiety on the occurrence of acute adverse reactions (AAR) to iodinated contrast media in patients undergoing contrast-enhanced CT examinations.

METHODS

Inpatients who underwent contrast-enhanced CT examinations at the Third Xiangya Hospital between February and October 2021 were prospectively recruited. Prior to the imaging examinations, all patients completed the Generalized Anxiety Disorder Scale-7 (GAD-7) assessment before the imaging examinations to determine the severity of anxiety, which was categorized as mild, moderate, or severe. Based on the occurrence of AAR, patients were classified into an AAR group and a non-AAR group. The difference in anxiety was compared between the 2 groups. Multivariate logistic regression analysis was used to identify independent risk factors associated with AAR. To ensure comparability between the 2 groups, propensity score matching (PSM) was utilized to align the clinical characteristics. Subsequently, the difference in anxiety within the matched groups was analyzed.

RESULTS

The study comprised 880 patients, with 80 patients in the AAR group and 800 patients in the non-AAR group. There was a significant difference in proportion of patients with mild-severe anxiety between the 2 groups (75% in the AAR group and 36% in the non-AAR group, P<0.001). Additionally, differences were also observed in occupation, income, underlying diseases, and allergy history (all P<0.001). The results of multivariate logistic regression analysis revealed that patients' income, allergy history, and anxiety were independent risk factors for AAR to iodinated contrast media (all P<0.05). Following PSM, each matched group included 66 cases, and no significant differences in clinical characteristics were observed between the 2 groups (all P>0.05). However, the proportion of patients with mild-severe anxiety remained significantly higher in the AAR group compared to the non-AAR group (75% in the AAR group and 31% in the non-AAR group, P<0.001).

CONCLUSIONS

Anxiety is associated with an increased risk of AAR to iodinated contrast media in patients undergoing contrast-enhanced CT examinations, suggesting the clinical importance of screening for anxiety before imaging examinations.

A contrast-enhanced CT-based radiomic nomogram for the differential diagnosis of intravenous leiomyomatosis and uterine leiomyoma

Objective

Uterine intravenous leiomyomatosis (IVL) is a rare and unique leiomyoma that is difficult to surgery due to its ability to extend into intra- and extra-uterine vasculature. And it is difficult to differentiate from uterine leiomyoma (LM) by conventional CT scanning, which results in a large number of missed diagnoses. This study aimed to evaluate the utility of a contrast-enhanced CT-based radiomic nomogram for preoperative differentiation of IVL and LM.

Methods

124 patients (37 IVL and 87 LM) were retrospectively enrolled in the study. Radiomic features were extracted from contrast-enhanced CT before surgery. Clinical, radiomic, and combined models were developed using LightGBM (Light Gradient Boosting Machine) algorithm to differentiate IVL and LM. The clinical and radiomic signatures were integrated into a nomogram. The diagnostic performance of the models was evaluated using the area under the curve (AUC) and decision curve analysis (DCA).

Results

Clinical factors, such as symptoms, menopausal status, age, and selected imaging features, were found to have significant correlations with the differential diagnosis of IVL and LM. A total of 108 radiomic features were extracted from contrast-enhanced CT images and selected for analysis. 29 radiomics features were selected to establish the Rad-score. A clinical model was developed to discriminate IVL and LM (AUC=0.826). Radiomic models were used to effectively differentiate IVL and LM (AUC=0.980). This radiological nomogram combined the Rad-score with independent clinical factors showed better differentiation efficiency than the clinical model (AUC=0.985, p=0.046).

Conclusion

This study provides evidence for the utility of a radiomic nomogram integrating clinical and radiomic signatures for differentiating IVL and LM with improved diagnostic accuracy. The nomogram may be useful in clinical decision-making and provide recommendations for clinical treatment.

Parapharyngeal Abscess: Antibiotic-only or Open Surgical Drainage?

Objective:Many problems of parapharyngeal abscess (PPA), such as etiology, predisposing factors, and therapeutic methods, are still controversial. We aim to investigate the characteristics of PPA to better understand the therapeutic effects of the disease. Methods: We retrospectively collated the medical record reviews of 49 PPA patients who were treated as PPA inpatients when a patient was hospitalized and diagnosed with PPA, and empiric antibiotics were used. Only if the drug treatment was ineffective, the abscess was large, or the disease continued to progress, and surgical treatment was adopted. Results: In total, 49 patients who met the research criteria were identified. Streptococcus was the most common organism in PPA patients. The morbidity of diabetes in PPA patients was higher than the prevalence of diabetes in the overall population. Interestingly, the length of hospital stay was shorter in the antibiotic-only group than in the surgery group (P < 0.05). Furthermore, the duration from onset to treatment in the antibiotic-only group was shorter than in the surgery group. Conclusion: Our treatment protocol is effective. Antibiotic-only method is also recommended for the PPA which was effective for the empiric antibiotics and localized. Early diagnosis and treatment of PPA could ultimately reduce the severity of PPA.

Multi-View Radiomics Feature Fusion Reveals Distinct Immuno-Oncological Characteristics and Clinical Prognoses in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most prevalent malignancies worldwide, and the pronounced intra- and inter-tumor heterogeneity restricts clinical benefits. Dissecting molecular heterogeneity in HCC is commonly explored by endoscopic biopsy or surgical forceps, but invasive tissue sampling and possible complications limit the broadeer adoption. The radiomics framework is a promising non-invasive strategy for tumor heterogeneity decoding, and the linkage between radiomics and immuno-oncological characteristics is worth further in-depth study. In this study, we extracted multi-view imaging features from contrast-enhanced CT (CE-CT) scans of HCC patients, followed by developing a fused imaging feature subtyping (FIFS) model to identify two distinct radiomics subtypes. We observed two subtypes of patients with distinct texture-dominated radiomics profiles and prognostic outcomes, and the radiomics subtype identified by FIFS model was an independent prognostic factor. The heterogeneity was mainly attributed to inflammatory pathway activity and the tumor immune microenvironment. The predominant radiogenomics association was identified between texture-related features and immune-related pathways by integrating network analysis, and was validated in two independent cohorts. Collectively, this work described the close connections between multi-view radiomics features and immuno-oncological characteristics in HCC, and our integrative radiogenomics analysis strategy may provide clues to non-invasive inflammation-based risk stratification.

Impact of iodinated contrast media conserving interventions and lessons for the future

INTRODUCTION

A severe shortage of iodinated contrast medium (ICM) has forced radiology departments around the world to implement strategies to reduce contrast utilization. The aim of this study was to evaluate the effect of these interventions on ordering practices and ICM consumption for computed tomography (CT).

METHODS

Our radiology department instituted several ICM-conserving interventions on 13^th May 2022, encompassing: (i) improved triage; (ii) diversion to alternative modalities and non-enhanced CT (NECT); and (iii) reduction in ICM dosing. The impact of these changes on contrast-enhanced CT (CECT) scan numbers, and ICM consumption in the first 28 days post-intervention, was quantified and compared with the preceding 12 months. Sub-analyses of CT pulmonary angiography (CTPA), abdominal and pelvic CECT (CECT AP), and 'Code stroke' CT numbers and the impact on alternative modalities was also performed. The t-test for unpaired samples was used to assess the statistical significance of change.

RESULTS

The average daily number of CECT (all), CECT (inpatient and ED), CTPA, CECT AP, and 'Code stroke' CT scans decreased significantly (P < 0.01), by 58.6%, 68.8%, 74.1%, 88.0%, and 37.5%, respectively. The number of NECT, NECT abdomen and pelvis (NECT AP), and nuclear medicine lung ventilation:perfusion (VQ) scans increased significantly (P < 0.01), by 41.6%, 608.2%, and 165.8%, respectively. ICM consumption also decreased significantly (P < 0.01), by 65.3% (75.8% for ED and inpatient scans).

CONCLUSION

Interventions in CT alone, focused on improving patient triage to CECT while avoiding deferment of any outpatient oncology studies, have achieved an approximately two-thirds reduction in ICM consumption.

A nomogram diagnostic prediction model of pancreatic metastases of small cell lung carcinoma based on clinical characteristics, radiological features and biomarkers

Objective

To investigate clinical characteristics, radiological features and biomarkers of pancreatic metastases of small cell lung carcinoma (PM-SCLC), and establish a convenient nomogram diagnostic predictive model to differentiate PM-SCLC from pancreatic ductal adenocarcinomas (PDAC) preoperatively.

Methods

A total of 299 patients with meeting the criteria (PM-SCLC n=93; PDAC n=206) from January 2016 to March 2022 were retrospectively analyzed, including 249 patients from hospital 1 (training/internal validation cohort) and 50 patients from hospital 2 (external validation cohort). We searched for meaningful clinical characteristics, radiological features and biomarkers and determined the predictors through multivariable logistic regression analysis. Three models: clinical model, CT imaging model, and combined model, were developed for the diagnosis and prediction of PM-SCLC. Nomogram was constructed based on independent predictors. The receiver operating curve was undertaken to estimate the discrimination.

Results

Six independent predictors for PM-SCLC diagnosis in multivariate logistic regression analysis, including clinical symptoms, CA199, tumor size, parenchymal atrophy, vascular involvement and enhancement type. The nomogram diagnostic predictive model based on these six independent predictors showed the best performance, achieved the AUCs of the training cohort (n = 174), internal validation cohort (n = 75) and external validation cohort (n = 50) were 0.950 (95%CI, 0.917-0.976), 0.928 (95%CI, 0.873-0.971) and 0.976 (95%CI, 0.944-1.00) respectively. The model achieved 94.50% sensitivity, 83.20% specificity, 86.80% accuracy in the training cohort and 100.00% sensitivity, 80.40% specificity, 86.70% accuracy in the internal validation cohort and 100.00% sensitivity, 88.90% specificity, 87.50% accuracy in the external validation cohort.

Conclusion

We proposed a noninvasive and convenient nomogram diagnostic predictive model based on clinical characteristics, radiological features and biomarkers to preoperatively differentiate PM-SCLC from PDAC.

Development and validation of a contrast-enhanced CT-based radiomics nomogram for preoperative diagnosis in neuroendocrine carcinoma of digestive system

Objectives

To develop and validate a contrast-enhanced CT-based radiomics nomogram for the diagnosis of neuroendocrine carcinoma of the digestive system.

Methods

The clinical data and contrast-enhanced CT images of 60 patients with pathologically confirmed neuroendocrine carcinoma of the digestive system and 60 patients with non-neuroendocrine carcinoma of the digestive system were retrospectively collected from August 2015 to December 2021 at Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, and randomly divided into a training cohort (n=84) and a validation cohort (n=36). Clinical characteristics were analyzed by logistic regression and a clinical diagnosis model was developed. Radiomics signature were established by extracting radiomic features from contrast-enhanced CT images. Based on the radiomic signature and clinical characteristics, radiomic nomogram was developed. ROC curves and Delong's test were used to evaluate the diagnostic efficacy of the three models, calibration curves and application decision curves were used to analyze the accuracy and clinical application value of nomogram.

Results

Logistic regression results showed that TNM stage (stage IV) (OR 6.8, 95% CI 1.320-43.164, p=0. 028) was an independent factor affecting the diagnosis for NECs of the digestive system, and a clinical model was constructed based on TNM stage (stage IV). The AUCs of the clinical model, radiomics signature, and radiomics nomogram for the diagnosis of NECs of the digestive system in the training, validation cohorts and pooled patients were 0.643, 0.893, 0.913; 0.722, 0.867, 0.932 and 0.667, 0.887, 0.917 respectively. The AUCs of radiomics signature and radiomics nomogram were higher than clinical model, with statistically significant difference (Z=4.46, 6.85, both p < 0.001); the AUC difference between radiomics signature and radiomics nomogram was not statistically significant (Z=1.63, p = 0.104). The results of the calibration curve showed favorable agreement between the predicted values of the nomogram and the pathological results, and the decision curve analysis indicated that the nomogram had favorable application in clinical practice.

Conclusions

The nomogram constructed based on contrast-enhanced CT radiomics and clinical characteristics was able to effectively diagnose neuroendocrine carcinoma of the digestive system.

CT Radiomics Combined With Clinicopathological Features to Predict Invasive Mucinous Adenocarcinoma in Patients With Lung Adenocarcinoma

Objective: This study aimed to develop and validate predictive models using clinical parameters, radiomic features, and a combination of both for invasive mucinous adenocarcinoma (IMA) of the lung in patients with lung adenocarcinoma. Method: A total of 173 and 391 patients with IMA and non-IMA, respectively, were retrospectively analyzed from January 2017 to September 2022 in our hospital. Propensity Score Matching was used to match the 2 groups of patients. A total of 1037 radiomic features were extracted from contrast-enhanced computed tomography (CT). The patients were randomly divided into training and test groups at a ratio of 7:3. The least absolute shrinkage and selection operator algorithm was used for radiomic feature selection. Three radiomics prediction models were applied: logistic regression (logistic), support vector machine (SVM), and decision tree. The best-performing model was adopted, and the radiomics score (Radscore) was then computed. A clinical model was developed using logistic regression. Finally, a combined model was established based on a clinical model and a radiomics model. The area under the receiver operating characteristic (ROC) curve (AUC) and decision curve analysis were used to evaluate the predictive value of the developed models. Results: Both clinical and radiomics models established using the logistic method showed the best performance. The Delong test revealed that the combined model was superior to the clinical and radiomics models (P  =  .018 and .020, respectively). The ROC-AUC (also decision curve analysis) of the combined model was 0.840 and 0.850 in the training and testing groups, respectively, which showed good predictive performance for IMA. The Brier scores for the combined model were 0.161 and 0.154 in the training and testing groups, respectively. Conclusion: The combined model incorporating radiomic CT features and clinical predictors may have the potential to predict IMA in patients with lung cancer.

Combining polyp diameter and polyp-to-bile ratio by dynamic contrast-enhanced CT scanning can improve the diagnostic specificity of gallbladder neoplastic polyps

OBJECTIVE

This study aimed to distinguish between cholesterol and neoplastic gallbladder polyps using dynamic contrast-enhanced CT.

METHODS

The dataset retrospectively comprised 222 cases, including 106 cases of cholesterol polyps and 116 cases of neoplastic polyps (59 adenoma and 57 adenocarcinoma). The perception and Hounsfield units of the polyps and gallbladder bile were assessed by contrast-enhanced CT, and the polyp-to-bile ratio (PBR) was calculated. Receiver operating characteristic (ROC) curves and area under the curve analyses were used to assess the diagnostic value of the diameter and PBR for neoplastic polyps.

RESULTS

The diameter of cholesterol polyps was significantly smaller than that of neoplastic polyps. The proportion of perceived cholesterol polyps in the plain and arterial phases of CT were significantly lower than those of neoplastic polyps (p < .001). On the contrary, the CT values of gallbladder bile of cholesterol polyps were always significantly higher than those of neoplastic polyps (p < .001). The median PBR values of cholesterol polyps were significantly lower than those of neoplastic polyps (p ≤ .001). ROC analysis showed that diameter and a plain phase PRB had better diagnostic value for neoplastic polyps. Polyp diameter ≥ 11.95 mm and the plain phase PBR ≥1.48 were the optimal cut-off values for diagnosis of neoplastic polyps. Combining a diameter ≥ 12 mm and a PBR in the plain phase ≥1.48 further improved neoplastic polyp diagnostic specificity and positive likelihood ratio (10.453).

CONCLUSIONS

Polyp-to-bile ratio in contrast-enhanced CT scanning is a new and convenient index for identifying cholesterol and neoplastic gallbladder polyps.

Dual-Energy Computed Tomography-Based Iodine Concentration Estimation for Evaluating Choroidal Malignant Melanoma Response to Treatment: Optimization and Primary Validation

Contrast-enhanced imaging for choroidal malignant melanoma (CMM) is mostly limited to detecting metastatic tumors, possibly due to difficulties in fixing the eye position. We aimed to (1) validate the appropriateness of estimating iodine concentration based on dual-energy computed tomography (DECT) for CMM and optimize the calculation parameters for estimation, and (2) perform a primary clinical validation by assessing the ability of this technique to show changes in CMM after charged-particle radiation therapy. The accuracy of the optimized estimate (eIC_optimized) was compared to an estimate obtained by commercial software (eIC_commercial) by determining the difference from the ground truth. Then, eIC_optimized, tumor volume, and CT values (80 kVp, 140 kVp, and synthesized 120 kVp) were measured at pre-treatment and 3 months and 1.5−2 years after treatment. The difference from the ground truth was significantly smaller in eIC_optimized than in eIC_commercial (p < 0.01). Tumor volume, CT values, and eIC_optimized all decreased significantly at 1.5−2 years after treatment, but only eIC_commercial showed a significant reduction at 3 months after treatment (p < 0.01). eIC_optimized can quantify contrast enhancement in primary CMM lesions and has high sensitivity for detecting the response to charged-particle radiation therapy, making it potentially useful for treatment monitoring.

A patient-informed approach to predict iodinated-contrast media enhancement in the liver

OBJECTIVE

To devise a patient-informed time series model that predicts liver contrast enhancement, by integrating clinical data and pharmacokinetics models, and to assess its feasibility to improve enhancement consistency in contrast-enhanced liver CT scans.

METHODS

The study included 1577 Chest/Abdomen/Pelvis CT scans, with 70-30% training/validation-testing split. A Gaussian function was used to approximate the early arterial, late arterial, and the portal venous phases of the contrast perfusion curve of each patient using their respective bolus tracking and diagnostic scan data. Machine learning models were built to predict the Gaussian parameters of each patient using the patient attributes (weight, height, age, sex, BMI). Pearson's coefficient, mean absolute error, and root mean squared error were used to assess the prediction accuracy.

RESULTS

The integration of the pharmacokinetics model with a two-layered neural network achieved the highest prediction accuracy on the test data (R2 = 0.61), significantly exceeding the performance of the pharmacokinetics model alone (R2 = 0.11). Applying the model demonstrated that adjusting the contrast administration directed by the model may reduce clinical enhancement inconsistency by up to 40 %.

CONCLUSIONS

A new model using a Gaussian function and supervised machine learning can be used to build liver parenchyma contrast enhancement prediction model. The model can have utility in clinical settings to optimize and improve consistency in contrast-enhanced liver imaging.

Iodinated contrast media shortage: Insights and guidance from two major public hospitals

Global shortage of iodinated contrast medium (ICM) is the latest health care ripple-effect from the COVID-19 pandemic. Some public hospitals in Australia have less than a week's supply. Strategies are, therefore, urgently needed to conserve ICM for those diagnostic tests and interventions, which are time-critical, and without which patients would suffer death or significant morbidity. A plan is also required to continue providing best possible care to patients in the worst-case scenario of exhausted ICM supplies. This document, by representatives from two major public hospitals, will provide some guidance that is tailored to the Australian context.

Warfarin-related epidural hematoma: a case report

Spinal epidural hematomas are rare, with trauma being the most common cause. Spinal epidural hematomas caused by coagulation dysfunction are even rarer; however, long-term warfarin therapy increases the risk. The clinical manifestations of spinal epidural hematoma are neurological deficits below the corresponding spinal cord segment level. Magnetic resonance imaging (MRI) is the preferred method for diagnosis, and the main treatment for epidural hematoma with typical symptoms is urgent decompression of the lumbar spine. We describe an almost 80-year-old female patient who received long-term oral warfarin therapy for atrial fibrillation. She developed sudden onset waist pain, and 2 days later, she developed pain and weakness in both lower limbs. Computed tomography (CT) of the thoracolumbar spine showed no obvious hematoma. Eight days after admission, contrast-enhanced CT of the thoracolumbar spine showed intraspinal hematomas at T5–T8 and T12–L2 levels. We performed T3–T7 laminectomy, T5–T8 hematoma removal, and spinal dural repair. The clinical symptoms did not improve significantly, postoperatively. The low incidence of spinal epidural hematoma after anticoagulation treatment means this condition is not recognized timely, and it is misdiagnosed easily. Clinicians should consider this condition when patients treated with anticoagulants have neurological deficits below a spinal segmental plane.

Progression-Free Survival Prediction in Small Cell Lung Cancer Based on Radiomics Analysis of Contrast-Enhanced CT

Purposes and Objectives

The aim of this study was to predict the progression-free survival (PFS) in patients with small cell lung cancer (SCLC) by radiomic signature from the contrast-enhanced computed tomography (CT).

Methods

A total of 186 cases with pathological confirmed small cell lung cancer were retrospectively assembled. First, 1,218 radiomic features were automatically extracted from tumor region of interests (ROIs) on the lung window and mediastinal window, respectively. Then, the prognostic and robust features were selected by machine learning methods, such as (1) univariate analysis based on a Cox proportional hazard (CPH) model, (2) redundancy removing using the variance inflation factor (VIF), and (3) multivariate importance analysis based on random survival forests (RSF). Finally, PFS predictive models were established based on RSF, and their performances were evaluated using the concordance index (C-index) and the cumulative/dynamic area under the curve (C/D AUC).

Results

In total, 11 radiomic features (6 for mediastinal window and 5 for lung window) were finally selected, and the predictive model constructed from them achieved a C-index of 0.7531 and a mean C/D AUC of 0.8487 on the independent test set, better than the predictions by single clinical features (C-index = 0.6026, mean C/D AUC = 0.6312), and single radiomic features computed in lung window (C-index = 0.6951, mean C/D AUC = 0.7836) or mediastinal window (C-index = 0.7192, mean C/D AUC = 0.7964).

Conclusion

The radiomic features computed from tumor ROIs on both lung window and mediastinal window can predict the PFS for patients with SCLC by a high accuracy, which could be used as a useful tool to support the personalized clinical decision for the diagnosis and patient management of patients with SCLC.

Comparative analysis of the efficacy and accuracy of magnetic resonance imaging (MRI) and contrast-enhanced CT for residual and new lesions after transcatheter arterial chemoembolization (TACE) in patients with primary liver cancer

Background

The purpose of this study was to investigate the efficacy and accuracy of magnetic resonance imaging (MRI) and contrast-enhanced computed tomography (CECT) for residual and new lesions after transcatheter arterial chemoembolization (TACE) in patients with primary liver cancer (PHC).

Methods

Seventy-two PHC patients admitted to Linyi Central Hospital from May 2018 to May 2020 were selected as the study subjects, with a total of 92 lesions. All patients were treated with TACE, and were followed up at 6 months postoperatively. In addition, all patients underwent digital subtraction angiography (DSA), and with DSA results serving as the gold standard for diagnosis, the efficacy and accuracy of MRI and CECT for residual and new lesions after TACE in PHC patients were evaluated.

Results

There were no significant differences in the specificity between the two diagnostic methods (P>0.05), and the diagnostic accuracy and sensitivity of MRI were markedly higher than those of CECT (P<0.05). The number of residual and new lesions diagnosed by MRI was notably higher than that by multislice spiral computed tomography (MSCT) (P<0.05), and the detection rate of residual and new lesions after TACE in PHC patients with different types of iodized oil deposition by MRI was significantly higher than that by CECT (P<0.05). Also, the number of postoperative tumor capsules diagnosed by MRI was considerably higher than that by CECT (P<0.05). There were no significant differences between the two diagnostic methods in the score of residual enhancement appearances in the arterial phase after surgery (P>0.05). Furthermore, there were no notable differences between the two diagnostic methods in the diagnosis of portal vein tumorous emboli and the source of blood supply to lesions after surgery (P>0.05).

Conclusions

The diagnostic accuracy and sensitivity of MRI for residual and new lesions after TACE in PHC patients were higher than those of CECT. However, these two diagnostic methods were similar in diagnosing portal vein tumorous emboli, the source of blood supply to lesions, and the score of residual enhancement appearances in the arterial phase after surgery.

A radiologic diagnostic scoring model based on CT features for differentiating gastric schwannoma from gastric gastrointestinal stromal tumors

We aimed to further explore the CT features of gastric schwannoma (GS), propose and validate a convenient diagnostic scoring system to distinguish GS from gastric gastrointestinal stromal tumors (GISTs) preoperatively. 170 patients with submucosal tumors pathologically confirmed (GS n=35; gastric GISTs n=135) from Hospital 1 were analyzed retrospectively as the training cohort, and 72 patients (GS=11; gastric GISTs=61) from Hospital 2 were enrolled as the validation cohort. We searched for significant CT imaging characteristics and constructed the scoring system via binary logistic regression and converted regression coefficients to weighted scores. The ROC curves, AUCs and calibration tests were carried out to evaluate the scoring models in both the training cohort and the validation cohort. For convenient assessment, the system was further divided into four score ranges and their diagnostic probability of GS was calculated respectively. Four CT imaging characteristics were ultimately enrolled in this scoring system, including transverse position (2 points), location (5 points), perilesional lymph nodes (6 points) and pattern of enhancement (2 points). The AUC of the scoring model in the training cohort were 0.873 (95% CI, 0.816-0.929) and the cutoff point was 6 points. In the validation cohort, the AUC was 0.898 (95% CI, 0.804-0.957) and the cutoff value was 5 points. Four score ranges were as follows: 0-3 points for very low probability of GS, 4-7 points for low probability; 8-9 points for middle probability; 10-15 points for very high probability. A convenient scoring model to preoperatively discriminate GS from gastric GISTs was finally proposed.

Can Lymphovascular Invasion be Predicted by Preoperative Contrast-Enhanced CT in Esophageal Squamous Cell Carcinoma?

Objective: To explore whether preoperative contrast-enhanced computed tomogrpahy (CT) can predict lymphovascular invasion (LVI) in esophageal squamous cell carcinoma (ESCC), and provide a reliable reference for the formulation of clinical individualized treatment plans. Methods: This retrospective study enrolled 228 patients with surgically resected and pathologically confirmed ESCC, including 36 patients with LVI and 192 patients without LVI. All patients underwent contrast-enhanced CT (CECT) scan within 2 weeks before the operation. Tumor size (including tumor length and maximum tumor thickness), tumor-to-normal wall enhancement ratio (TNR), and gross tumor volume (GTV) were obtained. All clinical features and CECT-derived parameters associated with LVI were analyzed by univariate and multivariate analysis. The independent predictors for LVI were identified, and their combination was built by multivariate logistic regression analysis, using the significant variables from the univariate analysis as inputs. Results: Univariate analysis of clinical features and CECT-derived parameters revealed that age, TNR, and clinical N stage (cN stage) were significantly associated with LVI. The multivariable analysis results demonstrated that age (odds ratio [OR]: 5.32, 95% confidence interval [CI]: 2.224-12.743, P<.001), TNR (OR: 5.399, 95% CI: 1.609-18.110, P  =  .006), and cN stage (cN1: OR: 2.874, 95% CI: 1.182-6.989, P  =  .02; cN2: OR: 6.876, 95% CI: 2.222-21.227) were identified to be independent predictors for LVI. The combination of age, TNR, and cN stage achieved a relatively higher area under the curve (AUC) (0.798), accuracy (ACC) (65.4%), sensitivity (SEN) (69.4%), specificity (SPE) (79.7%), positive predictive value (PPV) (77.4%), and negative predictive value (NPV) (71.6%). Conclusions: The combination of clinical features and CECT-derived parameters may be effective in predicting LVI status preoperatively in ESCC.

Extrathyroidal Extension Prediction of Papillary Thyroid Cancer With Computed Tomography Based Radiomics Nomogram: A Multicenter Study

OBJECTIVES

To develop and validate a Computed Tomography (CT) based radiomics nomogram for preoperative predicting of extrathyroidal extension (ETE) in papillary thyroid cancer (PTC) patients.

METHODS

A total of 153 patients were randomly assigned to training and internal test sets (7:3). 46 patients were recruited to serve as an external test set. A radiologist with 8 years of experience segmented the images. Radiomics features were extracted from each image and Delta-radiomics features were calculated. Features were selected by using one way analysis of variance and the least absolute shrinkage and selection operator in the training set. K-nearest neighbor, logistic regression, decision tree, linear-support vector machine (linear -SVM), gaussian-SVM, and polynomial-SVM were used to build 6 radiomics models. Next, a radiomics signature score (Rad-score) was constructed by using the linear combination of selected features weighted by their corresponding coefficients. Finally, a nomogram was constructed combining the clinical risk factors with Rad-scores. Receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and calibration curve were performed on the three sets to evaluate the nomogram's performance.

RESULTS

4 radiomics features were selected. The six models showed the certain value of radiomics, with area under the curves (AUCs) from 0.642 to 0.701. The nomogram combining the Rad-score and clinical risk factors (radiologists' interpretation) showed good performance (internal test set: AUC 0.750; external test set: AUC 0.797). Calibration curve and DCA demonstrated good performance of the nomogram.

CONCLUSION

Our radiomics nomogram incorporating the radiomics and radiologists' interpretation has utility in the identification of ETE in PTC patients.

Assessment of glomerular filtration rate measurement in dogs using dynamic contrast CT compared to serum iohexol clearance

Dynamic contrast CT with Patlak plot analysis can be used to determine the glomerular filtration rate (GFR). However, several studies have shown different GFR values and they are most likely less than the values by the standard techniques. The purpose of this prospective, experimental, and method comparison study was to evaluate the GFR using a CT technique (CT-GFR) in 12 healthy dogs compared to serum iohexol clearance (SIC-GFR). All dogs were anesthetized and placed in the right lateral recumbency position and the caudal part was lifted inside the CT gantry. A single-slice dynamic CT of the aorta and both kidneys was scanned sequentially every 2 s for 2 min after a bolus injection (3 mL/s) of iohexol (300 mg/kg). Time attenuation curves (TAC) were constructed and the GFR per volume of kidney was calculated using the Patlak plot analysis method based on 30-120 s time intervals, and results were compared to global GFR from SIC that was determined with eight blood samples for up to 240 min. The CT-GFR value (1.85 ± 0.48 mL/min/kg) was significantly less than the SIC-GFR value (3.40 ± 0.80 mL/min/kg; P < .05). The CT-GFR was correlated with SIC-GFR by the coefficient of correlation (r) at 0.61 (P = .046). In conclusion, the CT-GFR underestimated SIC-GFR and should be used carefully. We suggest that the GFR should be calculated using the equation derived from linear regression between CT-GFR and the standard GFR method. With its own particular parameters, each institute should have its own prediction equation.

Spectral CT using a fine grid structure and varying x-ray incidence angle

PURPOSE

Interest in spectral computed tomography (CT) for diagnostics and therapy evaluation has been growing. Data acquisitions with distinct spectral sensitivities provide the ability to discriminate multiple materials, quantitative density estimates, and reduced artifacts due to energy dependencies. We introduce a novel spectral CT concept that includes a fine-pitch grid structure for prefiltration of the x-ray beam.

METHODS

We develop physical models for grid designs and illustrate the basic operating principles wherein small angulations of the incident x rays results significant filtration and spectral shaping of the beam. We fabricate a prototype grid with tungsten lamellae. We compare x-ray spectra induced by this filter as a function of incidence angle in both simulation students and in physical measurements. The grid is also integrated onto a CT test bench where we scanned an iodinated phantom with clinically relevant concentrations (5, 10, 20, and 50 mgI/mL) to demonstrate the ability to perform spectral CT acquisitions and material decomposition.

RESULTS

X-ray spectrometer measurements reveal diverse and controllable spectral shaping with small angle changes that are in agreement with simulation studies. Critical angles where the characteristics of the induced spectrum changes dramatically are identified. Reconstructions of projection data for two angulations separated by 2° was reconstructed and material decomposition into iodine and water images shows good agreement with the known iodine concentrations.

CONCLUSIONS

This work demonstrates the feasibility of the grid-based approach to enable spectral CT data acquisitions and accurate material decompositions. On-going and future studies will investigate the potential of this novel concept as a relatively simple upgrade to standard energy-integrating CT.

Difficulty Diagnosing Retrograde Type A Aortic Dissection with Intramural Hematoma and Risk of Re-dissection and Rupture: A Report of Two Cases

Acute type A aortic dissection is a potentially fatal disease, and emergency surgery should be considered when it is diagnosed. We herein report two cases of retrograde type A aortic dissection with intramural hematoma, followed by re-dissection, rupture, and cardiac tamponade. The diagnoses in these cases had to be made carefully, as the false lumen of the ascending aorta was sometimes unclear on contrast-enhanced computed tomography.

Effect of contrast medium on treatment modalities planned with different photon beam energies: a planning study

BACKGROUND

Routinely, patient's planning scans are acquired after administration of iodinized contrast media but they will be treated in the absence of that. Similarly, high energy photons have a better penetrating power, while low energy photons will result in tighter dose distribution and negligible neutron contamination. The aim of the study was to investigate a suitable photon beam energy in the presence of intravenous contrast medium.

MATERIALS AND METHODS

An indigenously made original-contrast (OC) phantom was mentioned as virtual-contrast (VC) and virtual-without-contrast (VWC) phantom were generated by assigning the Hounsfield Units (HU) to different structures. Intensity-modulated (IMRT) and volumetric-modulated-arc (VMAT) plans were generated as per criteria of the TG-119 protocol.

RESULTS

It was observed that the maximum dose to the spinal cord was better with 6 mega-voltage (MV) in IMRT. The coverage of Prostate PTV (PR PTV) was similar with all the photon energies and was comparable with TG-119, except for original-contrast (OC) phantom using the VMAT technique. Homogeneity-index (HI) was comparatively better for VMAT plans.

CONCLUSION

The contrast CT images lower the dose to targets. IMRT or VMAT plans, generated on such CT images will be delivered with higher doses than evaluated. However, the overdose remains non-significant.

Contrast-enhanced to noncontrast CT transformation via an adjacency content-transfer-based deep subtraction residual neural network

To reduce overall patient radiation exposure in some clinical scenarios (since cancer patients need frequent follow-ups), noncontrast CT is not used in some institutions. However, although less desirable, noncontrast CT could provide additional important information. In this article, we propose a deep subtraction residual network based on adjacency content transfer to reconstruct noncontrast CT from contrast CT and maintain image quality comparable to that of a CT scan originally acquired without contrast. To address the slight structural dissimilarity of the paired CT images (noncontrast CT and contrast CT) due to involuntary physiological motion, we introduce a contrastive loss network derived from the adjacency content-transfer strategy. We evaluate the results of various similarity metrics (MSE, SSIM, NRMSE, PSNR, MAE) and the fitting curve (HU distribution) of the output mapping to estimate the reconstruction performance of the algorithm. To build the model, we randomly select a total of 15,405 CT paired images (noncontrast CT and contrast-enhanced CT) for training and 10,270 CT paired images for testing. The proposed algorithm preserves the robust structures from the contrast-enhanced CT scans and learns the noncontrast attenuation pattern from the noncontrast CT scans. During the evaluation, the deep subtraction residual network achieves higher MSE, MAE, NRMSE, and PSNR scores (by 30%) than those of the baseline models (BEGAN, CycleGAN, Pixel2Pixel) and better simulates the HU curve of noncontrast CT attenuation. After validation based on an analysis of the experimental results, we can report that the noncontrast CT images reconstructed by our proposed algorithm not only preserve the high-quality structures from the contrast-enhanced CT images, but also mimic the CT attenuation of the originally acquired noncontrast CT images.

18F-FDG PET/CT versus Diagnostic Contrast-Enhanced CT for Follow-Up of Stage IV Melanoma Patients Treated by Immune Checkpoint Inhibitors: Frequency and Management of Discordances over a 3-Year Period in a University Hospital

Aim: To perform a comprehensive analysis of discordances between contrast-enhanced CT (ceCT) and ¹⁸F-FDG PET/CT in the evaluation of the extra-cerebral treatment monitoring in patients with stage IV melanoma. Materials and methods: We conducted a retrospective monocentric observational study over a 3-year period in patients referred for ¹⁸F-FDG PET/CT and ceCT in the framework of therapy monitoring of immune checkpoint (ICIs) as of January 2017. Imaging reports were analyzed by two physicians in consensus. The anatomical site responsible for discordances, as well as induced changes in treatment were noted. Results: Eighty patients were included and 195 pairs of scans analyzed. Overall, discordances occurred in 65 cases (33%). Eighty percent of the discordances (52/65) were due to ¹⁸F-FDG PET/CT scans upstaging the patient. Amongst these discordances, 17/52 (33%) led to change in patient’s management, the most frequent being radiotherapy of a progressing site. ceCT represented 13/65 (20%) of discordances and induced changes in patients’ management in 2/13 cases (15%). The most frequent anatomical site involved was subcutaneous for ¹⁸F-FDG PET/CT findings and lung or liver for ceCT. Conclusions: Treatment monitoring with ¹⁸F-FDG PET/CT is more efficient than ceCT and has a greater impact in patient’s management.

Targeting Treatment Resistance in Head and Neck Squamous Cell Carcinoma - Proof of Concept for CT Radiomics-Based Identification of Resistant Sub-Volumes

Purpose

Radiomics has already been proposed as a prognostic biomarker in head and neck cancer (HNSCC). However, its predictive power in radiotherapy has not yet been studied. Here, we investigated a local radiomics approach to distinguish between tumor sub-volumes with different levels of radiosensitivity as a possible target for radiation dose intensification.

Materials and Methods

Of 40 patients (n=28 training and n=12 validation) with biopsy confirmed locally recurrent HNSCC, pretreatment contrast-enhanced CT images were registered with follow-up PET/CT imaging allowing identification of controlled (GTVcontrol) vs non-controlled (GTVrec) tumor sub-volumes on pretreatment imaging. A bi-regional model was built using radiomic features extracted from pretreatment CT in the GTVrec and GTVcontrol to differentiate between those regions. Additionally, concept of local radiomics was implemented to perform detection task. The original tumor volume was divided into sub-volumes with no prior information on the location of recurrence. Radiomic features from those sub-volumes were then used to detect recurrent sub-volumes using multivariable logistic regression.

Results

Radiomic features extracted from non-controlled regions differed significantly from those in controlled regions (training AUC = 0.79 CI 95% 0.66 - 0.91 and validation AUC = 0.88 CI 95% 0.72 – 1.00). Local radiomics analysis allowed efficient detection of non-controlled sub-volumes both in the training AUC = 0.66 (CI 95% 0.56 – 0.75) and validation cohort 0.70 (CI 95% 0.53 – 0.86), however performance of this model was inferior to bi-regional model. Both models indicated that sub-volumes characterized by higher heterogeneity were linked to tumor recurrence.

Conclusion

Local radiomics is able to detect sub-volumes with decreased radiosensitivity, associated with location of tumor recurrence in HNSCC in the pre-treatment CT imaging. This proof of concept study, indicates that local CT radiomics can be used as predictive biomarker in radiotherapy and potential target for dose intensification.

Contrast-Enhanced CT-Based Radiomics Analysis in Predicting Lymphovascular Invasion in Esophageal Squamous Cell Carcinoma

Objectives

To develop a radiomics model based on contrast-enhanced CT (CECT) to predict the lymphovascular invasion (LVI) in esophageal squamous cell carcinoma (ESCC) and provide decision-making support for clinicians.

Patients and Methods

This retrospective study enrolled 334 patients with surgically resected and pathologically confirmed ESCC, including 96 patients with LVI and 238 patients without LVI. All enrolled patients were randomly divided into a training cohort and a testing cohort at a ratio of 7:3, with the training cohort containing 234 patients (68 patients with LVI and 166 without LVI) and the testing cohort containing 100 patients (28 patients with LVI and 72 without LVI). All patients underwent preoperative CECT scans within 2 weeks before operation. Quantitative radiomics features were extracted from CECT images, and the least absolute shrinkage and selection operator (LASSO) method was applied to select radiomics features. Logistic regression (Logistic), support vector machine (SVM), and decision tree (Tree) methods were separately used to establish radiomics models to predict the LVI status in ESCC, and the best model was selected to calculate Radscore, which combined with two clinical CT predictors to build a combined model. The clinical model was also developed by using logistic regression. The receiver characteristic curve (ROC) and decision curve (DCA) analysis were used to evaluate the model performance in predicting the LVI status in ESCC.

Results

In the radiomics model, Sphericity and gray-level non-uniformity (GLNU) were the most significant radiomics features for predicting LVI. In the clinical model, the maximum tumor thickness based on CECT (cThick) in patients with LVI was significantly greater than that in patients without LVI (P<0.001). Patients with LVI had higher clinical N stage based on CECT (cN stage) than patients without LVI (P<0.001). The ROC analysis showed that both the radiomics model (AUC values were 0.847 and 0.826 in the training and testing cohort, respectively) and the combined model (0.876 and 0.867, respectively) performed better than the clinical model (0.775 and 0.798, respectively), with the combined model exhibiting the best performance.

Conclusions

The combined model incorporating radiomics features and clinical CT predictors may potentially predict the LVI status in ESCC and provide support for clinical treatment decisions.

[Computed tomography in determining the differentiation of ductal adenocarcinoma of pancreatic head]

OBJECTIVE

To evaluate the features of «hypervascular rim», tumor dimensions and density as prognostic factors of differentiation of pancreatic head adenocarcinoma.

MATERIAL AND METHODS

Pancreatoduodenectomy was performed in 311 patients with pancreatic head adenocarcinoma for the period 2013-2019. A retrospective study included 81 patients who met the following criteria: available data of morphological and immunohistological examination indicating tumor grade from Grade 1 to Grade 3, as well as available preoperative CT images in four phases (native, arterial, portal and delayed). Tumor dimensions, density of the pancreas, adenocarcinoma and abdominal aorta by the phases of contrast enhancement were analyzed in all patients. Moreover, we estimated coefficient of relative enhancement change. Perifocal hypervascular enhancement was assessed in arterial and portal phases. Contrast-enhanced MRI was performed in 15 out of 81 patients. MR images were analyzed regarding a hypervascular rim, and the last one was compared with CT images.

RESULTS

There was no significant difference in density values between different tumor grades. Coefficient of relative enhancement change >1 was observed in 63.64% of highly-differentiated tumors. REC ≤1 was found in 85.11% of tumors grade 2 and 82.6% of tumors grade 3 (p=0.005). According to Chi-square test, there was a correlation between tumor differentiation and hypervascular rim (p=0.03). Moderate and low differentiation was observed in 96.42% of tumors with perifocal enhancement. Hypervascular rim was absent in 81.82% of tumors grade 1. Adenocarcinoma grade 2 was found in 85.71% of cases with unclear perifocal enhancement.

CONCLUSION

Preoperative contrast-enhanced CT is valuable to assume the tumor grade in patients with pancreatic head adenocarcinoma due to assessment of hypervascular rim and REC.

The Preoperative Enhanced Degree of Contrast-enhanced CT Images: A Potential Independent Predictor in Gastric Adenocarcinoma Patients After Radical Gastrectomy

Aim

To discover the value of contrast-enhanced CT parameters in predicting the prognosis of gastric adenocarcinoma (GAC) patients after radical gastrectomy.

Methods

The patients with a clinical diagnosis of GAC were retrospectively enrolled. Two radiologists drew the regions of interest (ROIs) in CT images and measured the CT attenuate value (CAV) in each phase and the corrected CAV (cCAV) in each contrast-enhanced phase. Patients were divided into two groups (high/low-enhancement) according to receiver operating characteristic (ROC) curve. Kaplan–Meier curve and Cox proportional hazards regression analysis were performed to evaluate correlation between prognosis and variables. Subgroup analysis was used to further analyze the prognostic value of variables.

Results

In total 435 patients were included. According to ROC curve, the cCAV in delayed phase (DP-cCAV) with maximum AUC and Youden index was chosen. A total of 312 patients (71.7%) entered DP-cCAV^low group and remaining 123 (28.3%) patients were in DP-cCAV^high group. According to univariate (high vs low, HR=2.120, p<0.001) and multivariate (high vs low, HR=1.623, p<0.001) Cox regression analysis, the low-enhancement state was considered as an independent protective factor. Subgroup analysis was based on age, maximum diameter of tumor, differentiation, vascular invasion status, and TNM staging. In most subgroups, the overall survival (OS) of DP-cCAV^low group was overwhelmingly satisfactory (all HR >1, expect TNM stage I, IV and differentiated type subgroups).

Conclusion

The prognostic effectiveness of CT parameters as biomarkers for OS in GAC patients treated with radical gastrectomy has potential value.

A 3D ontogenetic atlas of Alligator mississippiensis cranial nerves and their significance for comparative neurology of reptiles

Cranial nerves are key features of the nervous system and vertebrate body plan. However, little is known about the anatomical relationships and ontogeny of cranial nerves in crocodylians and other reptiles, hampering understanding of adaptations, evolution, and development of special senses, somatosensation, and motor control of cranial organs. Here we share three dimensional (3D) models an of the cranial nerves and cranial nerve targets of embryonic, juvenile, and adult American Alligators (Alligator mississippiensis) derived from iodine-contrast CT imaging, for the first time, exploring anatomical patterns of cranial nerves across ontogeny. These data reveal the tradeoffs of using contrast-enhanced CT data as well as patterns in growth and development of the alligator cranial nervous system. Though contrast-enhanced CT scanning allows for reconstruction of numerous tissue types in a nondestructive manner, it is still limited by size and resolution. The position of alligator cranial nerves varies little with respect to other cranial structures yet grow at different rates as the skull elongates. These data constrain timing of trigeminal and sympathetic ganglion fusion and reveal morphometric differences in nerve size and path during growth. As demonstrated by these data, alligator cranial nerve morphology is useful in understanding patterns of neurological diversity and distribution, evolution of sensory and muscular innervation, and developmental homology of cranial regions, which in turn, lead to inferences of physiology and behavior.

Application of Computer-Aided Design (CAD) and Three-Dimensional (3D) Visualization Technologies in the Diagnosis and Treatment of Refractory Thyroid Tumors

Background

To evaluate the application of computer-aided design (CAD) and three-dimensional (3D) visualization techniques in the diagnosis and treatment of refractory thyroid tumors.

Materials and Methods

The clinical data from 12 cases of refractory thyroid tumors treated with CAD and 3D visualization techniques from September 2016 to January 2018 were analyzed retrospectively. Ten cases were malignant, while two cases were benign. All tracheas in the 12 cases were invaded or oppressed by the thyroid tumors. Six of the cases experienced type III dyspnea, while the other six cases had type II dyspnea. All patients underwent contrast-enhanced computed tomography (CT) imaging.

Results

CAD and 3D visualization technologies were used to guide the surgeries. Ten cases of malignant thyroid tumors underwent total thyroidectomy, cervical lymph node dissection, and invaded organ resection. Among the ten cases, five underwent sleeve resections and anastomosis reconstructions, one underwent a tracheal sleeve resection and total laryngectomy, two underwent tracheal window resections, one case underwent a sternotomy, and one case underwent a laryngopharyngectomy, invaded skin resection, and pectoralis major muscle flap reconstruction. The two cases of benign thyroid tumors underwent subtotal thyroidectomies. Using CAD and 3D visualization techniques, surgeons can visually observe the relationship of the tumor with the respiratory tract and essential blood vessels, which can lead to optimized surgical plans and improved surgical outcomes.

Conclusion

CAD and 3D visualization technologies have an important role in the personalized surgical intervention of thyroid cancer, which will likely have important clinical implications.

Predictive Value of the Texture Analysis of Enhanced Computed Tomographic Images for Preoperative Pancreatic Carcinoma Differentiation

Purpose

To assess the utility of texture analysis for predicting the pathological degree of differentiation of pancreatic carcinoma (PC).

Methods

Eighty-three patients with PC who went through postoperative pathology diagnose and CT examination were selected at Anhui Provincial Hospital. Among them, 34 cases were moderately differentiated, 13 cases were poorly differentiated, and 36 cases were moderately poorly differentiated. The images in the arterial and venous phase (VP) with the lesions at their largest cross section were selected to manually outline the region of interest (ROI) to delineate lesions using open-source software. A total of 396 features were extracted from the ROI using AK software. Spearman correlation analysis and random forest selection by filter (rfSBF) in the caret package of R studio were used to select the discriminating features. The receiver operating characteristic ROC analysis was used to evaluate their discriminative performance.

Results

Twelve and six features were selected in the arterial and VPs, respectively. The areas under the ROC curve (AUC) in the arterial phase (AP) for diagnosing poorly differentiated, moderately differentiated and moderate-poorly differentiated cases were 0.80, 1, and 0.80 in the training group and 0.77, 1, and 0.77 in the test group; in the VP, the values were 0.81, 1, and 0.82 in the training group and 0.74, 1, and 0.74 in the test group.

Conclusion

Texture analysis based on contrast-enhanced CT images can be used as an adjunct for the preoperative assessment of the pathological degrees of differentiation of PC.

Contrast-enhanced CT radiomics for preoperative evaluation of microvascular invasion in hepatocellular carcinoma: A two-center study

Background

The present study constructed and validated the use of contrast‐enhanced computed tomography (CT)‐based radiomics to preoperatively predict microvascular invasion (MVI) status (positive vs negative) and risk (low vs high) in patients with hepatocellular carcinoma (HCC).

Methods

We enrolled 637 patients from two independent institutions. Patients from Institution I were randomly divided into a training cohort of 451 patients and a test cohort of 111 patients. Patients from Institution II served as an independent validation set. The LASSO algorithm was used for the selection of 798 radiomics features. Two classifiers for predicting MVI status and MVI risk were developed using multivariable logistic regression. We also performed a survival analysis to investigate the potentially prognostic value of the proposed MVI classifiers.

Results

The developed radiomics signature predicted MVI status with an area under the receiver operating characteristic curve (AUC) of .780, .776, and .743 in the training, test, and independent validation cohorts, respectively. The final MVI status classifier that integrated two clinical factors (age and α‐fetoprotein level) achieved AUC of .806, .803, and .796 in the training, test, and independent validation cohorts, respectively. For MVI risk stratification, the AUCs of the radiomics signature were .746, .664, and .700 in the training, test, and independent validation cohorts, respectively, and the AUCs of the final MVI risk classifier‐integrated clinical stage were .783, .778, and .740, respectively. Survival analysis showed that our MVI status classifier significantly stratified patients for short overall survival or early tumor recurrence.

Conclusions

Our CT radiomics‐based models were able to predict MVI status and MVI risk of HCC and might serve as a reliable preoperative evaluation tool.

Imaging Features of Multiple Myeloma Extramedullary Lesions in the Liver with 18F-FDG PET/CT, Contrast-Enhanced CT and MRI

Ηepatic involvement in multiple myeloma is not common; nevertheless, it is associated with poorer outcome. Heterogeneous features have been described in few published reports so far. We present the imaging findings of PET/CT in comparison to those of MRI for two multiple myeloma (MM) patients, one with a liver lesion suspicious for myeloma metastasis on PET and one with multiple liver lesions suspicious for myeloma metastases on MRΙ. The subsequent ultrasound-guided needle biopsies confirmed the extramedullary spread of the disease in both patients. The first case exhibited a match in both functional imaging modalities (PET and MRI) but a mismatch of intense metabolic activity on ¹⁸F-fluorodeoxyglucose (18F-FDG) PET/CT and iso-attenuating liver parenchyma on contrast-enhanced CT. The second case showed a mismatch of signal elevation persistence on diffusion-weighted imaging (DWI) and physiologic 18F-FDG distribution in the liver parenchyma. These cases present different imaging features in MM lesions of the liver using PET/CT and MRI, reflecting the high disease heterogeneity in patients with MM and demonstrating that the use of both PET/CT and MRI may offer complementary information.

A digital dissection of two teleost fishes: comparative functional anatomy of the cranial musculoskeletal system in pike (Esox lucius) and eel (Anguilla anguilla)

Advances in X-ray computed tomography (CT) have led to a rise in the use of non-destructive imaging methods in comparative anatomy. Among these is contrast-enhanced CT scanning, which employs chemical stains to visualize soft tissues. Specimens may then be 'digitally dissected', producing detailed, three-dimensional digital reconstructions of the soft- and hard-tissue anatomy, allowing examination of anatomical structures in situ and making accurate measurements (lengths, volumes, etc.). Here, we apply this technique to two species of teleost fish, providing one of the first comprehensive three-dimensional (3D) descriptions of teleost cranial soft tissue and quantifying differences in muscle anatomy that may be related to differences in feeding ecology. Two species with different feeding ecologies were stained, scanned and imaged to create digital 3D musculoskeletal reconstructions: Esox lucius (Northern Pike), predominantly a suction feeder; and Anguilla anguilla (European eel), which captures prey predominantly by biting. Muscle cross-sectional areas were calculated and compared between taxa, focusing on muscles that serve important roles in feeding. The adductor mandibulae complex - used in biting - was larger in Esox than Anguilla relative to head size. However, the overall architecture of the adductor mandibulae was also very different between the two species, with that of Anguilla better optimized for delivering forceful bites. Levator arcus palatini and sternohyoideus - which are used in suction feeding - are larger in Esox, whereas the levator operculi is larger in Anguilla. Therefore, differences in the size of functionally important muscles do not necessarily correlate neatly with presumed differences in feeding mode.

Imaging Characteristics of Liver Metastases Overlooked at Contrast-Enhanced CT

OBJECTIVE

The purpose of this study was to evaluate the imaging characteristics of liver metastases overlooked at contrast-enhanced CT.

MATERIALS AND METHODS

The records of 746 patients with a diagnosis of liver metastases from colorectal, breast, gastric, or lung cancer between November 2010 and September 2017 were reviewed. Images were reviewed when liver metastases were first diagnosed, and images from prior contrast-enhanced CT examinations were checked if available. These lesions were classified into two groups: missed lesions (those missed on the prior images) and detected lesions (those correctly identified and invisible on the prior images or there were no prior images). Tumor size, contrast-to-noise ratio, location, presence of coexisting liver cysts and hepatic steatosis, and indications for examination were compared between the groups. The t test and Fisher exact test were used to analyze the imaging characteristics of previously overlooked lesions.

RESULTS

The final analysis included 137 lesions, of which 68 were classified as missed. In univariate analysis, contrast-to-noise ratio was significantly lower in missed lesions (95% CI, 2.65 ± 0.24 vs 3.90 ± 0.23; p < 0.001). The proportion of subcapsular lesions (odds ratio, 3.44; p < 0.001), hepatic steatosis (odds ratio, 6.35; p = 0.007), and examination indication other than survey of malignant tumors (odds ratio, 9.07; p = 0.02) were significantly higher for missed lesions.

CONCLUSION

Liver metastases without sufficient contrast enhancement, those in patients with hepatic steatosis, those in subcapsular locations, and those found at examinations for indications other than to assess for tumors were significantly more likely to be overlooked.

Can Texture Analysis Be Used to Distinguish Benign From Malignant Adrenal Nodules on Unenhanced CT, Contrast-Enhanced CT, or In-Phase and Opposed-Phase MRI?

OBJECTIVE

The purpose of this study is to determine whether second-order texture analysis can be used to distinguish lipid-poor adenomas from malignant adrenal nodules on unenhanced CT, contrast-enhanced CT (CECT), and chemical-shift MRI.

MATERIALS AND METHODS

In this retrospective study, 23 adrenal nodules (15 lipid-poor adenomas and eight adrenal malignancies) in 20 patients (nine female patients and 11 male patients; mean age, 59 years [range, 15-80 years]) were assessed. All patients underwent unenhanced CT, CECT, and chemical-shift MRI. Twenty-one second-order texture features from the gray-level cooccurrence matrix and gray-level run-length matrix were calculated in 3D. The mean values for 21 texture features and four imaging features (lesion size, unenhanced CT attenuation, CECT attenuation, and signal intensity index) were compared using a t test. The diagnostic performance of texture analysis versus imaging features was also compared using AUC values. Multivariate logistic regression models to predict malignancy were constructed for texture analysis and imaging features.

RESULTS

Lesion size, unenhanced CT attenuation, and the signal intensity index showed significant differences between benign and malignant adrenal nodules. No significant difference was seen for CECT attenuation. Eighteen of 21 CECT texture features and nine of 21 unenhanced CT texture features revealed significant differences between benign and malignant adrenal nodules. CECT texture features (mean AUC value, 0.80) performed better than CECT attenuation (mean AUC value, 0.60). Multivariate logistic regression models showed that CECT texture features, chemical-shift MRI texture features, and imaging features were predictive of malignancy.

CONCLUSION

Texture analysis has a potential role in distinguishing benign from malignant adrenal nodules on CECT and may decrease the need for additional imaging studies in the workup of incidentally discovered adrenal nodules.

Assessment of pancreatic colloid carcinoma using 18F-FDG PET/CT compared with MRI and enhanced CT

Pancreatic colloid carcinoma (CC) is a rare sub-type of pancreatic adenocarcinoma which has an improved prognosis compared with pancreatic ductal carcinoma. Consequently, the early detection of CC by imaging may be of great significance in guiding patient management and therapeutic decisions. The present study aimed to analyze ¹⁸F-FDG PET/CT findings of CC in comparison to MRI and CT. PET/CT findings in 5 patients with CC were retrospectively reviewed based on visual interpretation and semi-quantitative index of SUV_max and TNR. Four patients received dual-time-point PET/CT scans. Additionally, one patient underwent contrast-enhanced CT scan, one MRI, and three received both. A total of five lesions were detected in five patients. Visually, two cases presented with mild FDG uptake, two with moderate and one with high. The mean of SUV_max and TNR was 5.1±2.2 and 2.8±0.7, respectively. Compared with CCs with low SUV_max, CCs with high SUV_max were more aggressive. No distant metastases were observed in five cases. Among four patients with dual-time-point PET/CT imaging, SUV_max increased in three cases and decreased in one case. The mean early and delayed SUV_max were 4.2±1.1 and 4.7±1.9, respectively (P>0.05). Radiological findings mainly included septated cystic components, internal sponge-like contrast-enhancement, calcification and 'salt-and-pepper sign' on MRI T2-weighted imaging. Thus, PET/CT provided additional information on metabolic tumor activity as well as locoregional and distant staging, which are important prognostic markers and may improve further patient management. However, PET/CT did not show any findings in addition to MRI and contrast-enhanced CT that were unique to CC and allowed a clear differentiation from other pancreatic malignancies.

Concerning CT features used to select patients for treatment of peritoneal metastases, a pictoral essay

BACKGROUND

During the Fifth International Workshop on Peritoneal Surface Malignancy in Milan in 2008, a consensus was reached that contrast-enhanced CT (ceCT) was the principal imaging modality for patients being evaluated for treatment of peritoneal metastases. This fact being accepted, the radiologic criteria for that may exclude patients from a high value cytoreductive surgery (CRS) plus hyperthermic perioperative chemotherapy (HIPEC) have not been reliably determined.

METHODS

From a consensus of surgeons and radiologists, radiologic images were selected and their determinant radiologic characteristics described. The anatomic pathology causing the abnormal images were identified and characterised. The cytoreductive surgical procedures that may, in selected patients, result in a complete resection of the pathology identified were presented.

RESULTS

Radiographs of 15 CT images that cause concern when a patient is being evaluated for CRS were listed. The anatomic pathology these images define and possible surgical resections they require were reviewed. The surgical implications of the absence or presence of a single, or of multiple concerning CT features was extracted from the surgical and radiologic literature.

CONCLUSIONS

There is a definite need to identify new pre-operative imaging parameters to define optimal indication of CRS with HIPEC. The presence of a single concerning radiologic feature is associated with the possibility of an adverse outcome or technically more complex resections associated with increased morbidity and mortality. If two or more of the concerning radiologic features are described from the CT, suboptimal cytoreduction will usually occur.

Preoperative 18F-FDG-PET/CT vs Contrast-Enhanced CT to Identify Regional Nodal Metastasis among Patients with Head and Neck Squamous Cell Carcinoma

Objective Our objective was to compare the accuracy of preoperative positron emission tomography (PET)/computed tomography (CT) and contrast-enhanced CT (CECT) in detecting cervical nodal metastases in patients treated with neck dissection and to scrutinize the ability of each modality to determine nodal stage. Study Design Case series with chart review. Setting Montefiore Medical Center, Bronx, New York. Subjects and Methods Patients who underwent neck dissection at our institution for primary treatment of head and neck squamous cell carcinoma (HNSCC) and had received preoperative PET/CT and CECT were included in this study. Imaging studies were reinterpreted by 3 specialists within the field and compared for interreader agreement. Concordance between radiology and histopathology was measured using neck levels and sides, along with patient nodal stage. Sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and agreement coefficients were calculated. Results Seventy-three patients were included in the study. Sensitivity was 0.69 and 0.94 (level and side) for PET/CT vs 0.53 and 0.66 for CECT ( P = .056, P = .001). Specificity was 0.86 and 0.56 for PET/CT vs 0.91 and 0.76 for CECT ( P = .014, P = .024). No significant difference was found in overall accuracy ( P = .33, P = .88). The overall agreement percentages between N stage called by imaging modality and pathology were 52% and 55% for PET/CT and CECT, respectively. Conclusion No significant difference in sensitivity was found between PET/CT and CECT. CECT was found to have superior specificity compared with PET/CT. The information gleaned from each modality in the pretreatment evaluation of HNSCC appears to be complementary.

Diagnostic Accuracy of Ultrasound, Contrast-enhanced CT, and Conventional MRI for Differentiating Leiomyoma From Leiomyosarcoma

RATIONALE AND OBJECTIVES

This study aimed to determine whether uterine leiomyoma can be distinguished from uterine leiomyosarcoma on ultrasound (US), computed tomography (CT), and/or magnetic resonance imaging (MRI) without diffusion-weighted imaging.

MATERIALS AND METHODS

Institutional review board approval was obtained and informed consent was waived for this Health Insurance Portability and Accountability Act-compliant retrospective case-control diagnostic accuracy study. All subjects with resected uterine leiomyosarcoma diagnosed over a 17-year period (1998-2014) at a single institution for whom pre-resection US (n = 10), CT (n = 11), or MRI (n = 7) was available were matched by tumor size and imaging modality with 28 subjects with resected uterine leiomyoma. Six blinded radiologists (three attendings, three residents) assigned 5-point Likert scores for the following features: (1) margins, (2) necrosis, (3) hemorrhage, (4) vascularity, (5) calcifications, (6) heterogeneity, and (7) likelihood of malignancy (primary end point). Mean suspicion scores were calculated and receiver operating characteristic curves were generated. The ability of individual morphologic features to predict malignancy was assessed with logistic regression.

RESULTS

Mean suspicion scores were 2.5 ± 1.2 (attendings) and 2.4 ± 1.3 (residents) for leiomyoma, and 2.7 ± 1.3 (attendings) and 2.7 ± 1.4 (residents) for leiomyosarcoma. The areas under the receiver operating characteristic curves (range: 0.330-0.685) were not significantly different from chance, either overall (P = .36-.88) or by any modality (P = .28-.96), for any reader. Reader experience had no effect on diagnostic accuracy. No morphologic parameter was significantly predictive of malignancy (P = .10-.97).

CONCLUSIONS

Uterine leiomyoma cannot be differentiated accurately from leiomyosarcoma on US, CT, or MRI without diffusion-weighted imaging.