A CT-based novel model to predict pathological complete response of locally advanced esophageal squamous cell carcinoma to neoadjuvant PD-1 blockade in combination with chemotherapy

PURPOSE

To develop a novel CT-based model to predict pathological complete response (pCR) of locally advanced esophageal squamous cell carcinoma (ESCC) to neoadjuvant PD-1 blockade in combination with chemotherapy.

METHODS

117 consecutive patients with locally advanced ESCC were stratified into training cohort (n = 82) and validation cohort (n = 35). All patients underwent non-contrast and contrast-enhanced thoracic and upper abdominal CT before neoadjuvant PD-1 blockade in combination with chemotherapy (CTpre), and after two cycles of the therapy before esophagectomy (CTpost), respectively. Univariate analyses and binary logistic regression analyses of ESCC quantitative and qualitative CT features were performed to determine independent predictors of pCR. Prediction performance of the model developed with independent predictors from training cohort was evaluated by receiver operating characteristic (ROC) analysis, and validated by Kappa test in validation cohort.

RESULTS

In training cohort, the difference in CT attenuation between tumor and background normal esophageal wall obtained from CTpre (ΔTNpre), tumoral increased CT attenuation after contrast-enhanced scan from CTpost images (ΔTpost) and gross tumor volume (GTV) from CTpre were independent predictors of pCR (odds ratio = 1.128 (95% confidence interval (CI): 0.997-1.277), 1.113 (95%CI: 0.965-1.239) and 1.133 (95%CI: 1.043-1.231), respectively, all P-values < 0.05). Logistic regression model equation (0.121 × ΔTNpre + 0.107 × ΔTpost + 0.125 × GTV - 9.856) to predict pCR showed the best performance with an area under the ROC of 0.876, compared with each independent predictor. The good performance was confirmed by the Kappa test (K-value = 0.796) in validation cohort.

CONCLUSIONS

This novel model can be reliable to predict pCR to neoadjuvant PD-1 blockade in combination with chemotherapy in locally advanced ESCC.

Interleukin 18 and IL-18 BP response to Sars-CoV-2 virus infection

The immune response to the SARS-CoV-2 infection is crucial to the patient outcome. IL-18 is involved in the lymphocyte response to the disease and it is well established its important role in the complex developing of the host response to viral infection. This study aims at the analysis of the concentrations of IL-18, IL-18BP, INF-γ at the onset of the SARS-CoV-2 infection. The serum levels of measured interleukins were obtained through enzyme-linked immunosorbent assay. Furthermore, the free fraction of IL-18 was numerically evaluated. The enrolled patients were divided in two severity groups according to a threshold value of 300 for the ratio of arterial partial pressure of oxygen and fraction of inspired oxygen fraction and according to the parenchymal involvement as evaluated by computerized tomography at the admittance. In the group of patients with a more severe disease, a significant increase of the IL-18, INF-γ and IL-18BP levels have been observed, whereas the free IL-18 component values were almost constant. The results confirm that, at the onset of the disease, the host response keep the inflammatory cytokines in an equilibrium and support the hypothesis to adopt the IL-18BP modulation as a possible and effective therapeutic approach.

Development of clinical-guideline-based mobile application and its effect on head CT scan utilization in neurology and neurosurgery departments

Background

There is little evidence regarding the adoption and intention of using mobile apps by health care professionals (HCP) and the effectiveness of using mobile apps among physicians is still unclear. To address this challenge, the current study seeks two objectives: developing and implementing a head CT scan appropriateness criteria mobile app (HAC app), and investigating the effect of HAC app on CT scan order.

Methods

A one arm intervention quasi experimental study with before/after analysis was conducted in neurology & neurosurgery (N&N) departments at the academic hospital. We recruited all residents' encounters to N&N departments with head CT scan to examine the effect of HAC app on residents' CT scan utilization. The main outcome measure was CT scan order per patient for seven months at three points, before the intervention, during the intervention, after cessation of the intervention -post-intervention follow-up. Data for CT scan utilization were collected by reviewing medical records and then analyzed using descriptive statistics, Kruskal-Wallis, and Mann-Whitney tests. A focus group discussion with residents was performed to review and digest residents' experiences during interaction with the HAC app.

Results

Sixteen residents participated in this study; a total of 415 N&N encounters with CT scan order, pre-intervention 127 (30.6%), intervention phase 187 (45.1%), and 101 (24.3%) in the post-intervention follow-up phase were included in this study. Although total CT scan utilization was statistically significant during three-time points of the study (P = 0.027), no significant differences were found for CT utilization after cessation of the intervention (P = 1).

Conclusion

The effect of mobile devices on residents' CT scan ordering behavior remains open to debate since the changes were not long-lasting. Further studies based on real interactive experiences with mobile devices is advisable before it can be recommended for widespread use by HCP.

Facilitating standardized COVID-19 suspicion prediction based on computed tomography radiomics in a multi-demographic setting

Objective

To develop an automatic COVID-19 Reporting and Data System (CO-RADS)–based classification in a multi-demographic setting.

Methods

This multi-institutional review boards–approved retrospective study included 2720 chest CT scans (mean age, 58 years [range 18–100 years]) from Italian and Russian patients. Three board-certified radiologists from three countries assessed randomly selected subcohorts from each population and provided CO-RADS–based annotations. CT radiomic features were extracted from the selected subcohorts after preprocessing steps like lung lobe segmentation and automatic noise reduction. We compared three machine learning models, logistic regression (LR), multilayer perceptron (MLP), and random forest (RF) for the automated CO-RADS classification. Model evaluation was carried out in two scenarios, first, training on a mixed multi-demographic subcohort and testing on an independent hold-out dataset. In the second scenario, training was done on a single demography and externally validated on the other demography.

Results

The overall inter-observer agreement for the CO-RADS scoring between the radiologists was substantial (k = 0.80). Irrespective of the type of validation test scenario, suspected COVID-19 CT scans were identified with an accuracy of 84%. SHapley Additive exPlanations (SHAP) interpretation showed that the “wavelet_(LH)_GLCM_Imc1” feature had a positive impact on COVID prediction both with and without noise reduction. The application of noise reduction improved the overall performance between the classifiers for all types.

Conclusion

Using an automated model based on the COVID-19 Reporting and Data System (CO-RADS), we achieved clinically acceptable performance in a multi-demographic setting. This approach can serve as a standardized tool for automated COVID-19 assessment.

Keypoints

• Automatic CO-RADS scoring of large-scale multi-demographic chest CTs with mean AUC of 0.93 ± 0.04.

• Validation procedure resembles TRIPOD 2b and 3 categories, enhancing the quality of experimental design to test the cross-dataset domain shift between institutions aiding clinical integration.

• Identification of COVID-19 pneumonia in the presence of community-acquired pneumonia and other comorbidities with an AUC of 0.92.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-022-08730-6.

Value of spectral detector computed tomography to differentiate infected from noninfected thoracoabominal fluid collections

PURPOSE

To investigate the diagnostic value of spectral detector CT (SDCT)-derived virtual non-contrast (VNC), virtual monoenergetic images (VMI) and iodine overlays (IO) for distinguishing infected from noninfected fluid collections (FC) in the chest or abdomen.

METHOD

This retrospective study included 58 patients with venous phase SDCT with 77 FC. For all included FC, microbiological analysis of aspirated fluid served as reference. For quantitative analysis, wall thickness was measured, and (ROI)-based analysis performed within the fluid, the FC's wall (if any) and the aorta. Two radiologists qualitatively evaluated visibility of wall enhancement, diagnostic confidence regarding infection of fluid collection, confidence of CT-guided drainage catheter placement and visibility of anatomical landmarks in conventional images (CI) and VNC, VMI_40keV, IO.

RESULTS

Wall thickness significantly differed between infected (n = 46) and noninfected (n = 31) FC (3.5 ± 1.8 mm vs. 1.4 ± 1.8 mm, AUC = 0.81; p < 0.05). Fluid attenuation and wall enhancement was significantly higher in infected as compared to noninfected FC in all reconstructions (p < 0.05, respectively). Highest AUC regarding A) attenuation in fluid was yielded in CI and VMI_70,80keV (0.75); B) wall enhancement in CI (0.88) followed by iodine concentration (0.86). Contrast-to-noise ratio of wall vs. fluid was highest in VMI_40keV (p < 0.05). All assessed qualitative parameters received significantly higher ratings when using spectral reconstructions vs. CI (p for all <0.05), except for visibility of wall enhancement.

CONCLUSION

Spectral reconstructions improve the assessment of infected from noninfected thoracoabdominal fluid collections and depiction of wall enhancement. Diagnostic performance of the quantitative measurements in spectral reconstructions were comparable with measurements in conventional images.

Quantitative Assessment of Radiologically Indeterminate Local Colonic Wall Thickening on Iodine Density Images Using Dual-Layer Spectral Detector CT

RATIONALE AND OBJECTIVES

To assess local colonic wall thickening (LCWT, thicknesses: >3 mm, lengths: <5 cm) quantitatively on iodine density images using dual-layer spectral detector computed tomography (DLSCT).

MATERIALS AND METHODS

This retrospective study included 80 patients who underwent both conventional contrast-enhanced CT and colonoscopy within one month. The region of interest was delineated on the chosen images with the iodine density image model. The iodine concentration (IC), normalized IC (NIC), and thickness of the colonic wall in the lesion area were compared between the pathological and nonpathological groups.

RESULTS

There were 50 patients whose area of LCWT discovered at CT scans displayed colon neoplasia at colonoscopy. The other 30 patients with LCWT on CT images showed normal appearances during colonoscopy. There was no significant difference in colonic wall thickness between the pathological and nonpathological (p> 0.05) LCWT groups. The IC and NIC of patients with colon neoplasms were significantly higher than those with nonpathologic LCWT (both p< 0.001). The ROC curve showed that when IC and NIC was 1.49 mg/mL and 0.33, the sensitivity and specificity for diagnosing colon neoplasm were 91.5% and 75.8%, 85.1% and 84.8%, respectively.

CONCLUSION

IC and NIC values from DLSCT could provide a satisfied diagnostic value to identify LCWT caused by colon neoplasia.

Magnetic resonance versus computed tomography for the detection of retroperitoneal lymph node metastasis due to testicular cancer: A systematic literature review

INTRODUCTION

It is essential to see if MRI can be used as an alternative to CT for the detection of retroperitoneal lymphadenopathy in patients with testicular neoplasms. By doing so, the amount of radiation received by these young patients might be reduced.

MATERIAL AND METHODS

A systematic literature review was carried out in 5 databases between January 1984 until December 2020. The articles included were randomized and non-randomized clinical trials, cross-sectional studies, cohort, case and control, and retrospective studies that compare the accuracy of MRI against CT to detect retroperitoneal lymph nodes in patients with testicular neoplasms.

RESULTS

The search string initially retrieved 222 non duplicated papers from which a total of 3 studies of diagnostic accuracy were included for analysis. These articles evaluated a total of 127 patients with testicular neoplasm; the sample size per study ranged from 25 to 52 patients, with a mean age between 29-34 years. MRI presented a sensitivity ranging from 98-80% and specificity of 100 % when read by an experienced radiologist. However, when it was read by a radiologist with 1 year of experience, the sensitivity dropped to 78 % and specificity to 91%.

CONCLUSION

This systematic literature review shows a knowledge gap since not much has been published regarding this topic; therefore, randomized clinical trials are mandatory. Research on when to use MRI over CT is necessary to reduce radiation exposure. The authors strongly suggest that readers start researching on this subject.

Intra-scan inter-tissue variability can help harmonize radiomics features in CT

OBJECTIVE

We studied the repeatability and the relative intra-scan variability across acquisition protocols in CT using phantom and unenhanced abdominal series.

METHODS

We used 17 CT scans from the Credence Cartridge Radiomics Phantom database and 20 unenhanced multi-site non-pathologic abdominal patient series for which we measured spleen and liver tissues. We performed multiple measurements in extracting 9 radiomics features. We defined a "tandem" as the measurement of a given tissue (or material) by a given radiomics. For each tandem, we assessed the proportion of the variability attributable to repetitions, acquisition protocols, material, or patient. We analyzed the distribution of the intra-scan correlation between pairs of tandems and checked the impact of correlation coefficient greater than 0.90 in comparing paired and unpaired differences.

RESULTS

The repeatability of radiomics features depends on the measured material; 56% of tandems were highly repeatable. Histogram-derived radiomics were generally less repeatable. Nearly 60% of relative radiomics measurements had a correlation coefficient higher than 0.90 allowing paired measurements to improve reliability in detecting the difference between two materials. The analysis of liver and spleen tissues showed that measurement variability was negligible with respect to other variabilities. As for phantom data, we found that gray level zone length matrix (GLZLM)-derived radiomics and gray level co-occurrence matrix (GLCM)-derived radiomics were the most correlating features. For these features, relative intra-scan measurements improved the detection of different materials or tissues.

CONCLUSIONS

We identified radiomics features for which the intra-scan measurements between tissues are linearly correlated. This property represents an opportunity to improve tissue characterization and inter-site harmonization.

KEY POINTS

• The repeatability of radiomics features on CT depends on the measured material or tissue. • Some tandems of radiomics features/tissues are linearly affected by the variability of acquisition protocols on CT. • Relative intra-scan measurements are an opportunity for improving quantitative imaging on CT.

CT evaluation of patent artery after percutaneous cryoablation of renal cell carcinoma

PURPOSE

The purpose of this retrospective study was to determine the incidence of persistent patent artery after percutaneous cryoablation of renal cell carcinoma (RCC) and the relationship between patent arteries one month after cryoablation and early tumor progression.

MATERIALS AND METHODS

One hundred and fifty-nine patients (112 men, 47 women; mean age, 63.6±14.6 [SD] years; age range: 21-91 years) who underwent percutaneous cryoablation for 186 RCCs (mean diameter, 1.9±0.6 [SD] cm; range: 0.7-4.0cm) were retrospectively included. After cryoablation, patients underwent contrast-enhanced computed tomography (CT) with ≤2-mm slice thickness within one week from cryoablation, and at one, three, and six months. The time course of patent artery in the ablated renal parenchyma after cryoablation was the primary endpoint. The relationships between patent arteries one month after cryoablation and treatment effectiveness, tumor vascularity, tumor enhancement one month after cryoablation, tumor subtype, and renal function changes were evaluated as secondary endpoints.

RESULTS

CT showed patent arteries in the ablated renal parenchyma within one week in 166 RCCs (89.2%), at one month in 54 RCCs (29.0%), at three months in 8 RCCs (4.3%), and at six months in 2 RCCs (1.1%). The presence of patent artery one month after cryoablation was significantly associated with tumor enhancement at the same time point (P=0.015). There was no association between patent arteries one month after cryoablation and treatment effectiveness (P=0.693).

CONCLUSION

Patent arteries in the ablated renal parenchyma are commonly observed on CT examination after percutaneous cryoablation of RCC. However, they gradually disappear and do not require specific treatment.

Ultra-low-dose chest CT imaging of COVID-19 patients using a deep residual neural network

OBJECTIVES

The current study aimed to design an ultra-low-dose CT examination protocol using a deep learning approach suitable for clinical diagnosis of COVID-19 patients.

METHODS

In this study, 800, 170, and 171 pairs of ultra-low-dose and full-dose CT images were used as input/output as training, test, and external validation set, respectively, to implement the full-dose prediction technique. A residual convolutional neural network was applied to generate full-dose from ultra-low-dose CT images. The quality of predicted CT images was assessed using root mean square error (RMSE), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR). Scores ranging from 1 to 5 were assigned reflecting subjective assessment of image quality and related COVID-19 features, including ground glass opacities (GGO), crazy paving (CP), consolidation (CS), nodular infiltrates (NI), bronchovascular thickening (BVT), and pleural effusion (PE).

RESULTS

The radiation dose in terms of CT dose index (CTDIvol) was reduced by up to 89%. The RMSE decreased from 0.16 ± 0.05 to 0.09 ± 0.02 and from 0.16 ± 0.06 to 0.08 ± 0.02 for the predicted compared with ultra-low-dose CT images in the test and external validation set, respectively. The overall scoring assigned by radiologists showed an acceptance rate of 4.72 ± 0.57 out of 5 for reference full-dose CT images, while ultra-low-dose CT images rated 2.78 ± 0.9. The predicted CT images using the deep learning algorithm achieved a score of 4.42 ± 0.8.

CONCLUSIONS

The results demonstrated that the deep learning algorithm is capable of predicting standard full-dose CT images with acceptable quality for the clinical diagnosis of COVID-19 positive patients with substantial radiation dose reduction.

KEY POINTS

• Ultra-low-dose CT imaging of COVID-19 patients would result in the loss of critical information about lesion types, which could potentially affect clinical diagnosis. • Deep learning-based prediction of full-dose from ultra-low-dose CT images for the diagnosis of COVID-19 could reduce the radiation dose by up to 89%. • Deep learning algorithms failed to recover the correct lesion structure/density for a number of patients considered outliers, and as such, further research and development is warranted to address these limitations.

CT features of lung metastases from pancreatic adenocarcinoma: Correlation with histopathologic findings

PURPOSE

The purpose of this study was to evaluate the prevalence of an atypical, alveolar presentation of pulmonary metastases from pancreatic adenocarcinoma (PDAC) on computed tomography (CT) and to correlate CT features with those obtained at histopathologic analysis.

MATERIAL AND METHODS

A total of 76 patients with lung metastases from PDAC over a 10-year period (2009-2019) in a French university hospital were retrospectively included. There were 34 men and 42 women with a mean age of 67.6±11.3 (SD) years (range: 38-89 years). CT features of PDAC were classified according to their presentations as usual metastatic pattern or atypical alveolar pattern; the atypical alveolar pattern corresponding to either ground glass nodules or opacities, solid nodules with a halo sign, "air-space" nodules with air bronchogram, or parenchymal consolidation. Imaging-histopathologic correlation was performed when tissue samples were available.

RESULTS

Pulmonary metastases were synchronous in 36 patients (36/76; 47%) and metachronous in 40 patients (40/76; 53%). A predominant alveolar presentation on CT was observed in 17 patients (17/76, 22%). Nodules with halo sign were the predominant alveolar pattern in 7 patients (7/17; 41%), air-space nodules were predominant in 4 patients (4/17; 24%) whereas pure ground glass nodules and consolidations were observed as predominant features in 3 patients (3/17; 18%) each. For 5 patients who had histopathological confirmation, alveolar metastases of PDAC were characterized by columnar tumor cells lining the alveolar wall, which was not seen in other radiological presentations, whereas there were no differences regarding mucin secretion between pulmonary metastases with alveolar presentation and those with typical pattern.

CONCLUSIONS

Lung metastases from PDAC may present with a so-called "alveolar" pattern on CT. This misleading CT features is found in 22% of patients with lung metastases from PDAC and is due to lepidic growth of the metastatic cells.

Computed tomography-derived myocardial extracellular volume: an early biomarker of cardiotoxicity in esophageal cancer patients undergoing radiation therapy

Objectives

We aimed to assess extracellular volume (ECV) through non-gated, contrast-enhanced computed tomography (CT) before and after radiation therapy (RT) in patients with esophageal cancer (EC).

Materials and methods

EC patients who had undergone CT before and after RT were retrospectively assessed. Patients with preexisting cardiovascular disease or with heavily artifacted CT were excluded. ECV was calculated using density values for the myocardial septum and blood pool. Data were reported as mean and standard deviation or median and interquartile range according to their distribution; t test or Wilcoxon and Pearson r or Spearman ρ were subsequently used.

Results

Twenty-one patients with stage ≥ IB EC, aged 64 ± 18 years, were included. Mean and maximum RT doses were 21.2 Gy (16.9–24.1) and 42.5 Gy (41.8–49.2), respectively. At baseline (n = 21), hematocrit was 39% ± 4%, ECV 27.9% ± 3.5%; 35 days (30–38) after RT (n = 20), hematocrit was 36% ± 4%, lower than at baseline (p = 0.002), ECV 30.3% ± 8.3%, higher than at baseline (p = 0.081); at follow-up 420 days (244–624) after RT (n = 13), hematocrit was 36% ± 5%, lower than at baseline (p = 0.030), ECV 31.4% ± 4.5%, higher than at baseline (p = 0.011). No patients showed signs of overt cardiotoxicity. ECV early after RT was moderately positively correlated with maximum RT dose (ρ = 0.50, p = 0.036).

Conclusions

In EC patients, CT-derived myocardial ECV was increased after RT and may thus appear as a potential early biomarker of cardiotoxicity.

Using texture analysis as a predictive factor of subtype, grade and stage of renal cell carcinoma

OBJECTIVE

The aim of this study was to evaluate the correlation between the tissue texture analysis and the histological subtypes, grade and stage of the disease in patients with renal cell carcinoma (RCC).

MATERIALS AND METHODS

Seventy-seven patients who underwent computed tomography due to renal mass and diagnosed with RCC as a result of pathological examination were retrospectively analyzed. In these analyses, the demographic characteristics, pathological and radiological findings of the patients were evaluated. The masses were introduced to the Radiomics extension of the software and the first- and second-order texture analysis parameters were obtained. The correlation of these parameters with histological subtype, Fuhrman grade and TNM stage was investigated.

RESULTS

In the comparison of the Radiomics values by stages, "minimum", "Long Run Low Gray-level Emphasis" values were higher in the stage 1-2 group, while "Energy", "Total energy", "Range", "Joint Average", "Sum Average", "Gray-Level Non-Uniformity", "Short-Run High Gray-level Emphasis ", "Run Length Non-Uniformity "and "High Gray-Level Run Emphasis "values were higher in the stage 3-4 group. Of these parameters, only "Gray-Level Non-Uniformity" and "Run Length Non-Uniformity'' values were significantly lower in tumors with low Fuhrman grade (1-2) and low TNM stage (1-2). There was no statistically significant correlation between the parameters found to be significant in histological subtype differentiation and Fuhrman grade and TNM stage.

CONCLUSION

This study demonstrates that "Gray-Level Non-Uniformity" and "Run Length Non-Uniformity "parameters in the texture analysis method can be used to evaluate the prognosis in patients with RCC.

Value of chest computed tomography scan in diagnosis of COVID-19; a systematic review and meta-analysis

Purpose

Real-time polymerase chain reaction (RT-PCR) and chest computed tomography (CT) scan are main diagnostic modalities of coronavirus disease 2019 (COVID-19). However, there is still no consensus on which of these methods is superior to the other. Therefore, the present meta-analysis was designed to answer to the question whether CT scan can be used in diagnosis of COVID-19 or not.

Methods

Searches were performed in Medline, Embase, Scopus, and Web of Science databases until the end of April 2020. Two researchers gathered the data of diagnostic accuracy studies that had attempted to evaluate sensitivity and specificity of CT scan in diagnosis of COVID-19.

Results

Data of 9 studies were included. Area under the curve of ground glass opacity (GGO), consolidation, pleural effusion, other CT features, and simultaneous observation of GGO with other CT features was 0.64 (95% CI 0.60-0.69), 0.30 (95% CI 0.26-0.34), 0.60 (95% CI 0.56-0.64), 0.61 (95% CI 0.56-0.65), and 0.90 (95% CI 0.87-0.92), respectively. Sensitivity and specificity of simultaneous observation of GGO with other CT scan features was higher than all of the other signs. Sensitivity, specificity, and diagnostic odds ratio of this sign was calculated to be 0.90, 0.89, and 20, respectively.

Conclusion

Simultaneous observation of GGO and other features of viral pneumonia in CT scan had optimum performance in detection of COVID-19. However, it is suggested to make the final diagnosis based on both CT scan and RT-PCR, as none of the two diagnostic modalities are reliable alone.

Eight-year follow-up of locally advanced lymphoepithelioma-like carcinoma at upper urinary tract: A case report

BACKGROUND

Urinary tract lymphoepithelioma-like carcinoma is rarely seen. Although it is termed after lymphoepithelioma at the nasopharynx, it behaves more like high grade urothelial carcinoma by immunohistochemical features. Most published literatures focused on its rarity but few discussed results of long-term follow-ups. As no available guidelines are applicable, we postulated that principles should be similar to that of urothelial carcinoma at urinary tract. As of now, this work features the longest follow-up of this cancer at the upper urinary tract.

CASE SUMMARY

A 63-year-old female had a chief complaint of intermittent left flank pain for 2 mo, along with accompanying symptoms including vomiting and body weight loss, about 7 kg over 2 mo. Laboratory data showed normocytic anemia, mildly poor renal function, and hyperparathyroidism. Urine analysis showed mild hematuria. Computed tomography showed a 4.2-cm-width irregular mass over left renal pelvic and enlarged lymph node at the left renal hilum. Whole-body bone scan was negative of active bone lesions. Biopsy from ureteroscopy showed urothelial carcinoma. Specimen from laparoscopic nephroureterectomy with bladder cuff resection showed lymphoepithelioma-like carcinoma with muscular invasion (pT3). She took adjuvant chemotherapies of 2 cycles and full courses of radiation therapy. No recurrence was observed with designed investigative programs.

CONCLUSION

Locally advanced urinary tract lymphoepithelioma-like carcinoma could benefit from nephroureterectomy and bladder cuff excision in terms of recurrence-free survival.

Ultra-low-dose chest CT imaging of COVID-19 patients using a deep residual neural network

OBJECTIVES

The current study aimed to design an ultra-low-dose CT examination protocol using a deep learning approach suitable for clinical diagnosis of COVID-19 patients.

METHODS

In this study, 800, 170, and 171 pairs of ultra-low-dose and full-dose CT images were used as input/output as training, test, and external validation set, respectively, to implement the full-dose prediction technique. A residual convolutional neural network was applied to generate full-dose from ultra-low-dose CT images. The quality of predicted CT images was assessed using root mean square error (RMSE), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR). Scores ranging from 1 to 5 were assigned reflecting subjective assessment of image quality and related COVID-19 features, including ground glass opacities (GGO), crazy paving (CP), consolidation (CS), nodular infiltrates (NI), bronchovascular thickening (BVT), and pleural effusion (PE).

RESULTS

The radiation dose in terms of CT dose index (CTDI_vol) was reduced by up to 89%. The RMSE decreased from 0.16 ± 0.05 to 0.09 ± 0.02 and from 0.16 ± 0.06 to 0.08 ± 0.02 for the predicted compared with ultra-low-dose CT images in the test and external validation set, respectively. The overall scoring assigned by radiologists showed an acceptance rate of 4.72 ± 0.57 out of 5 for reference full-dose CT images, while ultra-low-dose CT images rated 2.78 ± 0.9. The predicted CT images using the deep learning algorithm achieved a score of 4.42 ± 0.8.

CONCLUSIONS

The results demonstrated that the deep learning algorithm is capable of predicting standard full-dose CT images with acceptable quality for the clinical diagnosis of COVID-19 positive patients with substantial radiation dose reduction.

KEY POINTS

• Ultra-low-dose CT imaging of COVID-19 patients would result in the loss of critical information about lesion types, which could potentially affect clinical diagnosis. • Deep learning-based prediction of full-dose from ultra-low-dose CT images for the diagnosis of COVID-19 could reduce the radiation dose by up to 89%. • Deep learning algorithms failed to recover the correct lesion structure/density for a number of patients considered outliers, and as such, further research and development is warranted to address these limitations.

Improved differentiation between primary lung cancer and pulmonary metastasis by combining dual-energy CT-derived biomarkers with conventional CT attenuation

OBJECTIVES

To assess the clinical utility of dual-energy CT (DE-CT)-derived iodine concentration (IC) and effective Z (Z^eff) in addition to conventional CT attenuation (HU) for the discrimination between primary lung cancer (LC) and pulmonary metastases (PM) from different primary malignancies.

METHODS

DE-CT scans of 79 patients with LC (3 histopathologic subgroups) and 89 patients with PM (5 histopathologic subgroups) were evaluated. Quantitative IC, Z^eff, and conventional HU values were extracted and normalized to the thoracic aorta. Differences between groups were assessed by pairwise Welch's t test. Correlation and linear regression analyses were used to examine the relationship of imaging parameters in LC and PM. Diagnostic accuracy was measured by the area under receiver operator characteristic curve (AUC) and validated based on resampling methods.

RESULTS

Significant differences between subgroups of LC and PMs were noted for all imaging parameters, with the highest number of significant pairs for IC. In univariate analysis, only IC was a significant diagnostic feature for discriminating LC from PM (p = 0.03). All quantitative imaging parameters correlated significantly (p < 0.0001, respectively), with the highest correlation between IC and Z^eff (r = 0.91), followed by IC and HU (r = 0.76) and Z^eff and HU (r = 0.73). Diagnostic models combining IC or Z^eff with HU (IC+HU: AUC = 0.73; Z^eff+HU: AUC = 0.69; IC+Z^eff+HU: AUC = 0.73) were not significantly different and outperformed individual parameters (IC: AUC = 0.57; Z^eff: AUC = 0.57; HU: AUC = 0.55) in diagnostic accuracy (p < 0.05, respectively).

CONCLUSION

DE-CT-derived IC or Z^eff and conventional HU represent complementary imaging parameters, which, if used in combination, may improve the differentiation between LC and PM.

KEY POINTS

• Individual quantitative imaging parameters derived from DE-CT (iodine concentration, effective Z) and conventional CT (HU) provide complementary diagnostic information for the differentiation of primary lung cancer and pulmonary metastases. • A combination of conventional HU and DE-CT parameters enhances the diagnostic utility of individual parameters.

Reporting frequency of radiology findings increases after introducing visual rating scales in the primary care diagnostic work up of subjective and mild cognitive impairment

Objectives

Study the effect of introducing a template for radiological reporting of non-enhanced computed tomography (NECT) in the primary care diagnostic work up of cognitive impairment using visual rating scales (VRS).

Methods

Radiology reports were assessed regarding compliance with a contextual report template and the reporting of the parameters medial temporal lobe atrophy (MTA), white matter changes (WMC), global cortical atrophy (GCA), and width of lateral ventricles (WLV) using established VRS in two age-matched groups examined with NECT before (n = 111) and after (n = 125) the introduction of contextual reporting at our department. True positive rate (TPR) and true negative rate (TNR) before and after were compared.

Results

We observed a significant increase in the percentage of radiology reports with mentioning of MTA from 29 to 76% (p < 0.001), WMC from 69 to 86% (p < 0.01), and GCA from 54 to 82% (p < 0.001). We observed a significant increase in the percentages of reports where all of the parameters were mentioned, from 6 to 29% (p < 0.001). There was a significant increase in TPR from 10 to 55% for MTA.

Conclusion

This study suggests that contextual radiological assessment using VRS could increase the reporting frequency of radiology findings in the diagnostic work up of cognitive impairment but compliance with templates may be difficult to endorse.

Key Points

• Introducing visual rating scales in clinical practice increases the reporting frequency of MTA, WMC, and GCA in the diagnostic work up of subjective and mild cognitive impairment.

• Introducing visual rating scales has an effect on the true positive rate of reported MTA.

• Compliance with contextual radiology templates remains low when use of the template is not enforced by the department leadership.

Calcified brain metastases may be more frequent than normally considered

Objectives

To verify the incidence of calcified brain metastases (CBM), illustrating the different presentation patterns and histology of primary tumor.

Methods

A series of 1002 consecutive brain computed tomography (CT) scans of patients with known primary tumors was retrospectively assessed. CBM were defined by the presence of calcification within intra-axial-enhancing lesions; identification of CBM was based on visual examination and ROI analysis (> 85 Hounsfield units). Also, calcifications in the primary tumor of all patients with brain metastases were evaluated. In CBM patients, we investigated the type of calcifications (punctate, nodular, cluster, ring, coarse), the histology of primary tumor, and if a previous RT was performed.

Results

Among 190 (18.9%) patients with brain metastatic disease, 34 presented with CBM (17.9%). Sixteen patients were previously treated with RT, while 18 presented calcifications ab initio (9.5% of all brain metastases). The majority of patients with CBM had a primitive lung adenocarcinoma (56%), followed by breast ductal invasive carcinoma (20%) and small cell lung carcinoma (11.8%). CBM were single in 44.1% of patients and multiple in 55.9%. With regard to the type of calcifications, the majority of CBM were punctate, without specific correlations between calcification type and histology of primary tumor. No patients with ab initio CBM had calcifications in primary tumor.

Conclusion

In conclusion, our data show that CBM are more common than usually thought, showing an incidence of 9.5% ab initio in patients with brain metastases. This study underlines that neuroradiologists should not overlook intraparenchymal brain calcifications, especially in oncologic patients.

Key Points

• Among the differential diagnosis of brain intraparenchymal calcifications, metastases are considered uncommon and found predominantly in patients treated with radiotherapy (RT).

• Our data show that CBM are more common than usually thought, showing an incidence of 9.5% ab initio in patients with brain metastases.

• A proportion of intraparenchymal brain calcifications, especially in oncologic patients, might represent evolving lesions and neuroradiologists should not overlook them to avoid a delay in diagnosis and treatment.

Risk stratification of thymic epithelial tumors by using a nomogram combined with radiomic features and TNM staging

OBJECTIVES

To construct and validate a nomogram model that integrated the CT radiomic features and the TNM staging for risk stratification of thymic epithelial tumors (TETs).

METHODS

A total of 136 patients with pathology-confirmed TETs who underwent CT examination were collected from two institutions. According to the WHO pathological classification criteria, patients were classified into low-risk and high-risk groups. The TNM staging was determined in terms of the 8th edition AJCC/UICC staging criteria. LASSO regression was performed to extract the optimal features correlated to risk stratification among the 704 radiomic features calculated. A nomogram model was constructed by combining the Radscore and the TNM staging. The clinical performance was evaluated by ROC analysis, calibration curve, and decision curve analysis (DCA). The Kaplan-Meier (KM) analysis was employed for survival analysis.

RESULTS

Five optimal features identified by LASSO regression were employed to calculate the Radscore correlated to risk stratification. The nomogram model showed a better performance in both training cohort (AUC = 0.84, 95%CI 0.75-0.91) and external validation cohort (AUC = 0.79, 95%CI 0.69-0.88). The calibration curve and DCA analysis indicated a better accuracy of the nomogram model for risk stratification than either Radscore or the TNM staging alone. The KM analysis showed a significant difference between the two groups stratified by the nomogram model (p = 0.02).

CONCLUSIONS

A nomogram model that integrated the radiomic signatures and the TNM staging could serve as a reliable model of risk stratification in predicting the prognosis of patients with TETs.

KEY POINTS

• The radiomic features could be associated with the TET pathophysiology. • TNM staging and Radscore could independently stratify the risk of TETs. • The nomogram model is more objective and more comprehensive than previous methods.

Post-processing of computed tomography perfusion in patients with acute cerebral ischemia: variability of inter-reader, inter-region of interest, inter-input model, and inter-software

OBJECTIVE

To determine the reproducibility of quantitative computed tomography perfusion (CTP) parameters generated using different post-processing methods and identify the relative impact of subjective factors on the robustness of CTP parameters in acute ischemic stroke (AIS).

MATERIALS AND METHODS

A total of 80 CTP datasets from patients with AIS or transient ischemic attack (TIA) were retrospectively post-processed by two observers using different regions of interest (ROI) types, input models, and software. The CTP parameters were derived for 10 parenchymal ROIs. The intra-class correlation coefficients (ICCs) were used to assess the reproducibility of the CTP parameters for various post-processing methods. The Spearman correlation test was used to detect potential relationships between software and input models.

RESULTS

The ICCs with 95% confidence intervals (CIs) were 0.94 (0.93-0.96), 0.94 (0.92-0.96), 0.82 (0.79-0.86), and 0.87 (0.85-0.90) for inter-reader agreement by using elliptic ROI, irregular ROI, single-input model, and dual-input model, respectively. The ICCs with 95% CI were 0.98 (0.98-0.98), 0.46 (0.43-0.50), and 0.25 (0.20-0.30) for inter-ROI type, inter-input model, and inter-software agreement, respectively.

CONCLUSIONS

Although the CTP parameters were stable when measured using different readers with different ROI types, they varied for different input models and software. The standardization of CTP post-processing is essential to reduce variability of CTP values.

KEY POINTS

• The CTP parameters derived by different readers with different ROI types have agreements that range from good to excellent. • The CTP parameters derived from different input models and software programs have poor agreement but significant correlations.

Morphology of the Esophageal Hiatus: Is It Different in 3 Types of Hiatus Hernias?

Background/Aims

The esophageal hiatus is formed by the right crus of the diaphragm in the majority of subjects. Contraction of the hiatus exerts a sphincter-like action on the lower esophageal sphincter (LES). The aim is to study the hiatal anatomy (using CT scan imaging) and function (using high-resolution manometry [HRM]), and esophageal motor function in patients with sliding and paraesophageal hiatal hernia.

Methods

We assessed normal subjects (n = 20), patients with sliding type 1 hernia (n = 18), paraesophageal type 2 hernia (n = 19), and mixed type 3 hernia (n = 19). Hernia diagnosis was confirmed on the upper gastrointestinal series. The hiatal morphology was constructed from the CT scan images. The LES pressure and relaxation, percent peristalsis, bolus pressure, and hiatal squeeze pressure were assessed by HRM.

Results

The CT images revealed that the esophageal hiatus is formed by the right crus of the diaphragm in all normal subjects and 86% of hernia patients. The hiatus is elliptical in shape with a surface area of 1037 mm² in normal subjects. The hiatal dimensions were larger in patients compared to normal subjects. The HRM revealed impaired LES relaxation and higher bolus pressure in patients with paraesophageal compared to the sliding hernia. The hiatal pinch on HRM was recognized in significantly higher number of patients with sliding as compared to paraesophageal hernia.

Conclusions

Using a novel approach, we provide details of the esophageal hiatus in patients with various kinds of hiatal hernia. Impaired LES relaxation in paraesophageal hernia may play a role in its pathophysiology and genesis of symptoms.

Changes in trauma management following the implementation of the whole-body computed tomography: a retrospective multi-centre study based on the trauma registry of the German Trauma Society (TraumaRegister DGU®)

OBJECTIVES

Whole-body computed tomography (WBCT) plays an increasingly important role in the diagnostic assessment of trauma room patients. It is still unclear whether its use has led to changes of trauma room procedures and patient outcomes.

METHODS

In a retrospective multi-centric study based on the trauma registry of the German Trauma Society (TraumaRegister DGU^®), we analysed patients with an ISS ≥ 9 between 2002 and 2013. Two periods of time, i.e. up to 3 years preceding (pre-WBCT) and up to 3 years following the introduction of the WBCT (WBCT-group), were assessed separately for every hospital (TR-DGU Project ID 2014-020).

RESULTS

19,838 patients underwent treatment in 77 hospitals. Of these, 5621 were assigned to the pre-WBCT group and 11,307 to the WBCT group. Basic data did not differ relevantly. The time spent in the trauma room decreased from 77.9 min (pre-WBCT) to 63.3 min (WBCT). Following the introduction of the trauma scan, the number of diagnoses per patient increased from 4.6 to 5.1. The percentage of patients who underwent surgery immediately after the completion of trauma room procedures decreased from 44.5 to 39.1%. There was an increase in mortality from 15.7 to 15.9%.

CONCLUSIONS

Routine use of WBCT is not superior to a combination of conventional radiography, ultrasound and focused CT in terms of mortality. The entire process involving the introduction of the trauma scan and the further development of algorithms has caused changes that can be observed in the trauma room setting.

Validation of myocardial perfusion quantification by dynamic CT in an ex-vivo porcine heart model

To test the accuracy of quantification of myocardial perfusion imaging (MPI) using computed tomography (CT) in ex-vivo porcine models. Five isolated porcine hearts were perfused according to Langendorff. Hearts were perfused using retrograde flow through the aorta and blood flow, blood pressure and heart rate were monitored throughout the experiment. An inflatable cuff was placed around the circumflex (Cx) artery to create stenosis grades which were monitored using a pressure wire, analysing perfusion at several fractional flow reserve values of 1.0, 0.7, 0.5, 0.3, and total occlusion. Second-generation dual-source CT was used to acquire dynamic MPI in shuttle mode with 350 mAs/rot at 100 kVp. CT MPI was performed using VPCT myocardium software, calculating myocardial blood flow (MBF, ml/100 ml/min) for segments perfused by Cx artery and non-Cx myocardial segments. Microspheres were successfully infused at three stenosis grades in three of the five hearts. Heart rate ranged from 75 to 134 beats per minute. Arterial blood flow ranged from 0.5 to 1.4 l min and blood pressure ranged from 54 to 107 mmHg. MBF was determined in 400 myocardial segments of which 115 were classified as ‘Cx-territory’. MBF was significantly different between non-Cx and Cx segments at stenosis grades with an FFR ≤0.70 (Mann–Whitney U test, p < 0.05). MBF showed a moderate correlation with microsphere MBF for the three individual hearts (Pearson correlation 0.62–0.76, p < 0.01). CT MPI can be used to determine regional differences in myocardial perfusion parameters, based on severity of coronary stenosis. Significant differences in MBF could be measured between non-ischemic and ischemic segments.

Uterine Serous Adenocarcinoma in an Elderly Postmenopausal Woman: Clinically Misdiagnosed as Uterine Cervix Cancer

Uterine serous adenocarcinoma (USC) is rare and invasive cancer. This cancer is more often reported in the ovary, the fallopian tube, and the endometrium than uterine cervix. No matter where the tumor is located, the tumor exhibits similar histological characteristics. So when uterine cancer is proven to be serous adenocarcinoma, it is necessary to see if the tumor originated from ovary or endometrium and invaded the cervix. We report a case of a 73-year-old postmenopausal woman with USC arising near the internal os of endocervical canal, clinically misdiagnosed as uterine cervix cancer.

High patency of proximal splenorenal shunt: A myth or reality ? - A prospective cohort study

BACKGROUND

Proximal splenorenal shunt (PSRS) is a well-accepted surgical procedure for non-cirrhotic portal hypertension (NCPH). Though a patent shunt is important for good long term outcome, there are very few studies on patency of these shunts. We analysed shunt patency using dynamic computed tomographic (CT) portography and compared it with other modalities.

METHODS

From 2004 to 2014, 50 patients with PSRS were evaluated prospectively for shunt patency using dynamic CT portography, clinical parameters and ultrasound Doppler.

RESULTS

The causes of NCPH were extrahepatic portal vein obstruction (EHPVO) in 38 patients and non-cirrhotic portal fibrosis (NCPF) in 12 patients. The shunt patency rate using clinical parameters, ultrasound Doppler and dynamic CT portography were 70%, 40% and 60% respectively. Clinical parameters overestimated while ultrasound Doppler underestimated the shunt patency rate. Dynamic portography had 100% correlation with conventional angiography in the five patients when this was done. The site of shunt could be demonstrated convincingly by dynamic CT portography. The shunt patency rate decreased over time. It was 64%, 60% and 43% in <1 year, 1-5 years and >5 years respectively. Our NCPF patients had a greater shunt patency rate compared to EHPVO patients (9/12 vs. 21/38) though the difference was not significant. Only size of the splenic vein had a significant impact on the shunt patency rate on statistical analysis.

CONCLUSIONS

Dynamic CT portography is useful for evaluation of shunt patency. Proximal splenorenal shunts have a high blockage rate which has hitherto not been reported.

Predicting the image noise level of prospective ECG-triggered coronary computed tomography angiography: quantitative measurement of thoracic component versus body mass index

We evaluated the feasibility of using quantitatively measured thoracic components, as compared to body mass index (BMI), for predicting the image noise of coronary computed tomography angiography (CCTA). One hundred subjects (M:F = 64:36; mean age, 55 ± 8.8 years) who underwent prospective electrocardiography-gated CCTA and low-dose chest computed tomography (CT) were analyzed retrospectively. The image noise of the CCTA was determined by the standard deviation of the attenuation value in a region of interest on the aortic root level. On the low-dose chest CT, the areas of the thoracic components were measured at the aortic root level. An auto-segmentation technique with the following threshold levels was used: quantitatively measured area of total thorax [QMAtotal: -910 to 1000 Hounsfield units (HU)], lung (QMAlung: -910 to -200 HU), fat (QMAfat: -200 to 0 HU), muscle (QMAmuscle: 0-300 HU), soft tissue (fat + muscle, QMAsoft tissue: -200 to 300 HU), bone (QMAbone: 300-1000 HU) and solid tissue (fat + muscle + bone, QMAsolid tissue: -200 to 1000 HU). The relationship between image noise and variable biometric parameters including QMA was analyzed, and the linear correlation coefficients were used as indicators of the strength of association. Among the variable biometric parameters, including BMI, QMAsolid tissue showed the highest correlation coefficient with image noise in all subjects (r = 0.804), males (r = 0.716), females (r = 0.889), the overweight (r = 0.556), and the non-overweight subgroups (r = 0.783). QMAsolid tissue can be used as a potential surrogate predictor of the image noise level in low tube voltage CCTA.