Computed Tomography Radiomics for Preoperative Prediction of Spread Through Air Spaces in the Early Stage of Surgically Resected Lung Adenocarcinomas

PURPOSE

To assess the added value of radiomics models from preoperative chest CT in predicting the presence of spread through air spaces (STAS) in the early stage of surgically resected lung adenocarcinomas using multiple validation datasets.

MATERIALS AND METHODS

This retrospective study included 550 early-stage surgically resected lung adenocarcinomas in 521 patients, classified into training, test, internal validation, and temporal validation sets (n=211, 90, 91, and 158, respectively). Radiomics features were extracted from the segmented tumors on preoperative chest CT, and a radiomics score (Rad-score) was calculated to predict the presence of STAS. Diagnostic performance of the conventional model and the combined model, based on a combination of conventional and radiomics features, for the diagnosis of the presence of STAS were compared using the area under the curve (AUC) of the receiver operating characteristic curve.

RESULTS

Rad-score was significantly higher in the STAS-positive group compared to the STAS-negative group in the training, test, internal, and temporal validation sets. The performance of the combined model was significantly higher than that of the conventional model in the training set {AUC: 0.784 [95% confidence interval (CI): 0.722-0.846] vs. AUC: 0.815 (95% CI: 0.759-0.872), p=0.042}. In the temporal validation set, the combined model showed a significantly higher AUC than that of the conventional model (p=0.001). The combined model showed a higher AUC than the conventional model in the test and internal validation sets, albeit with no statistical significance.

CONCLUSION

A quantitative CT radiomics model can assist in the non-invasive prediction of the presence of STAS in the early stage of lung adenocarcinomas.

Validation of a deep learning-based software for automated analysis of T2 mapping in cardiac magnetic resonance imaging

Background

The reliability and diagnostic performance of deep learning (DL)-based automated T2 measurements on T2 map of 3.0-T cardiac magnetic resonance imaging (MRI) using multi-institutional datasets have not been investigated. We aimed to evaluate the performance of a DL-based software for measuring automated T2 values from 3.0-T cardiac MRI obtained at two centers.

Methods

Eighty-three subjects were retrospectively enrolled from two centers (42 healthy subjects and 41 patients with myocarditis) to validate a commercial DL-based software that was trained to segment the left ventricular myocardium and measure T2 values on T2 mapping sequences. Manual reference T2 values by two experienced radiologists and those calculated by the DL-based software were obtained. The segmentation performance of the DL-based software and the non-inferiority of automated T2 values were assessed compared with the manual reference standard per segment level. The software's performance in detecting elevated T2 values was assessed by calculating the sensitivity, specificity, and accuracy per segment.

Results

The average Dice similarity coefficient for segmentation of myocardium on T2 maps was 0.844. The automated T2 values were non-inferior to the manual reference T2 values on a per-segment analysis (45.35 vs. 44.32 ms). The DL-based software exhibited good performance (sensitivity: 83.6-92.8%; specificity: 82.5-92.0%; accuracy: 82.7-92.2%) in detecting elevated T2 values.

Conclusions

The DL-based software for automated T2 map analysis yields non-inferior measurements at the per-segment level and good performance for detecting myocardial segments with elevated T2 values compared with manual analysis.

Clinical implication of the 2020 International Association for the Study of Lung Cancer histologic grading in surgically resected pathologic stage 1 lung adenocarcinomas: Prognostic value and association with computed tomography characteristics

OBJECTIVES

To investigate the incremental prognostic value of the 2020 International Association for the Study of Lung Cancer (IASLC) histologic grading system over traditional prognosticators in surgically resected pathologic stage 1 lung adenocarcinomas and to identify the clinical and radiologic characteristics of lung adenocarcinomas reclassified by the 2020 histologic grading system.

MATERIALS AND METHODS

We retrospectively enrolled 356 patients who underwent surgery for pathologic stage 1 adenocarcinoma between January 2016 and December 2017. The histologic grading was classified according to the predominant histologic subtype (conventional system) and the updated 2020 IASLC grading system. The clinical and computed tomography (CT) characteristics were compared according to the reclassification of the updated system. The performance of prognostic models for recurrence-free survival based on the combination of pathologic tumor size, histologic grade, and CT-based information was compared using the c-index.

RESULTS

Postoperative recurrence occurred in 6.7% of patients during the follow-up period (mean, 1589.2 ± 406.7 days). Fifty-nine of 244 (24.2%) tumors with intermediate grades in the conventional system were reclassified as grade 3 with the updated grading system. They showed significantly larger solid proportions and higher percentages of pure solid nodules on CT compared to tumors without reclassification (n = 185) (P < 0.05). Prognostic prediction models based on pathology tumor size and histologic grades had significantly higher c-indices (0.754-0.803) compared to the model based on pathologic tumor size only (c-index:0.723, P < 0.05).

CONCLUSION

The 2020 IASLC histologic grading system has significant incremental prognostic value over the pathologic stage in surgically resected pathologic stage 1 lung adenocarcinoma. Reclassified lung adenocarcinomas using the updated grading system have a larger solid proportion and a higher percentage of pure solid nodules on CT.

Importance of Local Ablative Therapies for Lung Metastases in Patients With Colorectal Cancer

OBJECTIVE

To assess the effect of local ablative therapy (LAT) on overall survival in patients with lung metastases from colorectal cancer (CRC) compared with patients treated with systemic therapy.

SUMMARY BACKGROUND DATA

CRC affects approximately 1.4 million individuals worldwide every year. The lungs are commonly affected by CRC, and there is no treatment standard for a secondary lung metastasis from CRC.

METHODS

This longitudinal, retrospective cohort study (2010-2018) quantified the pulmonary and extrapulmonary tumor burden of 1143 patients by retrospectively reviewing computed tomography images captured at diagnosis. A comprehensive multidisciplinary approach informed how and when surgery and/or stereotactic body radiotherapy was administered.

RESULTS

Among 1143 patients, 473 patients (41%) received LAT, with surgery first (n = 421) or stereotactic ablative radiation therapy first (n = 52) either at the time of diagnosis (n = 288), within 1 year (n = 132), or after 1 year (n = 53). LAT was repeated in 158 patients (33.4%, 384 total sessions) when new lung metastases were detected. The 5- and 10-year survival rates for patients treated with LAT (71.2% and 64.0%, respectively) were significantly higher than those of patients treated with systemic therapy alone (14.2% and 10.0%, respectively; P <0.001). The overall survival of patients who received LAT intervention increased as the total tumor burden decreased.

CONCLUSIONS

A high long-term survival rate was achievable in a significant portion of patients with lung metastasis from CRC by the timely administrations of LAT to standard systemic therapy. The tumor burden and LAT feasibility should be included in a discussion during the follow-up period.

Stability selection for LASSO with weights based on AUC

Stability selection is a variable selection algorithm based on resampling a dataset. Based on stability selection, we propose weighted stability selection to select variables by weighing them using the area under the receiver operating characteristic curve (AUC) from additional modelling. Through an extensive simulation study, we evaluated the performance of the proposed method in terms of the true positive rate (TPR), positive predictive value (PPV), and stability of variable selection. We also assessed the predictive ability of the method using a validation set. The proposed method performed similarly to stability selection in terms of the TPR, PPV, and stability. The AUC of the model fitted on the validation set with the selected variables of the proposed method was consistently higher in specific scenarios. Moreover, when applied to radiomics and speech signal datasets, the proposed method had a higher AUC with fewer variables selected. A major advantage of the proposed method is that it enables researchers to select variables intuitively using relatively simple parameter settings.

Fully automatic coronary calcium scoring in non-ECG-gated low-dose chest CT: comparison with ECG-gated cardiac CT

OBJECTIVES

To validate an artificial intelligence (AI)-based fully automatic coronary artery calcium (CAC) scoring system on non-electrocardiogram (ECG)-gated low-dose chest computed tomography (LDCT) using multi-institutional datasets with manual CAC scoring as the reference standard.

METHODS

This retrospective study included 452 subjects from three academic institutions, who underwent both ECG-gated calcium scoring computed tomography (CSCT) and LDCT scans. For all CSCT and LDCT scans, automatic CAC scoring (CAC_auto) was performed using AI-based software, and manual CAC scoring (CAC_man) was set as the reference standard. The reliability and agreement of CAC_auto was evaluated and compared with that of CAC_man using intraclass correlation coefficients (ICCs) and Bland-Altman plots. The reliability between CAC_auto and CAC_man for CAC severity categories was analyzed using weighted kappa (κ) statistics.

RESULTS

CAC_auto on CSCT and LDCT yielded a high ICC (0.998, 95% confidence interval (CI) 0.998-0.999 and 0.989, 95% CI 0.987-0.991, respectively) and a mean difference with 95% limits of agreement of 1.3 ± 37.1 and 0.8 ± 75.7, respectively. CAC_auto achieved excellent reliability for CAC severity (κ = 0.918-0.972) on CSCT and good to excellent but heterogenous reliability among datasets (κ = 0.748-0.924) on LDCT.

CONCLUSIONS

The application of an AI-based automatic CAC scoring software to LDCT shows good to excellent reliability in CAC score and CAC severity categorization in multi-institutional datasets; however, the reliability varies among institutions.

KEY POINTS

• AI-based automatic CAC scoring on LDCT shows excellent reliability with manual CAC scoring in multi-institutional datasets. • The reliability for CAC score-based severity categorization varies among datasets. • Automatic scoring for LDCT shows a higher false-positive rate than automatic scoring for CSCT, and most common causes of a false-positive are image noise and artifacts for both CSCT and LDCT.

A Modified Length-Based Grading Method for Assessing Coronary Artery Calcium Severity on Non-Electrocardiogram-Gated Chest Computed Tomography: A Multiple-Observer Study

OBJECTIVE

To validate a simplified ordinal scoring method, referred to as modified length-based grading, for assessing coronary artery calcium (CAC) severity on non-electrocardiogram (ECG)-gated chest computed tomography (CT).

MATERIALS AND METHODS

This retrospective study enrolled 120 patients (mean age ± standard deviation [SD], 63.1 ± 14.5 years; male, 64) who underwent both non-ECG-gated chest CT and ECG-gated cardiac CT between January 2011 and December 2021. Six radiologists independently assessed CAC severity on chest CT using two scoring methods (visual assessment and modified length-based grading) and categorized the results as none, mild, moderate, or severe. The CAC category on cardiac CT assessed using the Agatston score was used as the reference standard. Agreement among the six observers for CAC category classification was assessed using Fleiss kappa statistics. Agreement between CAC categories on chest CT obtained using either method and the Agatston score categories on cardiac CT was assessed using Cohen's kappa. The time taken to evaluate CAC grading was compared between the observers and two grading methods.

RESULTS

For differentiation of the four CAC categories, interobserver agreement was moderate for visual assessment (Fleiss kappa, 0.553 [95% confidence interval {CI}: 0.496-0.610]) and good for modified length-based grading (Fleiss kappa, 0.695 [95% CI: 0.636-0.754]). The modified length-based grading demonstrated better agreement with the reference standard categorization with cardiac CT than visual assessment (Cohen's kappa, 0.565 [95% CI: 0.511-0.619 for visual assessment vs. 0.695 [95% CI: 0.638-0.752] for modified length-based grading). The overall time for evaluating CAC grading was slightly shorter in visual assessment (mean ± SD, 41.8 ± 38.9 s) than in modified length-based grading (43.5 ± 33.2 s) (P < 0.001).

CONCLUSION

The modified length-based grading worked well for evaluating CAC on non-ECG-gated chest CT with better interobserver agreement and agreement with cardiac CT than visual assessment.

Assessment of aortic valve area on cardiac computed tomography in symptomatic bicuspid aortic stenosis: Utility and differences from Doppler echocardiography

Background

In this study, we investigate the utility of geometric orifice area (GOA) on cardiac computed tomography (CT) and differences from effective orifice area (EOA) on Doppler echocardiography in patients with bicuspid aortic stenosis (AS).

Methods

A total of 163 patients (age 64 ± 10 years, 56.4% men) with symptomatic bicuspid AS who were referred for surgery and underwent both cardiac CT and echocardiography within 3 months were studied. To calculate the aortic valve area, GOA_CT was measured by multiplanar CT planimetry, and EOA_Echo was calculated by the continuity equation with Doppler echocardiography. The relationships between GOA_CT and EOA_Echo and patient symptom scale, biomarkers, and left ventricular (LV) functional variables were analyzed.

Results

There was a significant but modest correlation between EOA_Echo and GOA_CT (r = 0.604, p < 0.001). Both EOA_Echo and GOA_CT revealed significant correlations with mean pressure gradient and peak transaortic velocity, and the coefficients were higher in EOA_Echo than in GOA_CT. EOA_Echo of 1.05 cm² and GOA_CT of 1.25 cm² corresponds to hemodynamic cutoff values for diagnosing severe AS. EOA_Echo was well correlated with the patient symptom scale and log NT-pro BNP, but GOA_CT was not. In addition, EOA_Echo had a higher correlation coefficient with estimated LV filling pressure and LV global longitudinal strain than GOA_CT.

Conclusion

GOA_CT can be used to evaluate the severity of bicuspid AS. The threshold for GOA_CT for diagnosing severe AS should be higher than that for EOA_Echo. However, EOA_Echo is still the method of choice because EOA_Echo showed better correlations with clinical and functional variables than GOA_CT.

Automated Measurement of Native T1 and Extracellular Volume Fraction in Cardiac Magnetic Resonance Imaging Using a Commercially Available Deep Learning Algorithm

OBJECTIVE

T1 mapping provides valuable information regarding cardiomyopathies. Manual drawing is time consuming and prone to subjective errors. Therefore, this study aimed to test a DL algorithm for the automated measurement of native T1 and extracellular volume (ECV) fractions in cardiac magnetic resonance (CMR) imaging with a temporally separated dataset.

MATERIALS AND METHODS

CMR images obtained for 95 participants (mean age ± standard deviation, 54.5 ± 15.2 years), including 36 left ventricular hypertrophy (12 hypertrophic cardiomyopathy, 12 Fabry disease, and 12 amyloidosis), 32 dilated cardiomyopathy, and 27 healthy volunteers, were included. A commercial deep learning (DL) algorithm based on 2D U-net (Myomics-T1 software, version 1.0.0) was used for the automated analysis of T1 maps. Four radiologists, as study readers, performed manual analysis. The reference standard was the consensus result of the manual analysis by two additional expert readers. The segmentation performance of the DL algorithm and the correlation and agreement between the automated measurement and the reference standard were assessed. Interobserver agreement among the four radiologists was analyzed.

RESULTS

DL successfully segmented the myocardium in 99.3% of slices in the native T1 map and 89.8% of slices in the post-T1 map with Dice similarity coefficients of 0.86 ± 0.05 and 0.74 ± 0.17, respectively. Native T1 and ECV showed strong correlation and agreement between DL and the reference: for T1, r = 0.967 (95% confidence interval [CI], 0.951-0.978) and bias of 9.5 msec (95% limits of agreement [LOA], -23.6-42.6 msec); for ECV, r = 0.987 (95% CI, 0.980-0.991) and bias of 0.7% (95% LOA, -2.8%-4.2%) on per-subject basis. Agreements between DL and each of the four radiologists were excellent (intraclass correlation coefficient [ICC] of 0.98-0.99 for both native T1 and ECV), comparable to the pairwise agreement between the radiologists (ICC of 0.97-1.00 and 0.99-1.00 for native T1 and ECV, respectively).

CONCLUSION

The DL algorithm allowed automated T1 and ECV measurements comparable to those of radiologists.

Assessment of aortic valve area on cardiac computed tomography and doppler echocardiography: differences and clinical significance in symptomatic bicuspid aortic stenosis

Backgrounds

This study aimed to investigate the differences and clinical significance of effective orifice area (EOA) on Doppler echocardiography and geometric orifice area (GOA) on cardiac computed tomography (CT) in bicuspid aortic stenosis (AS).

Methods

One-hundred sixty-three consecutive patients (age 64±10 years, 56.4% men) with symptomatic bicuspid AS who were referred for surgery and underwent both cardiac CT and echocardiography within 3 months were studied. For the aortic valve area, GOACT was measured by multiplanar CT planimetry, and EOAEcho was calculated by continuity equation with Doppler echocardiography. The associations of GOACT and EOAEcho with the patients' symptom scale, biomarkers, and left ventricular (LV) functional variables were comprehensively analyzed.

Results

There was a significant but modest correlation between EOAEcho and GOACT (r=0.604, p&lt;0.001). Both EOAEcho and GOACT revealed significant correlations with mean pressure gradient and peak transaortic velocity and the coefficients were higher in EOAEcho than GOACT. EOAEcho of 1.05 cm2 and GOACT of 1.25 cm2 correspond to the hemodynamic cut-off values for diagnosing severe AS. EOAEcho was well correlated with patients' symptom scale and log NT-pro BNP, but GOACT was not. In addition, EOAEcho showed higher correlation coefficient with estimated LV filling pressure and LV global longitudinal strain than GOACT.

Conclusions

Both EOAEcho and GOACT can be used to evaluate the severity of bicuspid AS, however, the threshold for GOACT for diagnosing severe AS should be applied higher than that for EOAEcho. EOAEcho tends to be more correlated with the patients' symptom degree, biomarkers, and LV functional variables than GOACT.

Funding Acknowledgement

Type of funding sources: Public Institution(s). Main funding source(s): The Korean Cardiac Research Foundation

Deep learning-based reconstruction on cardiac CT yields distinct radiomic features compared to iterative and filtered back projection reconstructions

We aimed to determine the effects of deep learning-based reconstruction (DLR) on radiomic features obtained from cardiac computed tomography (CT) by comparing with iterative reconstruction (IR), and filtered back projection (FBP). A total of 284 consecutive patients with 285 cardiac CT scans that were reconstructed with DLR, IR, and FBP, were retrospectively enrolled. Radiomic features were extracted from the left ventricular (LV) myocardium, and from the periprosthetic mass if patients had cardiac valve replacement. Radiomic features of LV myocardium from each reconstruction were compared using a fitting linear mixed model. Radiomics models were developed to diagnose periprosthetic abnormality, and the performance was evaluated using the area under the receiver characteristics curve (AUC). Most radiomic features of LV myocardium (73 of 88) were significantly different in pairwise comparisons between all three reconstruction methods (P < 0.05). The radiomics model on IR exhibited the best diagnostic performance (AUC 0.948, 95% CI 0.880-1), relative to DLR (AUC 0.873, 95% CI 0.735-1) and FBP (AUC 0.875, 95% CI 0.731-1), but these differences did not reach significance (P > 0.05). In conclusion, applying DLR to cardiac CT scans yields radiomic features distinct from those obtained with IR and FBP, implying that feature robustness is not guaranteed when applying DLR.

Automated Computer-aided Detection of Lung Nodules in Metastatic Colorectal Cancer Patients for the Identification of Pulmonary Oligometastatic Disease

PURPOSE

This study aims to explore the possibility and clinical utility of existing artificial intelligence (AI)-based computer-aided detection (CAD) of lung nodules to identify pulmonary oligometastases.

PATIENTS AND METHODS

The chest computed tomography (CT) scans of patients with lung metastasis from colorectal cancer between March 2006 and November 2018 were analyzed. The patients were selected from a database of 1,395 patients and studied in two cohorts. The first cohort included 50 patients and the CT scans of these patients were independently evaluated for lung nodule (≥3 mm) detection by a CAD-assisted radiation oncologist (CAD-RO) as well as an expert radiologist. Inter-observer variability in additional two radiation oncologists and two thoracic surgeons was also measured. In the second cohort of 305 patients, survival outcomes were evaluated based on the number of CAD-RO-detected nodules.

RESULTS

In the first cohort, the sensitivity and specificity of the CAD-RO for the identification of oligometastatic disease (OMD) from varying criteria by ≤2 nodules, ≤3 nodules, ≤4 nodules, and ≤5 nodules were 71.9% and 88.9%; 82.9% and 93.3%; 97.1% and 73.3%; and 97.5% and 90.0%, respectively. The sensitivity of the CAD-RO in the nodule detection compared with the radiologist was 81.6%. The average (standard deviation) sensitivity in inter-observer variability analysis was 80.0% (3.7%). In the second cohort, the 5-year survival rates of patients with 1, 2, 3, 4, or ≥5 metastatic nodules were 75.2%, 52.9%, 45.7%, 29.1%, and 22.7%, respectively.

CONCLUSIONS

Proper identification of the pulmonary OMD and the correlation between the number of CAD-RO-detected nodules and survival suggest the potential practicality of AI in OMD recognition. Developing a deep learning-based model specific to the metastatic setting, which enables a quick estimation of disease burden and identification of OMD, is underway.

Progostic value of coronary artery calcium scores from 1.5 mm slice reconstructions of electrocardiogram-gated computed tomography scans in asymptomatic individuals

It is unknown whether the thinner slice reconstruction has added value relative to 3 mm reconstructions in predicting major adverse cardiac events (MACEs). This retrospective study included 550 asymptomatic individuals who underwent cardiac CT. Coronary artery calcium (CAC) scores and severity categories were assessed from 1.5 and 3 mm scans. CAC scores obtained from 1.5 and 3 mm scans were compared using Wilcoxon signed-rank tests. Cox proportional hazard models were developed to predict MACEs based on the degree of coronary artery stenosis on coronary CT angiography and the presence of CAC on both scans. Model performances were compared using the time-dependent ROC curve and integrated area under the curve (iAUC) methods. The CAC scores obtained from 1.5 mm scans were significantly higher than those from 3 mm scans (median, interquartile range 4.5[0–71] vs. 0[0–48.4]; p < 0.001). Models showed no difference in predictive accuracy of the presence of CAC between 1.5 and 3 mm scans (iAUC, 0.625 vs. 0.672). In conclusion, CAC scores obtained from 1.5 mm scans are significantly higher than those from 3 mm scans, but do not provide added prognostic value relative to 3 mm scans.

Quality assessment of radiomics research in cardiac CT: a systematic review

OBJECTIVES

To assess the quality of current radiomics research on cardiac CT using radiomics quality score (RQS) and Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) systems.

METHODS

Systematic searches of PubMed and EMBASE were performed to identify all potentially relevant original research articles about cardiac CT radiomics. Fifteen original research articles were selected. Two cardiac radiologists assessed the quality of the methodology adopted in those studies according to the RQS and TRIPOD guidelines. Basic adherence rates for the following six key domains were evaluated: image protocol and reproducibility, feature reduction and validation, biologic/clinical utility, performance index, high level of evidence, and open science.

RESULTS

Among the 15 included articles, six (40%) were about coronary artery disease and six (40%) were about myocardial infarction. The mean RQS was 9.9 ± 7.3 (27.4% of the ideal score of 36), and the basic adherence rate was 44.6%. Fourteen (93.3%) and nine (60%) studies performed feature selection and validation, but only two (13.3%) of them performed external validation. Two studies (13.3%) were prospective, and only one study (6.7%) conducted calibration analysis and stated the potential clinical utility. None of the studies conducted phantom study and cost-effective analysis. The overall adherence rate for TRIPOD was 63%.

CONCLUSION

The quality of radiomics studies in cardiac CT is currently insufficient. A higher level of evidence is required, and analysis of clinical utility and calibration of model performance need to be improved.

KEY POINTS

• The quality of science of radiomics studies in cardiac CT is currently insufficient. • No study conducted a phantom study or cost-effective analysis, with further limitations being demonstrated in a high level of evidence for radiomics studies. • Analysis of clinical utility and calibration of model performance need to be improved, and a higher level of evidence is required.

Synthetic contrast-enhanced computed tomography generation using a deep convolutional neural network for cardiac substructure delineation in breast cancer radiation therapy: a feasibility study

BACKGROUND

Adjuvant radiation therapy improves the overall survival and loco-regional control in patients with breast cancer. However, radiation-induced heart disease, which occurs after treatment from incidental radiation exposure to the cardiac organ, is an emerging challenge. This study aimed to generate synthetic contrast-enhanced computed tomography (SCECT) from non-contrast CT (NCT) using deep learning (DL) and investigate its role in contouring cardiac substructures. We also aimed to determine its applicability for a retrospective study on the substructure volume-dose relationship for predicting radiation-induced heart disease.

METHODS

We prepared NCT-CECT cardiac scan pairs of 59 patients. Of these, 35, 4, and 20 pairs were used for training, validation, and testing, respectively. We adopted conditional generative adversarial network as a framework to generate SCECT. SCECT was validated in the following three stages: (1) The similarity between SCECT and CECT was evaluated; (2) Manual contouring was performed on SCECT and CECT with sufficient intervals and based on this, the geometric similarity of cardiac substructures was measured between them; (3) The treatment plan was quantitatively analyzed based on the contours of SCECT and CECT.

RESULTS

While the mean values (± standard deviation) of the mean absolute error, peak signal-to-noise ratio, and structural similarity index measure between SCECT and CECT were 20.66 ± 5.29, 21.57 ± 1.85, and 0.77 ± 0.06, those were 23.95 ± 6.98, 20.67 ± 2.34, and 0.76 ± 0.07 between NCT and CECT, respectively. The Dice similarity coefficients and mean surface distance between the contours of SCECT and CECT were 0.81 ± 0.06 and 2.44 ± 0.72, respectively. The dosimetry analysis displayed error rates of 0.13 ± 0.27 Gy and 0.71 ± 1.34% for the mean heart dose and V5Gy, respectively.

CONCLUSION

Our findings displayed the feasibility of SCECT generation from NCT and its potential for cardiac substructure delineation in patients who underwent breast radiation therapy.

The image quality and diagnostic accuracy of T1-mapping-based synthetic late gadolinium enhancement imaging: comparison with conventional late gadolinium enhancement imaging in real-life clinical situation

BACKGROUNDS

Synthetic late gadolinium enhancement (LGE) images are less sensitive to inversion time (TI) and robust to motion artifact, because it is generated retrospectively by post-contrast T1-mapping images. To explore the clinical applicability of synthetic LGE, we investigated the image quality and diagnostic accuracy of synthetic LGE images, in comparison to that of conventional LGE for various disease groups.

METHOD AND MATERIALS

From July to November 2019, a total of 98 patients who underwent cardiovascular magnetic resonance imaging (CMR), including LGE and T1-mapping sequences, with suspicion of myocardial abnormality were retrospectively included. Synthetic magnitude inversion-recovery (IR) and phase-sensitive IR (PSIR) images were generated through calculations based on the post-contrast T1-mapping sequence. Three cardiothoracic radiologists independently analyzed the image quality of conventional and synthetic LGE images on an ordinal scale with per-segment basis and the image qualities were compared with chi-square test. The agreement of LGE detection was analyzed on per-patient and per-segment basis with Cohen's kappa test. In addition, the LGE area and percentage were semi-quantitatively analyzed for LGE positive ischemic (n = 14) and hypertrophic cardiomyopathy (n = 13) subgroups by two cardiothoracic radiologists. The difference of quantified LGE area and percentage between conventional and synthetic LGE images were assessed with Mann-Whitney U-test and the inter-reader agreement was assessed with Bland-Altman analysis.

RESULTS

The image quality of synthetic images was significantly better than conventional images in both magnitude IR and PSIR through all three observers (P < 0.001, all). The agreements of per-patient and per-segment LGE detection rates were excellent (kappa = 0.815-0.864). The semi-quantitative analysis showed no significant difference in the LGE area and percentage between conventional and synthetic LGE images. In the inter-reader agreement showed only small systematic differences in both magnitude IR and PSIR and synthetic LGE images showed smaller systematic biases compared to conventional LGE images.

CONCLUSION

Compared to conventional LGE images, synthetic LGE images have better image quality in real-life clinical situation.

Quality of science and reporting for radiomics in cardiac magnetic resonance imaging studies: a systematic review

OBJECTIVES

To evaluate the quality of radiomics studies using cardiac magnetic resonance imaging (CMR) according to the radiomics quality score (RQS), Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines, and the standards defined by the Image Biomarker Standardization Initiative (IBSI) and identify areas needing improvement.

MATERIALS AND METHODS

PubMed and Embase were searched to identify radiomics studies using CMR until March 10, 2021. Of the 259 identified articles, 32 relevant original research articles were included. Studies were scored according to the RQS, TRIPOD guidelines, and IBSI standards by two cardiac radiologists.

RESULTS

The mean RQS was 14.3% of the maximum (5.16 out of 36). RQS were low for the demonstration of validation (-60.6%), calibration statistics (1.6%), potential clinical utility (3.1%), and open science (3.1%) items. No study conducted a phantom study or cost-effectiveness analysis. The adherence to TRIPOD guidelines was 55.9%. Studies were deficient in reporting title (3.1%), stating objective in abstract and introduction (6.3% and 9.4%), missing data (0%), discrimination/calibration (3.1%), and how to use the prediction model (3.1%). According to the IBSI standards, non-uniformity correction, image interpolation, grey-level discretization, and signal intensity normalization were performed in two (6.3%), four (12.5%), six (18.8%), and twelve (37.5%) studies, respectively.

CONCLUSION

The quality of radiomics studies using CMR is suboptimal. Improvements are needed in the areas of validation, calibration, clinical utility, and open science. Complete reporting of study objectives, missing data, discrimination/calibration, how to use the prediction model, and preprocessing steps are necessary.

KEY POINTS

• The quality of science in radiomics studies using CMR is currently inadequate. • RQS were low for validation, calibration, clinical utility, and open science; no study conducted a phantom study or cost-effectiveness analysis. • In stating the study objective, missing data, discrimination/calibration, how to use the prediction model, and preprocessing steps, improvements are needed.

Usefulness of cardiac magnetic resonance images for prediction of sudden cardiac arrest in patients with mitral valve prolapse: a multicenter retrospective cohort study

Background

An association has been identified between mitral valve prolapse (MVP) and sudden cardiac arrest (SCA), and ventricular arrhythmias (VA). This study aimed to elucidate predictive factors for SCA or VA in MVP patients.

Methods

MVP patients who underwent cardiac magnetic resonance (CMR) were retrospectively included. Patients with other structural heart disease or causes of aborted SCA were excluded. Clinical characteristics (sex, age, body mass index, histories of diabetes, hypertension, and dyslipidemia) and electrocardiographic (PR interval, QRS duration, corrected QT interval, inverted T wave in the inferior leads, bundle branch block, and atrial fibrillation), echocardiographic [mitral regurgitation grade, prolapsing mitral leaflet, and right ventricular systolic pressure (RVSP)], and CMR [left atrial volume index, both ventricular ejection fractions, both ventricular end-diastolic and systolic volume indexes, prolapse distance, mitral annular disjunction, systolic curling motion, presence of late gadolinium enhancement (LGE), LGE volume and proportion] parameters were analyzed.

Results

Of the 85 patients [age, 54.0 (41.0–65.0) years; 46 men], seven experienced SCA or VA. Younger age and wide QRS complex were observed more often in the SCA/VA group than in the no-SCA/VA group. The SCA/VA group exhibited lower RVSP, more systolic curling motion and LGE, greater LGE volume, and higher LGE proportion. The presence of LGE [hazard ratio (HR), 19.8; 95% confidence interval (CI) 2.65–148.15; P = 0.004], LGE volume (HR 1.08; 95% CI 1.02–1.14; P = 0.006) and LGE proportion (HR 1.32; 95% CI 1.08–1.60; P = 0.006) were independently associated with higher risk of SCA or VA in MVP patients together with systolic curling motion in each model.

Conclusions

The presence of systolic curling motion, high LGE volume and proportion, and the presence of LGE on CMR were independent predictive factors for SCA or VA in MVP patients.

Prevalence of abnormal cardiovascular magnetic resonance findings in recovered patients from COVID-19: a systematic review and meta-analysis

BACKGROUND

The prevalence of abnormal cardiovascular magnetic resonance (CMR) findings in recovered coronavirus disease 2019 (COVID-19) patients is unclear. This study aimed to investigate the prevalence of abnormal CMR findings in recovered COVID-19 patients.

METHODS

A systematic literature search was performed to identify studies that report the prevalence of abnormal CMR findings in recovered COVID-19 patients. The number of patients with abnormal CMR findings and diagnosis of myocarditis on CMR (based on the Lake Louise criteria) and each abnormal CMR parameter were extracted. Subgroup analyses were performed according to patient characteristics (athletes vs. non-athletes and normal vs. undetermined cardiac enzyme levels). The pooled prevalence and 95% confidence interval (CI) of each CMR finding were calculated. Study heterogeneity was assessed, and meta-regression analysis was performed to investigate factors associated with heterogeneity.

RESULTS

In total, 890 patients from 16 studies were included in the analysis. The pooled prevalence of one or more abnormal CMR findings in recovered COVID-19 patients was 46.4% (95% CI 43.2%-49.7%). The pooled prevalence of myocarditis and late gadolinium enhancement (LGE) was 14.0% (95% CI 11.6%-16.8%) and 20.5% (95% CI 17.7%-23.6%), respectively. Further, heterogeneity was observed (I2 > 50%, p < 0.1). In the subgroup analysis, the pooled prevalence of abnormal CMR findings and myocarditis was higher in non-athletes than in athletes (62.5% vs. 17.1% and 23.9% vs. 2.5%, respectively). Similarly, the pooled prevalence of abnormal CMR findings and LGE was higher in the undetermined than in the normal cardiac enzyme level subgroup (59.4% vs. 35.9% and 45.5% vs. 8.3%, respectively). Being an athlete was a significant independent factor related to heterogeneity in multivariate meta-regression analysis (p < 0.05).

CONCLUSIONS

Nearly half of recovered COVID-19 patients exhibited one or more abnormal CMR findings. Athletes and patients with normal cardiac enzyme levels showed a lower prevalence of abnormal CMR findings than non-athletes and patients with undetermined cardiac enzyme levels. Trial registration The study protocol was registered in the PROSPERO database (registration number: CRD42020225234).

Serial T1 mapping of right ventricle in pulmonary hypertension: comparison with histology in an animal study

BACKGROUND

Right ventricular (RV) free wall fibrosis is an important component of adverse remodeling with RV dysfunction in pulmonary hypertension (PH). However, no previous reports have compared cardiovascular magnetic resonance (CMR) findings and histological analysis for RV free wall fibrosis in PH. We aimed to assess the feasibility of CMR T1 mapping with extracellular volume fraction (ECV) for evaluating the progression of RV free wall fibrosis in PH, and compared imaging findings to histological collagen density through an animal study.

METHODS

Among 42 6-week-old Wistar male rats, 30 were classified according to disease duration (baseline before monocrotaline injection, and 2, 4, 6 and 8 weeks after injection) and 12 were used to control for aging (4 and 8 weeks after the baseline). We obtained pre and post-contrast T1 maps for native T1 and ECV of RV and left ventricular (LV) free wall for six animals in each disease-duration group. Collagen density of RV free wall was calculated with Masson's trichrome staining. The Kruskall-Wallis test was performed to compare the groups. Native T1 and ECV to collagen density were analyzed with Spearman's correlation.

RESULTS

The mean values of native T1, ECV and collagen density of the RV free wall at baseline were 1541 ± 33 ms, 17.2 ± 1.3%, and 4.7 ± 0.5%, respectively. The values of RV free wall did not differ according to aging (P = 0.244, 0.504 and 0.331, respectively). However, the values significantly increased according to disease duration (P < 0.001 for all). Significant correlations were observed between native T1 and collagen density (r = 0.770, P < 0.001), and between ECV and collagen density for the RV free wall (r = 0.815, P < 0.001) in PH. However, there was no significant difference in native T1 and ECV values for the LV free wall according to the disease duration from the baseline (P = 0.349 and 0.240, respectively).

CONCLUSIONS

We observed significantly increased values for native T1 and ECV of the RV free wall without significant increase of the LV free wall according to the disease duration of PH, and findings were well correlated with histological collagen density.

Comparison of artery-based methods for ordinal grading of coronary artery calcium on low-dose chest computed tomography

OBJECTIVES

To identify the optimal artery-based method for ordinal grading of coronary artery calcium (CAC) on non-electrocardiogram (ECG)-gated low-dose chest computed tomography (LDCT) among three methods.

METHODS

A total of 120 asymptomatic subjects who underwent both LDCT and ECG-gated calcium scoring CT on the same day were retrospectively enrolled. Three cardiothoracic radiologists independently assessed CAC severity on LDCT (1.25-mm and 2.5-mm slice thickness) and classified it into four categories (none, mild, moderate, or severe) using three artery-based ordinal scoring methods (extent-based scoring, Weston scoring, and length-based scoring). Inter- and intra-observer CAC severity agreements of each method were assessed by Fleiss kappa statistics. Agreements between each method and ECG-gated calcium scoring CT were assessed by weighted kappa statistics.

RESULTS

The inter-observer agreement was highest with length-based method for both 1.25-mm (Fleiss kappa 0.735 for extent-based method, 0.801 for Weston score, and 0.813 for length-based method) and 2.5-mm slice thickness evaluation (Fleiss kappa 0.755 for extent-based method, 0.776 for Weston score, and 0.833 for extent-based method). Agreement across the three grading methods for the same observer was poor to moderate on 1.25-mm (Fleiss kappa 0.379-0.441) and moderate on 2.5-mm thickness evaluation (Fleiss kappa 0.427-0.461). Agreement of CAC severity between each method and ECG-gated calcium scoring CT was highest with the length-based method for all three observers on both 1.25-mm (weighted kappa 0.773-0.786) and 2.5-mm (weighted kappa 0.794-0.825) LDCT images.

CONCLUSION

Among the three artery-based ordinal grading methods, the length-based method appears to be the most reliable for evaluating CAC on non-ECG-gated LDCT.

KEY POINTS

• The length-based method showed the highest inter-observer agreement and the highest agreement with the ECG-gated calcium scoring CT, compared with the extent-based method and the Weston score.

Reliability of Coronary Artery Calcium Severity Assessment on Non-Electrocardiogram-Gated CT: A Meta-Analysis

OBJECTIVE

The purpose of this meta-analysis was to investigate the pooled agreements of the coronary artery calcium (CAC) severities assessed by electrocardiogram (ECG)-gated and non-ECG-gated CT and evaluate the impact of the scan parameters.

MATERIALS AND METHODS

PubMed, EMBASE, and the Cochrane library were systematically searched. A modified Quality Assessment of Diagnostic Accuracy Studies-2 tool was used to evaluate the quality of the studies. Meta-analytic methods were utilized to determine the pooled weighted bias, limits of agreement (LOA), and the correlation coefficient of the CAC scores or the weighted kappa for the categorization of the CAC severities detected by the two modalities. The heterogeneity among the studies was also assessed. Subgroup analyses were performed based on factors that could affect the measurement of the CAC score and severity: slice thickness, reconstruction kernel, and radiation dose for non-ECG-gated CT.

RESULTS

A total of 4000 patients from 16 studies were included. The pooled bias was 62.60, 95% LOA were -36.19 to 161.40, and the pooled correlation coefficient was 0.94 (95% confidence interval [CI] = 0.89-0.97) for the CAC score. The pooled weighted kappa of the CAC severity was 0.85 (95% CI = 0.79-0.91). Heterogeneity was observed in the studies (I² > 50%, p < 0.1). In the subgroup analysis, the agreement between the CAC categorizations was better when the two CT examinations had reconstructions based on the same slice thickness and kernel.

CONCLUSION

The pooled agreement of the CAC severities assessed by the ECG-gated and non-ECG-gated CT was excellent; however, it was significantly affected by scan parameters, such as slice thickness and the reconstruction kernel.

Pulmonary Embolism and Deep Vein Thrombosis in COVID-19: A Systematic Review and Meta-Analysis

Background The association of pulmonary embolism (PE) with deep vein thrombosis (DVT) in patients with coronavirus disease 2019 (COVID-19) remains unclear, and the diagnostic accuracy of D-dimer tests for PE is unknown. Purpose To conduct meta-analysis of the study-level incidence of PE and DVT and to evaluate the diagnostic accuracy of D-dimer tests for PE from multicenter individual patient data. Materials and Methods A systematic literature search identified studies evaluating the incidence of PE or DVT in patients with COVID-19 from January 1, 2020, to June 15, 2020. These outcomes were pooled using a random-effects model and were further evaluated using metaregression analysis. The diagnostic accuracy of D-dimer tests for PE was estimated on the basis of individual patient data using the summary receiver operating characteristic curve. Results Twenty-seven studies with 3342 patients with COVID-19 were included in the analysis. The pooled incidence rates of PE and DVT were 16.5% (95% CI: 11.6, 22.9; I2 = 0.93) and 14.8% (95% CI: 8.5, 24.5; I2 = 0.94), respectively. PE was more frequently found in patients who were admitted to the intensive care unit (ICU) (24.7% [95% CI: 18.6, 32.1] vs 10.5% [95% CI: 5.1, 20.2] in those not admitted to the ICU) and in studies with universal screening using CT pulmonary angiography. DVT was present in 42.4% of patients with PE. D-dimer tests had an area under the receiver operating characteristic curve of 0.737 for PE, and D-dimer levels of 500 and 1000 μg/L showed high sensitivity (96% and 91%, respectively) but low specificity (10% and 24%, respectively). Conclusion Pulmonary embolism (PE) and deep vein thrombosis (DVT) occurred in 16.5% and 14.8% of patients with coronavirus disease 2019 (COVID-19), respectively, and more than half of patients with PE lacked DVT. The cutoffs of D-dimer levels used to exclude PE in preexisting guidelines seem applicable to patients with COVID-19. © RSNA, 2020 Supplemental material is available for this article. See also the editorial by Woodard in this issue.

Structural and Functional Characteristics of Mitral Paravalvular Leakage Identified by Multimodal Imaging and Their Implication on Clinical Presentation

OBJECTIVE

Clinical presentation of patients with mitral paravalvular leakage (PVL) varies from asymptomatic to heart failure related with hemolytic anemia or pulmonary hypertension. We aimed to investigate the structural and functional characteristics of mitral PVL by multimodal imaging and their association with the severity of hemolysis and hemodynamic significance.

METHODS

A total of 74 patients with mitral PVL who underwent both cardiac computed tomography (CT) and echocardiography from March 2010 to December 2017 was investigated. Location and size of PVL, degree of left atrial (LA) calcification as measured by CT, and hemodynamic variables as measured by echocardiography were comprehensively analyzed. To investigate the degree of hemolysis and pulmonary hypertension, level of lactate dehydrogenase (LDH) and Doppler estimated systolic pulmonary artery pressure (SPAP) were used respectively.

RESULTS

Level of LDH was not related to PVL perimeter and was variable, especially in patients with a small PVL. However, it was positively correlated with mean mitral regurgitation velocity. Additionally, SPAP was significantly correlated with PVL perimeter and LA calcium score. In multivariable analysis, mean mitral regurgitation velocity was significantly correlated with levels of LDH (β = 0.345; p = 0.016), and PVL perimeter and LA calcium score were independently associated with SPAP (β = 0.249; p = 0.036 and β = 0.467; p < 0.001, respectively).

CONCLUSIONS

Characteristics of mitral PVL and adjacent structures are associated with the severity of hemolysis and pulmonary hypertension. Evaluating the structural and functional characteristics of mitral PVL by complementary multimodal imaging would be important for understanding the clinical presentation and deciding optimal treatments for individual patients.

Prognostic Value of Dual-Energy CT-Based Iodine Quantification versus Conventional CT in Acute Pulmonary Embolism: A Propensity-Match Analysis

Objective

The present study aimed to investigate whether quantitative dual-energy computed tomography (DECT) parameters offer an incremental risk stratification benefit over the CT ventricular diameter ratio in patients with acute pulmonary embolism (PE) by using propensity score analysis.

Materials and Methods

This study was conducted on 480 patients with acute PE who underwent CT pulmonary angiography (CTPA) or DECT pulmonary angiography (DE CT-PA). This propensity-matched study population included 240 patients with acute PE each in the CTPA and DECT groups. Altogether, 260 (54.1%) patients were men, and the mean age was 64.9 years (64.9 ± 13.5 years). The primary endpoint was all-cause death within 30 days. The Cox proportional hazards regression model was used to identify associations between CT parameters and outcomes and to identify potential predictors. Concordance (C) statistics were used to compare the prognoses between the two groups.

Results

In both CTPA and DECT groups, right to left ventricle diameter ratio ≥ 1 was associated with an increased risk of all-cause death within 30 days (hazard ratio: 3.707, p < 0.001 and 5.573, p < 0.001, respectively). However, C-statistics showed no statistically significant difference between the CTPA and DECT groups for predicting death within 30 days (C-statistics: 0.759 vs. 0.819, p = 0.117).

Conclusion

Quantitative measurement of lung perfusion defect volume by DECT had no added benefit over CT ventricular diameter ratio for predicting all-cause death within 30 days.

2020 Clinical Practice Guideline for Percutaneous Transthoracic Needle Biopsy of Pulmonary Lesions: A Consensus Statement and Recommendations of the Korean Society of Thoracic Radiology

Percutaneous transthoracic needle biopsy (PTNB) is one of the essential diagnostic procedures for pulmonary lesions. Its role is increasing in the era of CT screening for lung cancer and precision medicine. The Korean Society of Thoracic Radiology developed the first evidence-based clinical guideline for PTNB in Korea by adapting pre-existing guidelines. The guideline provides 39 recommendations for the following four main domains of 12 key questions: the indications for PTNB, pre-procedural evaluation, procedural technique of PTNB and its accuracy, and management of post-biopsy complications. We hope that these recommendations can improve the diagnostic accuracy and safety of PTNB in clinical practice and promote standardization of the procedure nationwide.

Performance of Prediction Models for Diagnosing Severe Aortic Stenosis Based on Aortic Valve Calcium on Cardiac Computed Tomography: Incorporation of Radiomics and Machine Learning

OBJECTIVE

We aimed to develop a prediction model for diagnosing severe aortic stenosis (AS) using computed tomography (CT) radiomics features of aortic valve calcium (AVC) and machine learning (ML) algorithms.

MATERIALS AND METHODS

We retrospectively enrolled 408 patients who underwent cardiac CT between March 2010 and August 2017 and had echocardiographic examinations (240 patients with severe AS on echocardiography [the severe AS group] and 168 patients without severe AS [the non-severe AS group]). Data were divided into a training set (312 patients) and a validation set (96 patients). Using non-contrast-enhanced cardiac CT scans, AVC was segmented, and 128 radiomics features for AVC were extracted. After feature selection was performed with three ML algorithms (least absolute shrinkage and selection operator [LASSO], random forests [RFs], and eXtreme Gradient Boosting [XGBoost]), model classifiers for diagnosing severe AS on echocardiography were developed in combination with three different model classifier methods (logistic regression, RF, and XGBoost). The performance (c-index) of each radiomics prediction model was compared with predictions based on AVC volume and score.

RESULTS

The radiomics scores derived from LASSO were significantly different between the severe AS and non-severe AS groups in the validation set (median, 1.563 vs. 0.197, respectively, p < 0.001). A radiomics prediction model based on feature selection by LASSO + model classifier by XGBoost showed the highest c-index of 0.921 (95% confidence interval [CI], 0.869-0.973) in the validation set. Compared to prediction models based on AVC volume and score (c-indexes of 0.894 [95% CI, 0.815-0.948] and 0.899 [95% CI, 0.820-0.951], respectively), eight and three of the nine radiomics prediction models showed higher discrimination abilities for severe AS. However, the differences were not statistically significant (p > 0.05 for all).

CONCLUSION

Models based on the radiomics features of AVC and ML algorithms may perform well for diagnosing severe AS, but the added value compared to AVC volume and score should be investigated further.

Characteristics of COVID-19 Patients Who Progress to Pneumonia on Follow-Up Chest Radiograph: 236 Patients from a Single Isolated Cohort in Daegu, South Korea

OBJECTIVE

We investigated the prevalence of pneumonia in novel coronavirus disease 2019 (COVID-19) patients using chest radiographs to identify the characteristics of those with initially negative chest radiographs, who were positive for pneumonia on follow-up.

MATERIALS AND METHODS

Retrospective cohort data of 236 COVID-19 patients were reviewed. Chest radiography was performed on admission, with serial radiographs obtained until discharge. The 'positive conversion group' was defined as patients whose initial chest radiographs were negative but were positive for pneumonia during follow-up. Patients with initially positive chest radiographs were defined as the 'initial pneumonia group.' Patients with negative initial and follow-up chest radiographs were defined as the 'non-pneumonia group.' Clinical and laboratory findings were compared between groups, and predictors of positive conversion were investigated.

RESULTS

Among 236 patients, 108 (45.8%) were in the non-pneumonia group, 69 (29.2%) were in the initial pneumonia group, and 59 (25%) were in the positive conversion group. The patients in the 'initial pneumonia group' and 'positive conversion group' were older, had higher C-reactive protein (CRP) and lactate dehydrogenase levels, and lower absolute lymphocyte counts than those in the 'non-pneumonia group' (all p < 0.001). Among patients with negative initial chest radiographs, age ≥ 45 years (odds ratio [OR]: 3.93, 95% confidence interval [CI]: 1.76-8.75, p = 0.001), absolute lymphocyte count < 1500 cells/μL (OR: 2.25, 95% CI: 1.03-4.89, p = 0.041), and CRP > 0.5 mg/dL (OR: 3.91, 95% CI: 1.54-9.91, p = 0.004) were independent predictors for future development of pneumonia.

CONCLUSION

More than a half of COVID-19 patients initially had normal chest radiographs; however, elderly patients (≥ 45 years of age) with abnormal laboratory findings (elevated CRP and low absolute lymphocyte counts) developed pneumonia on follow-up radiographs.

Adverse Initial CT Findings Associated with Poor Prognosis of Coronavirus Disease

BACKGROUND

The predictors of poor prognosis in patients with coronavirus disease 2019 (COVID-19) using computed tomography (CT) have not been investigated in a large cohort. Therefore, the purpose of this study was to investigate the adverse initial CT features to predict poor prognosis in COVID-19.

METHODS

From February to April 2020, 281 COVID-19 patients who underwent CT at the time of admission were included. We divided the patients into the severe and non-severe disease groups. The severe group included patients with severe pneumonia or critical events. Intensive care unit admission or death were the critical events in this study. We compared the clinical and CT findings between the severe and non-severe groups and investigated the prognostic factors and critical events of the severe group using the regression analysis.

RESULTS

Among the 281 patients, 36 (12.8%) patients were in the severe group and 245 (87.2%) patients were in the non-severe group. Critical events occurred in 10 patients (3.6%). In the severe group, patients showed significantly more pneumonia with consolidation, crazy-paving appearance, pleural effusion, and higher CT scores than those in the non-severe group (all, P < 0.05). In the multivariate regression, pleural effusion (odds ratio [OR], 8.96; 95% confidence interval [CI], 1.81-44.42; P = 0.007), CT score > 5 (OR, 3.70; 95% CI, 1.44-9.53; P = 0.007), old age (> 77 years, OR, 9.96; 95% CI, 3.78-26.28; P < 0.001), and elevated C-reactive protein (OR, 4.15; 95% CI, 1.62-10.6; P = 0.003) were significant prognostic factors of severe disease. CT score > 5 (OR, 7.29; 95% CI, 1.37-38.68; P = 0.020), pleural effusion (OR, 5.67; 95% CI, 1.04-30.8; P = 0.045) and old age (OR, 8.6; 95% CI, 1.80-41.0; P = 0.007) were also significant predictors of critical events.

CONCLUSION

Pleural effusion and the extent of pneumonia on initial CT scans are associated with poor prognosis in patients with COVID-19.

Characteristics and Implications of Left Atrial Calcium on Cardiac Computed Tomography in Patients With Earlier Mitral Valve Operation

Left atrial calcium (LAC) is often observed in patients who have undergone mitral valve (MV) surgery, but little is known about its characteristics and clinical implications. Therefore, we sought to investigate the structural and hemodynamic significance of LAC and its association with clinical outcomes. We investigated 327 patients with repaired or prosthetic MV who underwent cardiac CT from 2010 to 2017. The degree of LAC was analyzed and classified into three groups: group 1 (no LAC), group 2 (mild-to-moderate LAC), and group 3 (severe LAC). Clinical and echocardiographic characteristics and clinical outcomes were compared in three groups. LAC was seen in 79 (24.2%) patients. Groups 2 and 3 showed more prevalent atrial fibrillation, a rheumatic etiology, a higher number of previous surgeries, a larger LA volume index, and higher pulmonary artery systolic pressure than group 1. Paravalvular leakage of the MV increased progressively according to severity of LAC (15.4% in group 1, 39.3% in group 2, and 66.7% in group 3, p <0.001). Event-free survival rate for major adverse cardiovascular adverse events (log rank p = 0.033) and all-cause mortality (log rank p <0.001) were significantly different according to LAC group. In Cox regression analyses, presence of severe LAC was an independent predictor of all-cause mortality (hazard ratio: 4.44, 95% confidence interval: 1.71 to 11.58, p = 0.002). LAC on cardiac CT is not uncommon and reflects more advanced LA remodeling and a stiff LA. The presence and severity of LAC are associated with a worse clinical outcome after MV surgery.

Role of Cardiac Computed Tomography for Etiology Evaluation of Newly Diagnosed Heart Failure with Reduced Ejection Fraction

Delayed-enhanced dual-energy computed tomography (DECT) can evaluate the extent and degree of myocardial fibrosis while coronary CT angiography (CCTA) is a widely accepted coronary artery evaluation method. We sought to describe the role of combined cardiac CT for the evaluation of underlying etiology in patients with newly diagnosed heart failure with reduced ejection fraction (HFrEF). Sixty-three consecutive patients (31 men, 63 ± 16 years) with newly diagnosed HFrEF were enrolled in this prospective study. Coronary artery disease and myocardial fibrosis were evaluated on CCTA and DECT, respectively, and the tentative underlying etiologies of heart failure (HF) were determined with combinations of findings from both CTs. Concordance between tentative etiologies from cardiac CT and final etiologies from clinical decisions within a 2-year follow-up was assessed. Eighteen patients were diagnosed with ischemic HF on initial cardiac CT, and the final diagnosis was not changed. Another 45 patients with nonischemic HF included tentative etiologies of dilated cardiomyopathy (n = 32, 71.1%), sarcoidosis or myocarditis (n = 8, 17.8%), amyloidosis (n = 2, 4.4%), noncompaction (n = 2, 4.4%) and arrhythmogenic right ventricular cardiomyopathy (n = 1, 2.2%). Five nonischemic HF patients showed different etiologies between initial cardiac CT and clinical decisions. The concordance between cardiac CT and clinical decisions was 92.1%. A high degree of concordance was achieved between tentative etiologies from cardiac CT and final diagnoses from clinical decisions. Combined cardiac CT is a feasible, safe and effective imaging tool for the initial evaluation of newly diagnosed HFrEF patients.

Diagnostic Accuracy of Percutaneous Transthoracic Needle Lung Biopsies: A Multicenter Study

Objective

To measure the diagnostic accuracy of percutaneous transthoracic needle lung biopsies (PTNBs) on the basis of the intention-to-diagnose principle and identify risk factors for diagnostic failure of PTNBs in a multi-institutional setting.

Materials and Methods

A total of 9384 initial PTNBs performed in 9239 patients (mean patient age, 65 years [range, 20–99 years]) from January 2010 to December 2014 were included. The accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of PTNBs for diagnosis of malignancy were measured. The proportion of diagnostic failures was measured, and their risk factors were identified.

Results

The overall accuracy, sensitivity, specificity, PPV, and NPV were 91.1% (95% confidence interval [CI], 90.6–91.7%), 92.5% (95% CI, 91.9–93.1%), 86.5% (95% CI, 85.0–87.9%), 99.2% (95% CI, 99.0–99.4%), and 84.3% (95% CI, 82.7–85.8%), respectively. The proportion of diagnostic failures was 8.9% (831 of 9384; 95% CI, 8.3–9.4%). The independent risk factors for diagnostic failures were lesions ≤ 1 cm in size (adjusted odds ratio [AOR], 1.86; 95% CI, 1.23–2.81), lesion size 1.1–2 cm (1.75; 1.45–2.11), subsolid lesions (1.81; 1.32–2.49), use of fine needle aspiration only (2.43; 1.80–3.28), final diagnosis of benign lesions (2.18; 1.84–2.58), and final diagnosis of lymphomas (10.66; 6.21–18.30). Use of cone-beam CT (AOR, 0.31; 95% CI, 0.13–0.75) and conventional CT-guidance (0.55; 0.32–0.94) reduced diagnostic failures.

Conclusion

The accuracy of PTNB for diagnosis of malignancy was fairly high in our large-scale multi-institutional cohort. The identified risk factors for diagnostic failure may help reduce diagnostic failure and interpret the biopsy results.

Utility of CT radiomics for prediction of PD-L1 expression in advanced lung adenocarcinomas

Background

We aimed to assess if quantitative radiomic features can predict programmed death ligand 1 (PD‐L1) expression in advanced stage lung adenocarcinoma.

Methods

This retrospective study included 153 patients who had advanced stage (>IIIA by TNM classification) lung adenocarcinoma with pretreatment thin section computed tomography (CT) images and PD‐L1 expression test results in their pathology reports. Clinicopathological data were collected from electronic medical records. Visual analysis and radiomic feature extraction of the tumor from pretreatment CT were performed. We constructed two models for multivariate logistic regression analysis (one based on clinical variables, and the other based on a combination of clinical variables and radiomic features), and compared c‐statistics of the receiver operating characteristic curves of each model to identify the model with the higher predictability.

Results

Among 153 patients, 53 patients were classified as PD‐L1 positive and 100 patients as PD‐L1 negative. There was no significant difference in clinical characteristics or imaging findings on visual analysis between the two groups (P > 0.05 for all). Rad‐score by radiomic analysis was higher in the PD‐L1 positive group than in the PD‐L1 negative group with a statistical significance (−0.378 ± 1.537 vs. −1.171 ± 0.822, P = 0.0008). A prediction model that uses clinical variables and CT radiomic features showed higher performance compared to a prediction model that uses clinical variables only (c‐statistic = 0.646 vs. 0.550, P = 0.0299).

Conclusions

Quantitative CT radiomic features can predict PD‐L1 expression in advanced stage lung adenocarcinoma. A prediction model composed of clinical variables and CT radiomic features may facilitate noninvasive assessment of PD‐L1 expression.

Key points

Significant findings of the study

Quantitative CT radiomic features can help predict PD‐L1 expression, whereas none of the qualitative imaging findings is associated with PD‐L1 positivity.

What this study adds

A prediction model composed of clinical variables and CT radiomic features may facilitate noninvasive assessment of PD‐L1 expression.

Clinical Value of Cardiovascular Calcifications on Non-Enhanced, Non-ECG-Gated Chest CT

심혈관계 석회화는 다양한 심혈관계 질환에서 나타나며 심혈관 사건 발생의 표지자의 역할을 한다. CT의 기술이 발전함에 따라 심전도동기 CT뿐만이 아닌 비 심전도동기 CT에서도 심혈관계 석회화를 평가하는 것이 가능해졌다. 이번 종설에서는 비 조영증강 비 심전도동기 흉부 CT에서 발견되는 심혈관계 석회화를 심혈관 사건 발생과 연관되었다고 알려진 3가지 석회화(관상동맥, 흉부 대동맥, 판막 석회화)에 대해 자세히 살펴보고 추가적으로 우연적으로 발견될 수 있는 심막 석회화에 대해서도 간단히 기술하였다. 우리나라에서 2019년 하반기부터 폐암 검진이 시작되면서 고령 흡연자의 비 조영증강 비 심전도동기 저선량 CT의 영상의 수가 늘어나고 있고 이에 우연히 발견되는 심혈관계 석회화도 늘어나고 있다. 그러므로 비 조영증강 비 심전도동기 흉부 CT에서 발견되는 심혈관계 석회화의 의미를 이해하고 적절히 보고하는 것이 영상의학과 의사에게 중요할 것이다.

Utility of Cardiac CT for Preoperative Evaluation of Mitral Regurgitation: Morphological Evaluation of Mitral Valve and Prediction of Valve Replacement

OBJECTIVE

We aimed to investigate the diagnostic accuracy of cardiac computed tomography (CT) for the detection of mitral valve (MV) prolapse in mitral regurgitation (MR) with surgical findings as the standard reference, and to assess the predictability of MV replacement based on morphologic CT findings.

MATERIALS AND METHODS

A total of 156 patients who had undergone preoperative cardiac CT and subsequently received MV surgery due to severe MR were retrospectively enrolled. Non-repairable MV was defined when at least one of the following conditions was met: 1) anterior leaflet prolapse, 2) bi-leaflet prolapse, or 3) valve morphology (leaflet thickening, calcification, or mitral annular calcification [MAC]). Diagnostic performance of CT for the detection of the prolapsed segment was assessed with surgical findings as the standard reference. Logistic regression analysis was performed to evaluate the value of CT findings to predict actual valve replacement.

RESULTS

During surgery, MV prolapse was identified in 72.1%. The sensitivity, specificity, and diagnostic accuracy for the detection of MV prolapse were 99.1%, 81.4%, and 94.2%, respectively, per patient. One-hundred eighteen patients (75.6%) underwent MV repair and the remaining 38 patients received MV replacement. Bi-leaflet prolapse and valve morphology were independent predictors of valve replacement after adjusting for clinical variables (adjusted odds ratio, [OR] 8.63 for bi-leaflet prolapse; OR, 4.14 for leaflet thickening; and OR, 5.37 for leaflet calcium score > 5.6; p < 0.05).

CONCLUSION

Cardiac CT can have high diagnostic performance for detecting the prolapsed segment of the MV and predictability of valve replacement before surgery. Bi-leaflet prolapse and valve morphology, such as leaflet thickening, or calcification or MAC, are the most important predictors of valve replacement.

Value of Computed Tomography Radiomic Features for Differentiation of Periprosthetic Mass in Patients With Suspected Prosthetic Valve Obstruction

Background:

We aimed to determine whether quantitative computed tomography radiomic features can aid in differentiating between the causes of prosthetic valve obstruction (PVO) in patients who had undergone prosthetic valve replacement.

Methods:

This retrospective study included 39 periprosthetic masses in 34 patients who underwent cardiac computed tomography scan from January 2014 to August 2017 and were clinically suspected as PVO. The cause of PVO was assessed by redo-surgery and follow-up imaging as standard reference, and classified as pannus, thrombus, or vegetation. Visual analysis was performed to assess the possible cause of PVO on axial and valve-dedicated views. Computed tomography radiomic analysis of periprosthetic masses was performed and radiomic features were extracted. The advantage of radiomic score compared with visual analysis for differentiation of pannus from other abnormalities was assessed.

Results:

Of 39 masses, there were 20 cases of pannus, 11 of thrombus, and 8 of vegetation on final diagnosis. The radiomic score was significantly higher in the pannus group compared with nonpannus group (mean, −0.156±0.422 versus −0.883±0.474; P <0.001). The area under the curve of radiomic score for diagnosis of pannus was 0.876 (95% CI, 0.731–0.960). Combination of radiomic score and visual analysis showed a better performance for the differentiation of pannus than visual analysis alone.

Conclusions:

Compared with visual analysis, computed tomography radiomic features may have added value for differentiating pannus from thrombus or vegetation in patients with suspected PVO.

A Novel Algorithm to Differentiate Between Multiple Primary Lung Cancers and Intrapulmonary Metastasis in Multiple Lung Cancers With Multiple Pulmonary Sites of Involvement

INTRODUCTION

Differentiating between multiple primary lung cancer (MPLC) and intrapulmonary metastasis (IPM) is critical for developing a therapeutic strategy to treat multiple lung cancers with multiple pulmonary sites of involvement.

METHODS

We retrospectively included 252 lesions (126 pairs) from 126 patients with surgically resected multiple lung adenocarcinomas. Each pair was classified as MPLC or IPM based on histopathologic findings as the reference standard. A novel algorithm was established with four sequential decision steps based on the combination of computed tomography (CT) lesion types (step 1), CT lesion morphology (step 2), difference of maximal standardized uptake values on positron-emission tomography/CT (step 3), and presence of N2/3 lymph node metastasis or distant metastasis (step 4). The diagnostic accuracy of the algorithm was analyzed. Performances of 11 observers were assessed without and with knowledge of algorithm.

RESULTS

Among 126 pairs, 90 (71.4%) were classified as MPLCs and 36 (28.6%) as IPMs. On applying the diagnostic algorithm, the overall accuracy for diagnosis of IPM among conclusive cases up to step 4 was 88.9%, and 65 and 44 pairs were correctly diagnosed based on step 1 and step 2, respectively. Specificity and positive predictive value for diagnosis of IPM increased significantly in all observers compared with reading rounds without the algorithm.

CONCLUSIONS

Application of the algorithm based on comprehensive information on clinical and imaging variables can allow differentiation between MPLCs and IPMs. When both of two suspected malignant lesions appear as solid predominant lesions without spiculation or air-bronchogram on CT, IPM should be considered.

Analysis of Complications of Percutaneous Transthoracic Needle Biopsy Using CT-Guidance Modalities In a Multicenter Cohort of 10568 Biopsies

Objective

To analyze the complications of percutaneous transthoracic needle biopsy using CT-based imaging modalities for needle guidance in comparison with fluoroscopy in a large retrospective cohort.

Materials and Methods

This study was approved by multiple Institutional Review Boards and the requirement for informed consent was waived. We retrospectively included 10568 biopsies from eight referral hospitals from 2010 through 2014. In univariate and multivariate logistic analyses, 3 CT-based guidance modalities (CT, CT fluoroscopy, and cone-beam CT) were compared with fluoroscopy in terms of the risk of pneumothorax, pneumothorax requiring chest tube insertion, and hemoptysis, with adjustment for other risk factors.

Results

Pneumothorax occurred in 2298 of the 10568 biopsies (21.7%). Tube insertion was required after 316 biopsies (3.0%), and hemoptysis occurred in 550 cases (5.2%). In the multivariate analysis, pneumothorax was more frequently detected with CT {odds ratio (OR), 2.752 (95% confidence interval [CI], 2.325–3.258), p < 0.001}, CT fluoroscopy (OR, 1.440 [95% CI, 1.176–1.762], p < 0.001), and cone-beam CT (OR, 2.906 [95% CI, 2.235–3.779], p < 0.001), but no significant relationship was found for pneumothorax requiring chest tube insertion (p = 0.497, p = 0.222, and p = 0.216, respectively). The incidence of hemoptysis was significantly lower under CT (OR, 0.348 [95% CI, 0.247–0.491], p < 0.001), CT fluoroscopy (OR, 0.594 [95% CI, 0.419–0.843], p = 0.004), and cone-beam CT (OR, 0.479 [95% CI, 0.317–0.724], p < 0.001) guidance.

Conclusion

Hemoptysis occurred less frequently with CT-based guidance modalities in comparison with fluoroscopy. Although pneumothorax requiring chest tube insertion showed a similar incidence, pneumothorax was more frequently detected using CT-based guidance modalities.

Tricuspid annular diameter and right ventricular volume on preoperative cardiac CT can predict postoperative right ventricular dysfunction in patients who undergo tricuspid valve surgery

BACKGROUND

We investigated the predictive value of preoperative computed tomography (CT)-derived tricuspid annular and right ventricular (RV) parameters for postoperative RV dysfunction in patients undergoing tricuspid valve (TV) surgery.

METHODS

We retrospectively reviewed clinical, transthoracic echocardiography (TTE), and CT data of 100 consecutive patients who underwent cardiac CT and subsequently received TV surgery. Preoperative cardiac CT and TTE parameters were analyzed, including TV annulus diameter and RV size. Univariate and multivariate logistic regression analyses were performed to identify significant predictors for postoperative RV dysfunction, both in the entire study population and in the subgroup of patients without preoperative RV dysfunction.

RESULTS

Postoperative RV dysfunction occurred in 46% of all patients. In the multivariate logistic regression analysis, longer TV annulus diameter (>29.3 mm/m² on four-chamber view; (odds ratio [OR] 3.56, 95% confidence interval [CI] 1.13-11.24), larger RV volume (RV end-diastolic volume/body surface area > 128.8 ml/m²) on CT (OR 3.85, 95% CI 1.24-11.98) and presence of preoperative RV dysfunction on TTE (OR 11.96, 95% CI 2.8-50.99) were independent predictors for postoperative RV dysfunction in the entire study population (P < 0.05). Among patients without preoperative RV dysfunction, longer TV annulus diameter (OR 4.02, 95% CI 1.20-13.41) and larger RV volume on CT (OR 6.09, 95% CI 1.87-19.80) were independent predictors for postoperative RV dysfunction (P < 0.05).

CONCLUSIONS

Preoperative assessment of cardiac CT imaging-based TV annular diameter and RV volume can provide independent information for predicting postoperative RV dysfunction in patients undergoing TV surgery.

Nondiagnostic Percutaneous Transthoracic Needle Biopsy of Lung Lesions: A Multicenter Study of Malignancy Risk

Purpose To evaluate the malignancy risk of lung lesions that show nondiagnostic results at transthoracic needle biopsy (PTNB) of the lung and to identify any malignancy-associated risk factors in each nondiagnostic category. Materials and Methods In this retrospective study, 9384 initial PTNBs (9239 patients [mean age, 65 years; age range, 20-99 years] consisting of 5729 men [mean age, 66 years; age range, 20-99 years] and 3510 women [mean age, 63 years; age range, 20-94 years]) were performed in eight institutions between January 2010 and December 2014. PTNB results were categorized as diagnostic (malignant or specifically benign) or nondiagnostic (nonspecific benign pathologic findings, atypical cells, or insufficient specimen), and the proportion of final malignant diagnoses per nondiagnostic category was obtained. Malignancy-associated factors were determined by using multivariable analyses. Results Nondiagnostic results were present in 27.6% (2590 of 9384) of PTNBs. Proportions of final malignant diagnoses were 21.3% (339 of 1592) for nonspecific benignities, 90.1% (503 of 558) for atypical cells, and 46.6% (205 of 440) for insufficient specimens. In the nonspecific benign category, granulomatous inflammation (odds ratio [OR], 0.04; 95% confidence interval [CI]: 0.02, 0.12; P < .001), abscess (OR, 0.04; 95% CI: 0.01, 0.28; P = .001), and organizing pneumonia (OR, 0.05; 95% CI: 0.01, 0.23; P < .001) were demonstrated to be important factors negating malignancy. Atypical cells suspicious for malignancy were more associated with malignancy (OR, 6.3; 95% CI: 1.9, 21.0; P = .003) than were atypical cells of indeterminate malignancy. All 130 lesions with atypical cells suggestive of malignancy were finally malignant. Conclusion After nondiagnostic lung biopsies, lesions categorized as atypical cell lesions have a high likelihood of malignancy, with somewhat lower likelihood for lesions with insufficient specimens and nonspecific benign categories. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Elicker in this issue.

Thoracic recurrence in patients with curatively-resected colorectal cancer: incidence, risk factors, and value of chest CT as a postoperative surveillance tool

OBJECTIVE

To investigate the incidence of thoracic recurrence and the diagnostic value of chest CT for postoperative surveillance in curatively-resected colorectal cancer (CRC) patients.

METHODS

This retrospective study consisted of 648 CRC patients (M:F, 393:255; mean age, 66.2 years) treated with curative surgery between January 2010 and December 2012. The presence of CRC recurrence over follow-ups was analysed and recurrence-free survival and risk factors of recurrence were assessed using Kaplan-Meier analysis with log-rank test and Cox-regression analysis, respectively.

RESULTS

Over a median follow-up of 57 months, thoracic recurrence occurred in 8.0% (52/648) of patients with a median recurrence-free survival rate of 19.5 months. Among the 52 patients with thoracic recurrence, 18 (2.7%) had isolated thoracic recurrence, and only five (0.8%) were diagnosed through chest CT. Risk factors of overall thoracic recurrence included age, positive resection margin, presence of venous invasion, positive pathologic N-class, and presence of abdominal recurrence (odds ratio [OR] = 1.78, 19.691, 2.993, 2.502, and 31.137; p = 0.045, 0.004, 0.001, 0.005, and p < 0.001, respectively). As for isolated thoracic recurrence, serum carcinoembryonic antigen level ≥ 5 ng/mL during postoperative follow-up (OR = 9.112; p < 0.001) was demonstrated to be the only predictive factor. There were no thoracic recurrences in patients with CRC stages 0 and I.

CONCLUSION

In patients with curatively-resected CRCs, routine surveillance using chest CT may be of limited value, particularly in those with CRC stages 0 or I, as recurrence only detectable through chest CT was shown to be rare.

KEY POINTS

• Postoperative thoracic recurrence only detectable through chest CT was shown to be rare. • There were no thoracic recurrences in colorectal cancers stage 0 and I. • Postoperative surveillance chest CT is of limited value in patients with curatively resected colorectal cancers.