Caregivers of patients with long-term implantable ventricular assist device: a republication of the article published in the Japanese Journal of Artificial Organs.

Implantable ventricular assist device (VAD) has enabled patients with severe heart failure to be discharged from the hospital and to continue their care at home. The presence of caregivers is essential to maintain home care of patients with VAD. The caregivers are mainly the family members who live with the patient with VAD. The caregivers need to be trained (1) VAD device management, (2) disinfection of driveline skin punctures, (3) medication management, and (4) responding to sudden changes. The caregivers' lifestyle is also forced to change. In this article, we discuss the role of caregivers in the VAD era, where long-term support beyond 5 years is now possible. This review was created based on a translation of the Japanese review written in the Japanese Journal of Artificial Organs in 2023 (Vol. 52, No. 1, pp. 81-84), with some modifications.

Impact of the timing of first appropriate shock on outcomes in patients with an implantable cardioverter-defibrillator: Early versus late.

BACKGROUND: Appropriate implantable cardioverter-defibrillator (ICD) shocks are associated with an increased risk of mortality and heart failure (HF) events. The first appropriate shock may occur late after implantation. However, whether the timing of the first appropriate shock influences prognosis is unknown. This study aimed to evaluate the clinical significance of the timing of the first appropriate shock in patients with ICD. METHODS: This retrospective and observational study enrolled 565 consecutive ICD patients. Patients who received an appropriate shock were divided into the early group (first appropriate shock <1 year after ICD implantation) and late group (first appropriate shock ≥1 year after ICD implantation). All-cause mortality was compared between the two groups. RESULTS: Over a median follow-up of 5.6 years, 112 (19.8%) patients received an appropriate shock, including 32 patients (28.6%) in the early group and 80 patients (71.4%) in the late group. Comparisons of baseline characteristics at ICD implantation revealed that the late group was more likely to receive cardiac resynchronization therapy (66.3% vs. 31.3%, p < 0.001), ICD for primary prevention (60.0% vs. 31.3%, p = 0.001), and angiotensin-converting enzyme inhibitor or angiotensin-receptor blocker treatment (88.8% vs. 71.9%, p = 0.028). Survival after shock was significantly worse in the late group than in the early group (p = 0.027). In multivariable Cox proportional hazards analysis, the late group had an increased risk of all-cause mortality compared with the early group (HR: 2.22; 95% CI 1.01-4.53; p = 0.029). In both groups, the most common cause of death was HF. CONCLUSIONS: Late occurrence of the first appropriate ICD shock was associated with a worse prognosis compared with early occurrence of the first appropriate shock. Cardiac death was the most common cause of death in patients who experienced late occurrence of the first appropriate ICD shock, resulting from HF in most cases.

Implication of modified MELD scores for postdischarge prognosis in hospitalized patients with heart failure.

We evaluated whether modified Model for End-Stage Liver Disease (MELD) scores are useful for predicting the postdischarge prognosis in hospitalized patients with heart failure (HF) who are discharged alive. The MELD-XI and MELD-Na scores were calculated at discharge for a total of 1156 patients in the HIJ-HF II study. We also studied 3 groups on the basis of the left ventricular ejection fraction (LVEF): the HFrEF (LVEF < 40%), HFmrEF (LVEF 40-49%) and HFpEF (LVEF ≥ 50%) groups. The primary outcome was all-cause mortality, and the secondary outcome was rehospitalization due to worsening HF. The median MELD-XI and MELD-Na scores were 12 and 14, respectively. After a median follow-up of 19 months, there were significantly higher rates of all-cause mortality in patients with MELD-XI scores ≥ 12 than in those with MELD-XI scores < 12; there were also higher rates of all-cause mortality in patients with MELD-Na scores ≥ 14 than in those with MELD-Na scores < 14 (both log-rank p < 0.001). The cumulative incidence function based on a competing risks model showed a higher rate of rehospitalization due to worsening HF in patients with MELD-XI scores ≥ 12 than in those with MELD-XI scores < 12 and a higher rate of rehospitalization due to worsening HF in those with MELD-Na scores ≥ 14 than in those with MELD-Na scores < 14 (both Gray's test p < 0.001). The adjusted hazard ratios (HRs) of all-cause mortality for patients with MELD-XI scores ≥ 12 and those with MELD-Na scores ≥ 14 were 2.07 [95% confidence interval (CI) 1.25-3.44] and 2.79 [95% CI 1.63-4.79], respectively, in the HFrEF group; however, the HRs were not significant in the HFmrEF or HFpEF groups. Thus, MELD-XI and MELD-Na scores may be useful for predicting prognosis in hospitalized HF patients who are discharged alive, especially for those in the HFrEF group.

Diagnostic performance for pulmonary adenocarcinoma on CT: comparison of radiologists with and without three-dimensional convolutional neural network.

OBJECTIVES: To compare diagnostic performance for pulmonary invasive adenocarcinoma among radiologists with and without three-dimensional convolutional neural network (3D-CNN). METHODS: Enrolled were 285 patients with adenocarcinoma in situ (AIS, n = 75), minimally invasive adenocarcinoma (MIA, n = 58), and invasive adenocarcinoma (IVA, n = 152). A 3D-CNN model was constructed with seven convolution-pooling and two max-pooling layers and fully connected layers, in which batch normalization, residual connection, and global average pooling were used. Only the flipping process was performed for augmentation. The output layer comprised two nodes for two conditions (AIS/MIA and IVA) according to prognosis. Diagnostic performance of the 3D-CNN model in 285 patients was calculated using nested 10-fold cross-validation. In 90 of 285 patients, results from each radiologist (R1, R2, and R3; with 9, 14, and 26 years of experience, respectively) with and without the 3D-CNN model were statistically compared. RESULTS: Without the 3D-CNN model, accuracy, sensitivity, and specificity of the radiologists were as follows: R1, 70.0%, 52.1%, and 90.5%; R2, 72.2%, 75%, and 69%; and R3, 74.4%, 89.6%, and 57.1%, respectively. With the 3D-CNN model, accuracy, sensitivity, and specificity of the radiologists were as follows: R1, 72.2%, 77.1%, and 66.7%; R2, 74.4%, 85.4%, and 61.9%; and R3, 74.4%, 93.8%, and 52.4%, respectively. Diagnostic performance of each radiologist with and without the 3D-CNN model had no significant difference (p > 0.88), but the accuracy of R1 and R2 was significantly higher with than without the 3D-CNN model (p < 0.01). CONCLUSIONS: The 3D-CNN model can support a less-experienced radiologist to improve diagnostic accuracy for pulmonary invasive adenocarcinoma without deteriorating any diagnostic performances. KEY POINTS: • The 3D-CNN model is a non-invasive method for predicting pulmonary invasive adenocarcinoma in CT images with high sensitivity. • Diagnostic accuracy by a less-experienced radiologist was better with the 3D-CNN model than without the model.

Deep learning algorithm for detection of aortic dissection on non-contrast-enhanced CT.

OBJECTIVES: To develop a deep learning-based algorithm to detect aortic dissection (AD) and evaluate the diagnostic ability of the algorithm compared with those of radiologists. METHODS: Included in the study were 170 patients (85 with AD and 85 without AD). An AD detection algorithm was developed using a convolutional neural network with Xception architecture. Of the patient data, 80% were used for training and validation and 20% were used for testing. Fivefold cross-validation was performed to evaluate the method. An average of 6688 non-contrast-enhanced CT images (slice thickness, 5 mm) were used for training. A radiologist reviewed both contrast-enhanced and non-contrast-enhanced images and identified the slices of AD. The identified slices were used as ground truth. Receiver operating characteristic curve and area under the curve (AUC) analysis was performed. Five radiologists independently evaluated the images. The accuracy, sensitivity, and specificity of the algorithm and those of the radiologists were compared. RESULTS: The AUC of the developed algorithm was 0.940, and a cutoff value of 0.400 provided accuracy of 90.0%, sensitivity of 91.8%, and specificity of 88.2%. For the radiologists, median (range) accuracy, sensitivity, and specificity were 88.8 (83.5-94.1)%, 90.6 (83.5-94.1)%, and 94.1 (72.9-97.6)%, respectively. There was no significant difference in performance in terms of accuracy, sensitivity, or specificity between the algorithm and the average performance of the radiologists (p > 0.05). CONCLUSIONS: The developed algorithm showed comparable diagnostic performance to radiologists for detecting AD, which suggests the potential of the proposed method to support clinical practice by reducing missed ADs. KEY POINTS: • A deep learning-based algorithm for detecting aortic dissection was developed using the non-contrast-enhanced CT images of 170 patients. • The algorithm had an AUC of 0.940 for detecting aortic dissection. • The accuracy, sensitivity, and specificity of the algorithm were comparable to those of radiologists.

Lung Adenocarcinoma at CT with 0.25-mm Section Thickness and a 2048 Matrix: High-Spatial-Resolution Imaging for Predicting Invasiveness.

Background High-spatial-resolution (HSR) CT provides detailed information and clear delineation of lung anatomy and disease states. HSR CT may have high diagnostic performance for predicting invasiveness of lung adenocarcinoma. Purpose To examine the diagnostic performance of HSR CT in predicting the invasiveness of lung adenocarcinoma. Materials and Methods In this retrospective study, 89 consecutive patients with adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), or invasive adenocarcinoma (IVA) were included who underwent surgery for lung cancer between January 2018 and December 2019. All patients underwent HSR CT with 0.25-mm section thickness and a 2048 matrix. Two independent observers evaluated the images for the presence or absence of the following HSR CT findings: lobulation, spiculation, pleural indentation, vessel convergence, homogeneity of ground-glass opacity, reticulation, irregularity and centrality of solid portion, and air bronchiologram (irregularity, disruption, or dilatation). The total diameter (≤1.6 cm or >1.6 cm) and the longest diameter of the solid portion (≤0.8 cm or >0.8 cm) were evaluated. Logistic regression models were used to identify findings associated with MIA plus IVA. Receiver operating characteristic analysis was performed to determine diagnostic performance. Results Eighty-nine patients (mean, 69 years ± 11 [standard deviation]; 49 men) were evaluated. The size of the nodules with invasion was a mean of 2.5 cm ± 1.2. Univariable analysis revealed lobulation, spiculation, pleural indentation, irregular and central solid portion, air bronchiologram with disruption and/or irregular dilatation, and total and solid portion diameters as associated with MIA plus IVA (all, P < .05). After adjustment for age, sex, and pack-years of smoking, disruption of air bronchogram and solid portion diameter greater than 0.8 cm remained as predictors of invasiveness (P = .001 and P = .02, respectively). The diagnostic performance of these two findings combined were as follows: sensitivity of 97% (59 of 61 patients; 95% confidence interval: 94%, 100%) and specificity of 86% (19 of 22 patients; 95% confidence interval: 65%, 97%), with an area under the curve of 0.94. Conclusion Using high-spatial-resolution CT, disruption of air bronchiologram and a solid portion greater than 0.8 cm were independently associated with a greater likelihood of invasiveness in lung adenocarcinoma. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Lynch and Oh in this issue.

Influence of field of view size on image quality: ultra-high-resolution CT vs. conventional high-resolution CT.

OBJECTIVES: This study was conducted in order to compare the effect of field of view (FOV) size on image quality between ultra-high-resolution CT (U-HRCT) and conventional high-resolution CT (HRCT). METHODS: Eleven cadaveric lungs were scanned with U-HRCT and conventional HRCT and reconstructed with five FOVs (40, 80, 160, 240, and 320 mm). Three radiologists evaluated and scored the images. Three image evaluations were performed, comparing the image quality with the five FOVs with respect to the 160-mm FOV. The first evaluation was performed on conventional HRCT images, and the second evaluation on U-HRCT images. Images were scored on normal structure, abnormal findings, and overall image quality. The third evaluation was a comparison of the images obtained with conventional HRCT and U-HRCT, with scoring performed on overall image quality. Quantitative evaluation of noise was performed by setting ROIs. RESULTS: In conventional HRCT, image quality was improved when the FOV was reduced to 160 mm. In U-HRCT, image quality, except for noise, improved when the FOV was reduced to 80 mm. In the third evaluation, overall image quality was improved in U-HRCT over conventional HRCT at all FOVs. Noise of U-HRCT increased with respect to conventional HRCT when the FOV was reduced from 160 to 40 mm. However, at 240- and 320-mm FOVs, the noise of U-HRCT and conventional HRCT showed no differences. CONCLUSIONS: In conventional HRCT, image quality did not improve when the FOV was reduced below 160 mm. However, in U-HRCT, image quality improved even when the FOV was reduced to 80 mm. KEY POINTS: • Reducing the size of the field of view to 160 mm improves diagnostic imaging quality in high-resolution CT. • In ultra-high-resolution CT, improvements in image quality can be obtained by reducing the size of the field of view to 80 mm. • Ultra-high-resolution CT produces images of higher quality compared with conventional HRCT irrespective of the size of the field of view.

Subjective and objective comparisons of image quality between ultra-high-resolution CT and conventional area detector CT in phantoms and cadaveric human lungs.

OBJECTIVES: To compare the image quality of the lungs between ultra-high-resolution CT (U-HRCT) and conventional area detector CT (AD-CT) images. METHODS: Image data of slit phantoms (0.35, 0.30, and 0.15 mm) and 11 cadaveric human lungs were acquired by both U-HRCT and AD-CT devices. U-HRCT images were obtained with three acquisition modes: normal mode (U-HRCTN: 896 channels, 0.5 mm × 80 rows; 512 matrix), super-high-resolution mode (U-HRCTSHR: 1792 channels, 0.25 mm × 160 rows; 1024 matrix), and volume mode (U-HRCTSHR-VOL: non-helical acquisition with U-HRCTSHR). AD-CT images were obtained with the same conditions as U-HRCTN. Three independent observers scored normal anatomical structures (vessels and bronchi), abnormal CT findings (faint nodules, solid nodules, ground-glass opacity, consolidation, emphysema, interlobular septal thickening, intralobular reticular opacities, bronchovascular bundle thickening, bronchiectasis, and honeycombing), noise, artifacts, and overall image quality on a 3-point scale (1 = worst, 2 = equal, 3 = best) compared with U-HRCTN. Noise values were calculated quantitatively. RESULTS: U-HRCT could depict a 0.15-mm slit. Both U-HRCTSHR and U-HRCTSHR-VOL significantly improved visualization of normal anatomical structures and abnormal CT findings, except for intralobular reticular opacities and reduced artifacts, compared with AD-CT (p < 0.014). Visually, U-HRCTSHR-VOL has less noise than U-HRCTSHR and AD-CT (p < 0.00001). Quantitative noise values were significantly higher in the following order: U-HRCTSHR (mean, 30.41), U-HRCTSHR-VOL (26.84), AD-CT (16.03), and U-HRCTN (15.14) (p < 0.0001). U-HRCTSHR and U-HRCTSHR-VOL resulted in significantly higher overall image quality than AD-CT and were almost equal to U-HRCTN (p < 0.0001). CONCLUSIONS: Both U-HRCTSHR and U-HRCTSHR-VOL can provide higher image quality than AD-CT, while U-HRCTSHR-VOL was less noisy than U-HRCTSHR. KEY POINTS: • Ultra-high-resolution CT (U-HRCT) can improve spatial resolution. • U-HRCT can reduce streak and dark band artifacts. • U-HRCT can provide higher image quality than conventional area detector CT. • In U-HRCT, the volume mode is less noisy than the super-high-resolution mode. • U-HRCT may provide more detailed information about the lung anatomy and pathology.

Impact of Coronary Artery Calcification in the Donor Heart on Transmitted Coronary Artery Disease in Heart Transplant Recipients.

BACKGROUND: Coronary artery disease (CAD) after heart transplantation (HTx) develops as a combination of donor-transmitted coronary atherosclerosis (DTCA) and cardiac allograft vasculopathy. Assessing donor CAD before procurement is important. Because coronary artery calcification (CAC) is a predictor for CAD, donor-heart CAC is usually evaluated to estimate the risk of donor CAD. The usefulness of CAC for predicting DTCA, however, is not known. Methods and Results: Sixty-four HTx recipients whose donor underwent chest computed tomography before procurement or ≤2 weeks after HTx and who underwent coronary angiography and intravascular ultrasound (IVUS) ≤3 months after HTx were enrolled. Eight patients had CAC (CAC group) and 56 patients did not have CAC (no-CAC group). Patients in the CAC group were significantly older and had a higher prevalence of maximum intimal thickness (MIT) of the coronary artery ≥0.5 mm at initial IVUS than patients in the no-CAC group (100% vs. 55%, P=0.02). Adverse cardiac events and death were not significantly different. Everolimus tended to be used more often in the CAC group. CONCLUSIONS: Donor-heart CAC is a significant predictor for MIT of the coronary artery ≥0.5 mm after HTx. The presence of CAC, however, is not associated with future cardiac events. The higher prevalence of everolimus use in the CAC group may have affected the results.

Pulmonary Emphysema Quantification on Ultra-Low-Dose Computed Tomography Using Model-Based Iterative Reconstruction With or Without Lung Setting.

OBJECTIVES: To evaluate the influence of model-based iterative reconstruction (MBIR) with lung setting and conventional setting on pulmonary emphysema quantification by ultra-low-dose computed tomography (ULDCT) compared with standard-dose CT (SDCT). METHODS: Forty-five patients who underwent ULDCT (0.18 ± 0.02 mSv) and SDCT (6.66 ± 2.69 mSv) were analyzed in this retrospective study. Images were reconstructed using filtered back projection (FBP) with smooth and sharp kernels and MBIR with conventional and lung settings. Extent of emphysema was evaluated using fully automated software. Correlation between ULDCT and SDCT was assessed by interclass correlation coefficiency (ICC) and Bland-Altman analysis. RESULTS: Excellent correlation was seen between MBIR with conventional setting on ULDCT and FBP with smooth kernel on SDCT (ICC, 0.97; bias, -0.31%) and between MBIR with lung setting on ULDCT and FBP with sharp kernel on SDCT (ICC, 0.82; bias, -2.10%). CONCLUSION: Model-based iterative reconstruction improved the agreement between ULDCT and SDCT on emphysema quantification.

Increased Left Ventricular End-Diastolic Volume Index Is Associated With Increased Adverse Events After MitraClip Implantation.

This study investigated the association between the left ventricular end-diastolic volume index (LVEDVI) and the incidence of adverse clinical events in patients after MitraClip implantation. In this retrospective, observational study, 123 patients who underwent the MitraClip procedure were enrolled. Participants were divided into 2 groups according to the LVEDVI cut-off level, calculated using receiver operating characteristic curve analysis, to predict the primary end point and the occurrence of cardiovascular events was compared between the groups. The primary end point was all-cause mortality and hospitalization because of heart failure. The receiver operating characteristic curve analysis for the composite primary end point revealed an LVEDVI cut-off point of 118 ml/m2. Based on this threshold, 61 patients (49.6%) were categorized into the LVEDVI <118 ml/m2 group, whereas 62 (50.4%) fell into the LVEDVI ≥118 ml/m2 group. Over a median follow-up period of 336 days (interquartile range 80 to 667), the primary end points occurred in 15 and 26 patients in the LVEDVI <118 and LVEDVI ≥118 ml/m2 groups, corresponding to incidence rates of 24.6% and 41.9%, respectively. Patients in the LVEDVI ≥118 ml/m2 group demonstrated a significantly higher risk of adverse clinical events than those in the LVEDVI <118 ml/m2 group (hazard ratio 2.24, 95% confidence interval 1.17 to 4.28, p = 0.01). This trend persisted even after adjusting for several confounders (p = 0.02). In conclusion, increased LVEDVI values were associated with increased adverse clinical events after MitraClip implantation in patients with severe mitral valve regurgitation.

Three-dimensional iodine mapping quantified by dual-energy CT for predicting programmed death-ligand 1 expression in invasive pulmonary adenocarcinoma.

We examined the association between texture features using three-dimensional (3D) io-dine density histogram on delayed phase of dual-energy CT (DECT) and expression of programmed death-ligand 1 (PD-L1) using immunostaining methods in non-small cell lung cancer. Consecutive 37 patients were scanned by DECT. Unenhanced and enhanced (3 min delay) images were obtained. 3D texture analysis was performed for each nodule to obtain 7 features (max, min, median, mean, standard deviation, skewness, and kurtosis) from iodine density mapping and extracellular volume (ECV). A pathologist evaluated a tumor proportion score (TPS, %) using PD-L1 immunostaining: PD-L1 high (TPS ≥ 50%) and low or negative expression (TPS < 50%). Associations between PD-L1 expression and each 8 parameter were evaluated using logistic regression analysis. The multivariate logistic regression analysis revealed that skewness and ECV were independent indicators associated with high PD-L1 expression (skewness: odds ratio [OR] 7.1 [95% CI 1.1, 45.6], p = 0.039; ECV: OR 6.6 [95% CI 1.1, 38.4], p = 0.037). In the receiver-operating characteristic analysis, the area under the curve of the combination of skewness and ECV was 0.83 (95% CI 0.67, 0.93) with sensitivity of 64% and specificity of 96%. Skewness from 3D iodine density histogram and ECV on dual energy CT were significant factors for predicting PD-L1 expression.

Prediction of cardiac allograft vasculopathy using splenic switch-off on myocardial PET.

BACKGROUND: Heart transplantation (HTx) is a definitive therapy for refractory heart failure. Cardiac allograft vasculopathy (CAV), characterized by diffuse arteriopathy involving the epicardial coronary arteries and microvasculature, is the major cause of death for patients with HTx. 13N-ammonia positron emission tomography (NH3-PET) can offer diagnostic and prognostic utility for CAV. The splenic switch-off (SSO) detected in NH3-PET is a hemodynamic indicator of favorable response to adenosine. We hypothesized that both CAV and SSO reflected a pathology that progresses in parallel with systemic vascular endothelial dysfunction. Therefore, we quantitatively evaluated splenic adenosine reactivity measured using NH3-PET as an index of endothelial function, and examined its predictability for CAV. METHODS: Forty-eight patients who underwent NH3-PET after HTx were analyzed. The spleen ratio was calculated as the mean standardized uptake value, measured by placing an ROI on the spleen, at stress divided by that at rest. SSO was defined by a cutoff determined using receiver operating characteristic (ROC) analysis for the spleen ratio. The endpoint was appearance or progression of CAV. Predictability of SSO was analyzed using Kaplan-Meier analysis. RESULTS: The endpoint occurred in 9 patients during a mean follow-up of 45 ±â€¯17 months. ROC curve analysis demonstrated a cutoff of 0.94 for spleen ratio. Patients without SSO displayed a significantly higher CAV rate than those with SSO (p = 0.022). CONCLUSIONS: SSO reflects the endothelial function of systemic blood vessels and was a predictor of CAV in patients with HTx.

Photon-Counting Detector CT Radiological-Histological Correlation in Cadaveric Human Lung Nodules and Airways.

OBJECTIVES: The aim of this study was to compare the performances of photon-counting detector computed tomography (PCD-CT) and energy-integrating detector computed tomography (EID-CT) for visualizing nodules and airways in human cadaveric lungs. MATERIALS AND METHODS: Previously obtained 20 cadaveric lungs were scanned, and images were prospectively acquired by EID-CT and PCD-CT at a radiation dose with a noise level equivalent to the diagnostic reference level. PCD-CT was scanned with ultra-high-resolution mode. The EID-CT images were reconstructed with a 512 matrix, 0.6-mm thickness, and a 350-mm field of view (FOV). The PCD-CT images were reconstructed at 3 settings: PCD-512: same as EID-CT; PCD-1024-FOV350: 1024 matrix, 0.2-mm thickness, 350-mm FOV; and PCD-1024-FOV50: 1024 matrix, 0.2-mm thickness, 50-mm FOV. Two specimens per lung were examined after hematoxylin and eosin staining. The CT images were evaluated for nodules on a 5-point scale and for airways on a 4-point scale to compare the histology. The Wilcoxon signed rank test with Bonferroni correction was performed for statistical analyses. RESULTS: Sixty-seven nodules (1321 µm; interquartile range [IQR], 758-3105 µm) and 92 airways (851 µm; IQR, 514-1337 µm) were evaluated. For nodules and airways, scores decreased in order of PCD-1024-FOV50, PCD-1024-FOV350, PCD-512, and EID-CT. Significant differences were observed between series other than PCD-1024-FOV350 versus PCD-1024-FOV50 for nodules (PCD-1024-FOV350 vs PCD-1024-FOV50, P = 0.063; others P < 0.001) and between series other than EID-CT versus PCD-512 for airways (EID-CT vs PCD-512, P = 0.549; others P < 0.005). On PCD-1024-FOV50, the median size of barely detectable nodules was 604 µm (IQR, 469-756 µm) and that of barely detectable airways was 601 µm (IQR, 489-929 µm). On EID-CT, that of barely detectable nodules was 837 µm (IQR, 678-914 µm) and that of barely detectable airways was 1210 µm (IQR, 674-1435 µm). CONCLUSIONS: PCD-CT visualized small nodules and airways better than EID-CT and improved with high spatial resolution and potentially can detect submillimeter nodules and airways.

Association between interstitial lung abnormality and mortality in patients with esophageal cancer.

PURPOSE: To investigate the relationship between interstitial lung abnormalities (ILAs) and mortality in patients with esophageal cancer and the cause of mortality. MATERIALS AND METHODS: This retrospective study investigated patients with esophageal cancer from January 2011 to December 2015. ILAs were visually scored on baseline CT using a 3-point scale (0 = non-ILA, 1 = indeterminate for ILA, and 2 = ILA). ILAs were classified into subcategories of non-subpleural, subpleural non-fibrotic, and subpleural fibrotic. Five-year overall survival (OS) was compared between patients with and without ILAs using the multivariable Cox proportional hazards model. Subgroup analyses were performed based on cancer stage and ILA subcategories. The prevalences of treatment complications and death due to esophageal cancer and pneumonia/respiratory failure were analyzed using Fisher's exact test. RESULTS: A total of 478 patients with esophageal cancer (age, 66.8 years ± 8.6 [standard deviation]; 64 women) were evaluated in this study. Among them, 267 patients showed no ILAs, 125 patients were indeterminate for ILAs, and 86 patients showed ILAs. ILAs were a significant factor for shorter OS (hazard ratio [HR] = 1.68, 95% confidence interval [CI] 1.10-2.55, P = 0.016) in the multivariable Cox proportional hazards model adjusting for age, sex, smoking history, clinical stage, and histology. On subgroup analysis using patients with clinical stage IVB, the presence of ILAs was a significant factor (HR = 3.78, 95% CI 1.67-8.54, P = 0.001). Subpleural fibrotic ILAs were significantly associated with shorter OS (HR = 2.22, 95% CI 1.25-3.93, P = 0.006). There was no significant difference in treatment complications. Patients with ILAs showed a higher prevalence of death due to pneumonia/respiratory failure than those without ILAs (non-ILA, 2/95 [2%]; ILA, 5/39 [13%]; P = 0.022). The prevalence of death due to esophageal cancer was similar in patients with and without ILA (non-ILA, 82/95 [86%]; ILA 32/39 [82%]; P = 0.596). CONCLUSION: ILAs were significantly associated with shorter survival in patients with esophageal cancer.

Dual-source photon-counting computed tomography for coronary in-stent observation: influence of heart rate and virtual monoenergetic image.

To investigate the effect of heart rate and virtual monoenergetic image (VMI) on coronary stent imaging in dual-source photon-counting detector computed tomography (PCD-CT). A dynamic cardiac phantom was used to vary the heart rate at 50 beats per minute (bpm), 70 bpm, and 90 bpm. Five types of stents (4.0 mm, 3.5 mm, 3.0 mm, 2.75 mm, and 2.5 mm diameter) were scanned at three different locations and reconstructed VMI at 70 keV. In addition, 50% stenosis was assessed for 3.0 mm and 4.0 mm stents. To assess in-stent stenosis, 40 keV, 70 keV, and 100 keV images were compared. Measurable lumen and contrast to noise ratio (CNR) from lumen to stenosis were evaluated quantitatively. A-4-point scale was used for the qualitative image quality of in-stent stenosis. The measurable lumen had no significant differences among heart rates in patent stents (p = 0.55). In-stent stenosis, the residual lumen was significantly larger in 40 keV [27.5% (20.8-32.3%)] than in 70 keV [11.5% (10.0-23.0%), p < 0.05] and 100 keV [0% (0-5.2%), p < 0.05]. The CNR was higher in 40 keV [12.5 (7.5-18.2)] than in 70 keV [5.3 (2.9-7.7), p < 0.05] and 100 keV [1.3 (0.5-2.7), p < 0.05]. The image quality was better in 40 keV (3.4 ± 0.7) than in 70 keV [(2.6 ± 0.8), p < 0.05] and 100 keV [(1.3 ± 0.4), p < 0.05]. Dual-source PCD-CT maintains a measurable lumen even at high heart rates. Adjusting the VMI can be helpful in visualizing the in-stent stenosis.