Computed Diffusion-Weighted Images of Rectal Cancer: Image Quality, Restaging, and Treatment Response after Neoadjuvant Therapy.

BACKGROUND: Computed diffusion-weighted images (cDWI) of random b value could be derived from acquired DWI (aDWI) with at least two different b values. However, its comparison between aDWI and cDWI images in locally advanced rectal cancer (LARC) patients after neoadjuvant therapy (NT) is needed. PURPOSE: To compare the cDWI and aDWI in image quality, restaging, and treatment response of LARC after NT. STUDY TYPE: Retrospective. POPULATION: Eighty-seven consecutive patients. FIELD STRENGTH/SEQUENCE: 3.0 T/DWI. ASSESSMENT: All patients underwent two DWI sequences, including conventional acquisition with b = 0 and 1000 s/mm2 (aDWIb1000 ) and another with b = 0 and 700 s/mm2 on a 3.0-T MR scanner. The images of the latter were used to compute the diffusion images with b = 1000 s/mm2 (cDWIb1000 ). Four radiologists with 3, 4, 14, and 25 years of experience evaluated the images to compare the image quality, TN restaging performance, and treatment response between aDWIb1000 and cDWIb1000 . STATISTICAL TESTS: Interclass correlation coefficients, weighted κ coefficient, paired Wilcoxon, and McNemar or Fisher test were used. A significance level of 0.05 was used. RESULTS: The cDWIb1000 images were superior to the aDWIb1000 ones in both subjective and objective image quality. In T restaging, the overall diagnostic accuracy of cDWIb1000 images was higher than that of aDWIb1000 images (57.47% vs. 49.43%, P = 0.289 for the inexperienced radiologist; 77.01% vs. 63.22%, significant for the experienced radiologist), with better sensitivity in determining ypT0-Tis tumors. Additionally, it increased the sensitivity in detecting ypT2 tumors for the inexperienced radiologist and ypT3 tumors for the experienced radiologist. N restaging and treatment response were found to be similar between two sequences for both radiologists. DATA CONCLUSION: Compared to aDWIb1000 images, the computed ones might serve as a wise approach, providing comparable or better image quality, restaging performance, and treatment response assessment for LARC after NT. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

Efficacy and prognostic value of delta radiomics on dual-energy computed tomography for gastric cancer with neoadjuvant chemotherapy: a preliminary study.

BACKGROUND: A non-invasive tool for tumor regression grade (TRG) evaluation is urgently needed for gastric cancer (GC) treated with neoadjuvant chemotherapy (NAC). PURPOSE: To develop and validate a radiomics signature (RS) to evaluate TRG for locally advanced GC after NAC and assess its prognostic value. MATERIAL AND METHODS: A total of 103 patients with GC treated with NAC were retrospectively recruited from April 2018 to December 2019 and were randomly allocated into a training cohort (n = 69) and a validation cohort (n = 34). Delineation was performed on both mixed and iodine-uptake images based on dual-energy computed tomography (DECT). A total of 4094 radiomics features were extracted from the pre-NAC, post-NAC, and delta feature sets. Spearman correlation and the least absolute shrinkage and selection operator were used for dimensionality reduction. Multivariable logistic regression was used for TRG evaluation and generated the optimal RS. Kaplan-Meier survival analysis with the log-rank test was implemented in an independent cohort of 40 patients to validate the prognostic value of the optimal RS. RESULTS: Three, five, and six radiomics features were finally selected for the pre-NAC, post-NAC, and delta feature sets. The delta model demonstrated the best performance in assessing TRG in both the training and the validation cohorts (AUCs=0.91 and 0.76, respectively; P>0.1). The optimal RS from the delta model showed a significant capability to predict survival in the independent cohort (P<0.05). CONCLUSION: Delta radiomics based on DECT images serves as a potential biomarker for TRG evaluation and shows prognostic value for patients with GC treated with NAC.

Assessment of liver metastases radiomic feature reproducibility with deep-learning-based semi-automatic segmentation software.

BACKGROUND: Good feature reproducibility enhances model reliability. The manual segmentation of gastric cancer with liver metastasis (GCLM) can be time-consuming and unstable. PURPOSE: To assess the value of a semi-automatic segmentation tool in improving the reproducibility of the radiomic features of GCLM. MATERIAL AND METHODS: Patients who underwent dual-source computed tomography were retrospectively reviewed. As an intra-observer analysis, one radiologist segmented metastatic liver lesions manually and semi-automatically twice. Another radiologist re-segmented the lesions once as an inter-observer analysis. A total of 1691 features were extracted. Spearman rank correlation was used for feature reproducibility analysis. The times for manual and semi-automatic segmentation were recorded and analyzed. RESULTS: Seventy-two patients with 168 lesions were included. Most of the GCLM radiomic features became more reliable with the tool than the manual method. For the intra-observer feature reproducibility analysis of manual and semi-automatic segmentation, the rates of features with good reliability were 45.5% and 62.3% (P < 0.02), respectively; for the inter-observer analysis, the rates were 29.3% and 46.0% (P < 0.05), respectively. For feature types, the semi-automatic method increased reliability in 6/7 types in the intra-observer analysis and 5/7 types in the inter-observer analysis. For image types, the reliability of the square and exponential types was significantly increased. The mean time of semi-automatic segmentation was significantly shorter than that of the manual method (P < 0.05). CONCLUSION: The application of semi-automated software increased feature reliability in the intra- and inter-observer analyses. The semi-automatic process took less time than the manual process.

Clinical Features and Chest CT Manifestations of Coronavirus Disease 2019 (COVID-19) in a Single-Center Study in Shanghai, China.

OBJECTIVE. Confronting the new coronavirus infection known as coronavirus disease 2019 (COVID-19) is challenging and requires excluding patients with suspected COVID-19 who actually have other diseases. The purpose of this study was to assess the clinical features and CT manifestations of COVID-19 by comparing patients with COVID-19 pneumonia with patients with non-COVID-19 pneumonia who presented at a fever observation department in Shanghai, China. MATERIALS AND METHODS. Patients were retrospectively enrolled in the study from January 19 through February 6, 2020. All patients underwent real-time reverse transcription-polymerase chain reaction (RT-PCR) testing. RESULTS. Eleven patients had RT-PCR test results that were positive for severe acute respiratory syndrome coronavirus 2, whereas 22 patients had negative results. No statistical difference in clinical features was observed (p > 0.05), with the exception of leukocyte and platelet counts (p < 0.05). The mean (± SD) interval between onset of symptoms and admission to the fever observation department was 4.40 ± 2.00 and 5.52 ± 4.00 days for patients with positive and negative RT-PCR test results, respectively. The frequency of opacifications in patients with positive results and patients with negative results, respectively, was as follows: ground-glass opacities (GGOs), 100.0% versus 90.9%; mixed GGO, 63.6% versus 72.7%; and consolidation, 54.5% versus 77.3%. In patients with positive RT-PCR results, GGOs were the most commonly observed opacification (seen in 100.0% of patients) and were predominantly located in the peripheral zone (100.0% of patients), compared with patients with negative results (31.8%) (p = 0.05). The median number of affected lung lobes and segments was higher in patients with positive RT-PCR results than in those with negative RT-PCR results (five vs 3.5 affected lobes and 15 vs nine affected segments; p < 0.05). Although the air bronchogram reticular pattern was more frequently seen in patients with positive results, centrilobular nodules were less frequently seen in patients with positive results. CONCLUSION. At the point during the COVID-19 outbreak when this study was performed, imaging patterns of multifocal, peripheral, pure GGO, mixed GGO, or consolidation with slight predominance in the lower lung and findings of more extensive GGO than consolidation on chest CT scans obtained during the first week of illness were considered findings highly suspicious of COVID-19.

Can the Wall Shear Stress Values of Left Internal Mammary Artery Grafts during the Perioperative Period Reflect the One-Year Patency?

PURPOSE: The left internal mammary artery (LIMA) is the preferred graft for coronary artery bypass grafting, but the reasoning for LIMA occlusion is unclear. We sought to examine whether the wall shear stress (WSS) values of LIMA grafts during the perioperative period reflected the 1-year patency by using combining computational fluid dynamics (CFD) and coronary computed tomography angiography (CCTA) images. METHODS: CCTA was performed in 233 patients with LIMA graft perioperatively and 1 year later from October 2014 to May 2017. LIMA occlusion was detected in six patients at the 1-year follow-up CCTA. Two patients were excluded due to poor imaging quality. The remaining four patients were enrolled as occlusive (OCC) group, and eight patients with patent LIMA were recruited as patent (PAT) group. The WSS values of LIMA during perioperative period were calculated. LIMA graft was artificially divided into three even segments, proximal (pLIMA), middle (mLIMA) and distal (dLIMA) segments. The independent samples t-test and the Student-Newman-Keuls test were used. RESULTS: The WSS values of dLIMA were significantly higher in the PAT group than in the OCC group (4.43 vs. 2.56, p < 0.05). The WSS values of dLIMA in the PAT group were significantly higher than pLIMA, which was absent in the OCC group. CONCLUSIONS: A higher WSS value of the distal segment of LIMA and a higher WSS value of the distal segment compared with the proximal segment of LIMA in the PAT were observed; this tendency might be helpful in predicting the 1-year patency of LIMA.

Evaluation of Effects of TGF-ß1 Inhibition on Gastric Cancer in Nude Mice by Diffusion Kurtosis Imaging and In-Line X-ray Phase Contrast Imaging With Sequential Histology.

BACKGROUND: Accurate and complete response evaluation after treatment is important to implement individualized therapy for gastric cancer. PURPOSE: To investigate the effectiveness of diffusion kurtosis imaging (DKI) and in-line X-ray phase contrast imaging (ILXPCI) in the assessment of the therapeutic efficacy by transforming growth factor beta 1 (TGF-ß1) inhibition. STUDY TYPE: Prospective animal study. ANIMAL MODEL: Thirty nude mice subcutaneous xenotransplantation tumor model of gastric cancer for DKI and 10 peritoneal metastasis nude mice model for ILXPCI. FIELD STRENGTH/SEQUENCE: Examinations before and serially at 7, 14, 21, and 28 days after TGF-ß1 inhibition treatment were performed at 3T MRI including T2 -weighted imaging (T2 WI) and DKI with five b values of 0, 500, 1000, 1500, 2000 s/mm2 ; ILXPCI examinations were performed at 14 days after treatment. ASSESSMENT: DKI parameters (apparent diffusion coefficient [ADC], diffusivity [D] and kurtosis [K]) were calculated by two experienced radiologists after postprocessing. STATISTICAL TESTS: For the differences in all the parameters between the baseline and each timepoint for both the treated and the control mice, the Mann-Whitney test was used. The Spearman correlation test was used to evaluate correlations among the DKI parameters and corresponding pathologic necrosis fraction (NF). RESULTS: ADC, D, and K values were significantly different between the two groups after treatment (P < 0.05). Serial measurements in the treated group showed that the ADC, D, and K values were significantly different at 7, 14, 21, and 28 days compared with baseline (P < 0.05). There were significant correlations between DKI parameters and NF (ADC, r = 0.865, P < 0.001; D, r = 0.802, P < 0.001; K, r = -0.944, P < 0.001). The ILXPCI results in the treated group showed a stronger absorption area than the control group. DATA CONCLUSION: DKI may be used to evaluate the complete course therapeutic effects of gastric cancer induced by TGF-ß1 inhibition, and the ILXPCI technique will improve the tumor microstructure resolution. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2019;49:1553-1564.

Diffusion Kurtosis Imaging Study of Rectal Adenocarcinoma Associated with Histopathologic Prognostic Factors: Preliminary Findings.

Purpose To determine the correlation between diffusion kurtosis imaging (DKI)-derived parameters and prognostic factors for rectal adenocarcinoma. Materials and Methods This study was approved by the local institute review board, and written informed consent was obtained from each patient. Data from 56 patients (median age, 59.5 years; age range, 31-86 years) with rectal adenocarcinoma between April 2014 and September 2015 were involved in this prospective study. DKI (b = 0, 700, 1400, and 2100 sec/mm2) and conventional diffusion-weighted imaging (b = 0, 1000 sec/mm2) were performed. Kurtosis and diffusivity from DKI and apparent diffusion coefficients (ADCs) from diffusion-weighted imaging were measured by two radiologists. Student t test, receiver operating characteristic curves, and Spearman correlation were used for statistical analysis. Results Kurtosis was significantly higher in high-grade than in low-grade rectal adenocarcinomas on the basis of both the number of poorly differentiated clusters (PDCs) (1.136 ± 0.086 vs 0.988 ± 0.060, P < .05) and World Health Organization (WHO) grades (1.103 ± 0.086 [standard deviation] vs 1.034 ± 0.103, P < .05). In PDC grading, the diffusivity and ADC were significantly lower in high-grade tumors than in low-grade tumors (1.187 ± 0.150 vs 1.306 ± 0.129 and 1.020 ± 0.113 vs 1.108 ± 0.097, respectively; P < .05) and showed similar correlations with histologic grades (r = -0.486 and r = -0.406, respectively; P > .05). Compared with both diffusivity and ADC, kurtosis showed significantly higher sensitivity (83.3% [20 of 24] vs 70.8% [17 of 24] and 70.8% [17 of 24], respectively) and specificity (96.8% [31 of 32] vs 84.4% [24 of 32] and 81.3% [26 of 32], respectively). Kurtosis showed a better correlation with PDC grades than with WHO grades (r = 0.797 vs r = 0.293, P < .05). Kurtosis was significantly higher in pN1-2 than in pN0 tumors (1.086 ± 0.103 vs 1.009 ± 0.086, P < .05). Conclusion Kurtosis derived from DKI demonstrated a higher correlation with histologic grades compared with diffusivity and ADC. It also showed better performance in differentiating between high- and low-grade rectal adenocarcinomas and between pN1-2 and pN0 tumors. © RSNA, 2016.

Decreased stage migration rate of early gastric cancer with a new reconstruction algorithm using dual-energy CT images: a preliminary study.

OBJECTIVES: To evaluate the potential value of advanced monoenergetic images (AMEIs) on early gastric cancer (EGC) using dual-energy CT (DECT). METHODS: 31 EGC patients (19 men, 12 women; age range, 38-81 years; mean age, 57.19 years) were retrospectively enrolled in this study. Conventionally reconstructed polyenergetic images (PEIs) at 120 kV and virtual monoenergetic images (MEIs) and AMEIs at six different kiloelectron volt (keV) levels (from 40 to 90 keV) were evaluated from the 100 and Sn 140 kV dual energy image data, respectively. The visibility and stage migration of EGC for all three image data sets were evaluated and statistically analyzed. The objective and subjective image qualities were also evaluated. RESULTS: AMEIs at 40 keV showed the best visibility (80.7 %) and the lowest stage migration (35.5 %) for EGC. The stage migration for AMEIs at 40 keV was significantly lower than that for PEIs (p = 0.026). AMEIs at 40 keV had statistically higher CNR in the arterial and portal phases, gastric-specific diagnostic performance and visual sharpness compared with other AMEIs, MEIs and PEIs (all p < 0.05). CONCLUSIONS: AMEIs at 40 keV with MPR increase the CNR of EGC and thus potentially lower the stage migration of EGC. KEY POINTS: • AMEIs benefits from the recombination of low-keV images and medium energies. • AMEIs could receive better CNR results than MEIs. • AMEIs at 40 keV potentially lower the stage migration of EGC.

Gastric Cancer: Preoperative TNM Staging With Individually Adjusted Computed Tomography Scanning Phase.

OBJECTIVE: The aim of this study was to evaluate test bolus scan technology on preoperative diagnostic performance, vascular enhancement, and artery visualization for gastric cancer. METHODS: The institutional review board approved this study. Fifty-four patients in protocol 1 were resigned to a fixed delay time scan method, and their images were obtained in the late arterial phase (AP) and portal venous phase (PP), with start delays of 40 and 70 seconds, respectively. Fifty-six patients in protocol 2 had undergone the test bolus method first and received the time to peak enhancement of the aorta. Their images were obtained in the AP and PP with start delays in the time to peak enhancement and 20 seconds after the AP, respectively. Two radiologists performed consensus interpretation of the preoperative TNM staging, vascular enhancement, tumor contrast-to-noise ratio (CNR) and artery visualization between the 2 protocols. RESULTS: There is no significant difference in the T, N, and M staging diagnostic accuracy between the protocols (P = 0.41, P > 0.99, and P = 0.34, respectively). For serosa-negative (T1, T2, and T3) tumors, the diagnostic accuracy obtained with protocol 2 was superior to that obtained with protocol 1 (P = 0.04). Protocol 2 was superior for perigastric vessel enhancement (left gastric artery, right gastroepiploic artery, and splenic artery; P < 0.001, P < 0.001, and P = 0.001, respectively). The stomach-to-tumor CNR during the PP of protocol 2 was significantly higher than that during either the AP or PP of protocol 1 (P = 0.004 and P = 0.001, respectively). The mean rankings of the artery visualization were significantly higher with protocol 2 than with protocol 1 (P < 0.001). CONCLUSIONS: The dual-phase scan with test bolus technology could improve the tumor CNR and had high staging accuracy for serosa-negative tumors as well as high perigastric artery enhancement, yielding satisfactory artery visualization for diagnosis.

Spectral CT imaging of myocardial infarction: preliminary animal experience.

OBJECTIVES: To evaluate the capability of spectral CT imaging to detect the different stages and angiogenesis of myocardial infarction (MI). METHODS: MI was surgically induced in 40 rabbits that were evenly divided into four stages of MI: 6 h (6H), 3 days (3D), 7 days (7D) and 14 days (14D). Spectral CT was performed at 10 s, 1 min and 3 min after intravenous contrast medium administration. CD31 immunohistochemistry was used for the microvessel density (MVD) measurement. Iodine concentrations in the myocardium were measured and normalised to the aorta as nIC. The relationships between infarcted myocardial nIC and MVD were analysed. RESULTS: The nIC of infarct myocardium decreased at 10 s and increased in late-phase CT images. There were significant differences between the 6H and other groups (P ( 6H-3D ) = 0.01, P ( 6H-7D ) = 0.01, P ( 6H-14D ) = 0.00). There was a significant difference in the MVD of infarct myocardium between the two groups except in the 7D and 14D groups (P = 0.08). In the 10-s phase, the nIC of infarct myocardium was negatively correlated with MVD (r = -0.54, P = 0.00), whereas in the late phases, there was a positive correlation between them (r = 0.57, P = 0.00 in the 1-min phase, r = 0.48, P = 0.00 in the 3-min phase). CONCLUSION: Spectral CT imaging of the myocardium can be used to evaluate the different stages and angiogenesis of MI.

[Building and application of hospital's electronic film system].

This paper describes the design process and implementation process of electronic film system. The establishment of electronic film system allowed us to aggressively reduce film use and costs and to demonstrate a positive return.

Magnetic Resonance Perfusion-Weighted Imaging in Predicting Hemorrhagic Transformation of Acute Ischemic Stroke: A Retrospective Study.

Hemorrhagic transformation (HT) is one of the common complications in patients with acute ischemic stroke (AIS). This study aims to investigate the value of different thresholds of Tmax generated from perfusion-weighted MR imaging (PWI) and the apparent diffusion coefficient (ADC) value in the prediction of HT in AIS. A total of 156 AIS patients were enrolled in this study, with 55 patients in the HT group and 101 patients in non-HT group. The clinical baseline data and multi-parametric MRI findings were compared between HT and non-HT groups to identify indicators related to HT. The optimal parameters for predicting HT and the corresponding cutoff values were obtained using the receiver operating characteristic curve analysis of the volumes of ADC < 620 × 10-6 mm2/s and Tmax > 6 s, 8 s, and 10 s. The results showed that the volumes of ADC < 620 × 10-6 mm2/s and Tmax > 6 s, 8 s, and 10 s in the HT group were all significantly larger than that in the non-HT group and were all independent risk factors for HT. Early measurement of the volume of Tmax > 10 s had the highest value, with a cutoff lesion volume of 10.5 mL.

CT-Based Radiomic Score: A Risk Stratifier in Far-Advanced Gastric Cancer Patients.

OBJECTIVES: To prolong the survival, the value of a computed tomography-based radiomic score (RS) in stratifying survival and guiding personalized chemotherapy strategies in far-advanced gastric cancer (FGC) was investigated. MATERIALS AND METHODS: This retrospective multicenter study enrolled 283 FGC patients (cT4a/bNxM0-1) from three centers. Patients from one center were randomly divided into the training (n = 166) and internal validation (n = 83) cohorts, whereas the external validation cohort (n = 34) consisted of patients from the two other centers. The RS was calculated for each patient to predict progression-free survival (PFS). Features from the primary tumor and main metastasis (peritoneum, liver, and lymph node) were integrated in the training cohort and then validated for its ability to stratify PFS and overall survival (OS) in the validation cohort. The association between the RS and efficacy of neoadjuvant intraperitoneal and systemic (NIPS) therapy was also explored. RESULTS: The RS demonstrated a favorable prognostic ability to predict PFS in all cohorts (training: C-index 0.83, 95% confidence interval [CI]: 0.788-0.872; internal validation: C-index 0.75, 95% CI: 0.682-0.818; external validation: C-index 0.76, 95% CI: 0.669-0.851; all p < 0.05), as well as an excellent ability to stratify the PFS and OS in both the whole population and metastatic subgroups (p < 0.05). Patients with a low score were more likely to undergo surgery after perioperative chemotherapy (p < 0.05). Furthermore, only high-scoring patients with peritoneal metastasis benefited from NIPS. CONCLUSION: The RS may be an effective risk stratifier for the outcomes of FGC patients and may be used to select patients who can benefit from NIPS therapy.

Robustness of radiomics features of virtual unenhanced and virtual monoenergetic images in dual-energy CT among different imaging platforms and potential role of CT number variability.

OBJECTIVES: To evaluate robustness of dual-energy CT (DECT) radiomics features of virtual unenhanced (VUE) image and virtual monoenergetic image (VMI) among different imaging platforms. METHODS: A phantom with sixteen clinical-relevant densities was scanned on ten DECT platforms with comparable scan parameters. Ninety-four radiomic features were extracted via Pyradiomics from VUE images and VMIs at energy level of 70 keV (VMI70keV). Test-retest repeatability was assessed by Bland-Altman analysis. Inter-platform reproducibility of VUE images and VMI70keV was evaluated by coefficient of variation (CV) and quartile coefficient of dispersion (QCD) among platforms, and by intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC) between platform pairs. The correlation between variability of CT number radiomics reproducibility was estimated. RESULTS: 92.02% and 92.87% of features were repeatable between scan-rescans for VUE images and VMI70keV, respectively. Among platforms, 11.30% and 28.39% features of VUE images, and 15.16% and 28.99% features of VMI70keV were with CV < 10% and QCD < 10%. The average percentages of radiomics features with ICC > 0.90 and CCC > 0.90 between platform pairs were 10.00% and 9.86% in VUE images and 11.23% and 11.23% in VMI70keV. The CT number inter-platform reproducibility using CV and QCD showed negative correlations with percentage of the first-order radiomics features with CV < 10% and QCD < 10%, in both VUE images and VMI70keV (r2 0.3870-0.6178, all p < 0.001). CONCLUSIONS: The majority of DECT radiomics features were non-reproducible. The differences in CT number were considered as an indicator of inter-platform DECT radiomics variation. Critical relevance statement: The majority of radiomics features extracted from the VUE images and the VMI70keV were non-reproducible among platforms, while synchronizing energy levels of VMI to reduce the CT number value variability may be a potential way to mitigate radiomics instability.

[The value of electronic film for improving the quality of hospital services].

In this paper, by describing and comparing different implementations of electronic film combined with the actual application of the electronic film in the imaging department and the clinical departments. We elaborate electronic film for optimizing the imaging department workflow to improve service quality and patient satisfaction and other aspects of value.

Comparison of Computed and Acquired DWI in the Assessment of Rectal Cancer: Image Quality and Preoperative Staging.

Objective: The aim of the study was to evaluate the computed diffusion-weighted images (DWI) in image quality and diagnostic performance of rectal cancer by comparing with the acquired DWI. Methods: A total of 103 consecutive patients with primary rectal cancer were enrolled in this study. All patients underwent two DWI sequences, namely, conventional acquisition with b = 0 and 1,000 s/mm2 (aDWIb1,000) and another with b = 0 and 700 s/mm2 on a 3.0T MR scanner (MAGNETOM Prisma; Siemens Healthcare, Germany). The images (b = 0 and 700 s/mm2) were used to compute the diffusion images with b value of 1,000 s/mm2 (cDWIb1,000). Qualitative and quantitative analysis of both computed and acquired DWI images was performed, namely, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and signal intensity ratio (SIR), and also diagnostic staging performance. Interclass correlation coefficients, weighted κ coefficient, Friedman test, Wilcoxon paired test, and McNemar or Fisher test were used for repeatability and comparison assessment. Results: Compared with the aDWIb1,000 images, the cDWIb1,000 ones exhibited significant higher scores of subjective image quality (all P <0.050). SNR, SIR, and CNR of the cDWIb1,000 images were superior to those of the aDWIb1,000 ones (P <0.001). The overall diagnostic accuracy of computed images was higher than that of the aDWIb1,000 images in T stage (P <0.001), with markedly better sensitivity and specificity in distinguishing T1-2 tumors from the T3-4 ones (P <0.050). Conclusion: cDWIb1,000 images from lower b values might be a useful alternative option and comparable to the acquired DWI, providing better image quality and diagnostic performance in preoperative rectal cancer staging.

Deep learning for differentiating novel coronavirus pneumonia and influenza pneumonia.

BACKGROUND: Chest computed tomography (CT) has been found to have high sensitivity in diagnosing novel coronavirus pneumonia (NCP) at the early stage, giving it an advantage over nucleic acid detection during the current pandemic. In this study, we aimed to develop and validate an integrated deep learning framework on chest CT images for the automatic detection of NCP, focusing particularly on differentiating NCP from influenza pneumonia (IP). METHODS: A total of 148 confirmed NCP patients [80 male; median age, 51.5 years; interquartile range (IQR), 42.5-63.0 years] treated in 4 NCP designated hospitals between January 11, 2020 and February 23, 2020 were retrospectively enrolled as a training cohort, along with 194 confirmed IP patients (112 males; median age, 65.0 years; IQR, 55.0-78.0 years) treated in 5 hospitals from May 2015 to February 2020. An external validation set comprising 57 NCP patients and 50 IP patients from 8 hospitals was also enrolled. Two deep learning schemes (the Trinary scheme and the Plain scheme) were developed and compared using receiver operating characteristic (ROC) curves. RESULTS: Of the NCP lesions, 96.6% were >1 cm and 76.8% were of a density <-500 Hu, indicating them to have less consolidation than IP lesions, which had nodules ranging from 5-10 mm. The Trinary scheme accurately distinguished NCP from IP lesions, with an area under the curve (AUC) of 0.93. For patient-level classification in the external validation set, the Trinary scheme outperformed the Plain scheme (AUC: 0.87 vs. 0.71) and achieved human specialist-level performance. CONCLUSIONS: Our study has potentially provided an accurate tool on chest CT for early diagnosis of NCP with high transferability and showed high efficiency in differentiating between NCP and IP; these findings could help to reduce misdiagnosis and contain the pandemic transmission.

Determining gastric cancer resectability by dynamic MDCT.

PURPOSE: Multi-detector row CT (MDCT) has been widely used to detect primary lesions and to evaluate TNM staging. In this study we evaluated the accuracy of dynamic MDCT in the preoperative determination of the resectability of gastric cancer. METHODS: MDCT was used to image 350 cases of gastric cancer diagnosed by biopsy before surgery. MDCT findings regarding TNM staging and resectability were correlated with surgical and pathological findings. RESULTS: The accuracy of MDCT for staging gastric cancer was high, especially for tumour stage T1 (94.3%), lymph node stage N2 (87.3%), and for predicting distant metastases (>96.6%). When resectability was considered to be the outcome, the total accuracy of MDCT was 87.4%, sensitivity was 89.7% and specificity was 76.7%. Results showed high sensitivity for identifying peritoneal seeding (90.0%) and for predicting liver metastasis (80.0%). CONCLUSION: Dynamic enhanced MDCT is useful for TNM staging of gastric cancers and for predicting tumour respectability preoperatively.

The Performance of a Dual-Energy CT Derived Radiomics Model in Differentiating Serosal Invasion for Advanced Gastric Cancer Patients After Neoadjuvant Chemotherapy: Iodine Map Combined With 120-kV Equivalent Mixed Images.

OBJECTIVES: The aim was to determine whether the dual-energy CT radiomics model derived from an iodine map (IM) has incremental diagnostic value for the model based on 120-kV equivalent mixed images (120 kVp) in preoperative restaging of serosal invasion with locally advanced gastric cancer (LAGC) after neoadjuvant chemotherapy (NAC). METHODS: A total of 155 patients (110 in the training cohort and 45 in the testing cohort) with LAGC who had standard NAC before surgery were retrospectively enrolled. All CT images were analyzed by two radiologists for manual classification. Volumes of interests (VOIs) were delineated semi-automatically, and 1,226 radiomics features were extracted from every segmented lesion in both IM and 120 kVp images, respectively. Spearman's correlation analysis and the least absolute shrinkage and selection operator (LASSO) penalized logistic regression were implemented for filtering unstable and redundant features and screening out vital features. Two predictive models (120 kVp and IM-120 kVp) based on 120 kVp selected features only and 120 kVp combined with IM selected features were established by multivariate logistic regression analysis. We then build a combination model (ComModel) developed with IM-120 kVp signature and ycT. The performance of these three models and manual classification were evaluated and compared. RESULT: Three radiomics models showed great predictive accuracy and performance in both the training and testing cohorts (ComModel: AUC: training, 0.953, testing, 0.914; IM-120 kVp: AUC: training, 0.953, testing, 0.879; 120 kVp: AUC: training, 0.940, testing, 0.831). All these models showed higher diagnostic accuracy (ComModel: 88.9%, IM-120 kVp: 84.4%, 120 kVp: 80.0%) than manual classification (68.9%) in the testing group. ComModel and IM-120 kVp model had better performances than manual classification both in the training (both p<0.001) and testing cohorts (p<0.001 and p=0.034, respectively). CONCLUSIONS: Dual-energy CT-based radiomics models demonstrated convincible diagnostic performance in differentiating serosal invasion in preoperative restaging for LAGC. The radiomics features derived from IM showed great potential for improving the diagnostic capability.

Value of multidetector-row computed tomography in the preoperative T and N staging of gastric carcinoma: a large-scale Chinese study.

OBJECTIVES: To investigate the value of multidetector-row computed tomography (MDCT) in the preoperative T and N staging of gastric carcinoma and to further investigate the clinicopathological factors affecting the diagnostic accuracy. METHODS: Seven hundred ninety gastric carcinoma patients underwent preoperative MDCT examination. The results of MDCT were compared with surgical and pathological findings. RESULTS: Early gastric carcinoma patients whose primary tumor was detected by MDCT had higher incidence of lymph node metastasis, larger tumor size, and deeper invasion. The overall accuracy of MDCT in determining T stage of gastric carcinoma was 73.80% (T1 45.93%, T2 53.03%, T3 86.49%, and T4 85.79%). The overall accuracy of MDCT in preoperative N staging was 75.22% (N0 76.17%, N1 68.81%, and N2 80.63%). The overall diagnostic sensitivity, specificity, and accuracy of MDCT for determining lymph node metastasis was 86.26%, 76.17%, and 82.09%, respectively. Multivariate analysis showed that the diagnostic sensitivity of MDCT in determining lymph node metastasis related with tumor size, N stage, and number of metastatic lymph nodes. CONCLUSIONS: The clinical value of MDCT in the preoperative T and N staging of gastric carcinoma is relatively high. MDCT can be the first choice for the preoperative evaluation of patients with gastric carcinoma.