scholarly journals A Quantitative Lung Computed Tomography Image Feature for Multi-Center Severity Assessment of COVID-19

2020 ◽  
Author(s):  
Biswajoy Ghosh ◽  
Nikhil Kumar ◽  
Nitisha Singh ◽  
Anup K. Sadhu ◽  
Nirmalya Ghosh ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Texture Features ◽  
High Sensitivity ◽  
Image Feature ◽  
P Value ◽  
Severity Assessment ◽  
Machine Learning Classification ◽  
Therapeutic Decisions ◽  
Computed Tomography Image ◽  
Sensitivity Specificity

AbstractThe COVID-19 pandemic has affected millions and congested healthcare systems globally. Hence an objective severity assessment is crucial in making therapeutic decisions judiciously. Computed Tomography (CT)-scans can provide demarcating features to identify severity of pneumonia —commonly associated with COVID-19—in the affected lungs. Here, a quantitative severity assessing chest CT image feature is demonstrated for COVID-19 patients. We incorporated 509 CT images from 101 diagnosed and expert-annotated cases (age 20-90, 60% males) in the study collected from a multi-center Italian database1 sourced from 41 radio-diagnostic centers. Lesions in the form of opacifications, crazy-paving patterns, and consolidations were segmented. The severity determining feature —Lnorm was quantified and established to be statistically distinct for the three —mild, moderate, and severe classes (p-value<0.0001). The thresholds of Lnorm for a 3-class classification were determined based on the optimum sensitivity/specificity combination from Receiver Operating Characteristic (ROC) analyses. The feature Lnorm classified the cases in the three severity categories with 86.88% accuracy. ‘Substantial’ to ‘almost-perfect’ intra-rater and inter-rater agreements were achieved involving expert (manual segmentation) and non-expert (graph-cut and deep-learning based segmentation) labels (κ-score 0.79-0.97). We trained several machine learning classification models and showed Lnorm alone has a superior diagnostic accuracy over standard image intensity and texture features. Classification accuracy was further increased when Lnorm was used for 2-class classification i.e. to delineate the severe cases from non-severe ones with a high sensitivity (97.7%), and specificity (97.49%). Therefore, key highlights of the COVID-19 severity assessment feature are high accuracy, low dependency on expert availability, and wide utility across different CT-imaging centers.

scholarly journals Computed Tomography Image Feature under Intelligent Algorithms in Diagnosing the Effect of Humanized Nursing on Neuroendocrine Hormones in Patients with Primary Liver Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xiujie Wang ◽  
Lin Liu ◽  
Na Ma ◽  
Xinxin Zhao
Keyword(s):  
Computed Tomography ◽  
Liver Cancer ◽  
Primary Liver Cancer ◽  
Ct Images ◽  
Image Feature ◽  
Control Group ◽  
Intelligent Algorithms ◽  
Residual Coding ◽  
Computed Tomography Image ◽  
Experimental Group

This study was to explore the application value of computed tomography (CT) images processed by intelligent algorithm denoising in the evaluation of humanized nursing in postoperative neuroendocrine hormone changes in patients with primary liver cancer (PLC). In this study, a simple-structured recursive residual coding and decoding (RRCD) algorithm was constructed on the basis of residual network, which can effectively remove artifacts and noise in CT images and can also restore image details and lesion features well. In addition, 60 postoperative patients with primary liver cancer were collected and divided into routine nursing control group (30 cases) and humanized nursing experimental group (30 cases). After a period of nursing, CT images based on intelligent algorithms were evaluated by determining the hormone content. The results showed that the focal necrosis rate (FNR) of the experimental group was 6%. The adrenocorticotropic hormone (ACTH) levels of 6 and 15 days after admission (T3 and T4) were 41.25 ± 3.81 pg/mL and 19.55 ± 1.72 pg/mL, respectively. The cortisol levels of days 6, 15, and 30 after admission (T3, T4, and T5) were 424.86 ± 16.82 nmol/L, 277.98 ± 14.36 nmol/L, and 241.53 ± 13.27 nmol/L, respectively. Estradiol levels were 53.48 ± 11.19 pg/mL, 41.64 ± 9.28 pg/mL, and 30.59 ± 8.16 pg/mL, respectively. Testosterone levels were 2.18 ± 1.14 ng/mL, 1.78 ± 1.03 ng/mL, and 1.42 ± 0.69 ng/mL, respectively. Self-Rating Anxiety Scale (SAS) scores were 40.24 ± 5.81 points, 36.55 ± 5.02 points, and 32.53 ± 4.8 points, respectively. There were 24 cases, 27 cases, 23 cases, and 21 patients who followed no smoking and drinking, taking medication on time, diet control, and self-monitoring. The scores of physical function, self-cognition, emotional function, and social function were 62.59 ± 6.82 points, 69.26 ± 8.14 points, 73.89 ± 6.35 points, and 66.88 ± 7.04 points, which were better than those of the control group in all aspects ( P < 0.05 ). In short, the humanized nursing course can enhance the compliance of the patients after the surgery, improve the quality of life, and inhibit the anxiety and depression of the patients, so it showed a positive effect on the neuroendocrine hormones and the prognosis of the patients.

scholarly journals RiIG Modeled WCP Image-Based CNN Architecture and Feature-Based Approach in Breast Tumor Classification from B-Mode Ultrasound

2021 ◽  
Vol 11 (24) ◽  
pp. 12138
Author(s):  
Shahriar Mahmud Kabir ◽  
Mohammed I. H. Bhuiyan ◽  
Md Sayed Tanveer ◽  
ASM Shihavuddin
Keyword(s):  
Breast Tumor ◽  
Texture Features ◽  
Classification Performance ◽  
Tumor Classification ◽  
P Value ◽  
Ultrasound Images ◽  
Custom Made ◽  
Feature Based ◽  
Sensitivity Specificity ◽  
Breast Tumor Classification

This study presents two new approaches based on Weighted Contourlet Parametric (WCP) images for the classification of breast tumors from B-mode ultrasound images. The Rician Inverse Gaussian (RiIG) distribution is considered for modeling the statistics of ultrasound images in the Contourlet transform domain. The WCP images are obtained by weighting the RiIG modeled Contourlet sub-band coefficient images. In the feature-based approach, various geometrical, statistical, and texture features are shown to have low ANOVA p-value, thus indicating a good capacity for class discrimination. Using three publicly available datasets (Mendeley, UDIAT, and BUSI), it is shown that the classical feature-based approach can yield more than 97% accuracy across the datasets for breast tumor classification using WCP images while the custom-made convolutional neural network (CNN) can deliver more than 98% accuracy, sensitivity, specificity, NPV, and PPV values utilizing the same WCP images. Both methods provide superior classification performance, better than those of several existing techniques on the same datasets.

scholarly journals Evaluation of the triangular fibrocartilage: comparison of two-compartment wrist CT arthrography using the distal radioulnar and radiocarpal joints and unicompartment wrist CT arthrography using the radiocarpal joint

2019 ◽  
Vol 92 (1102) ◽  
pp. 20190298 ◽  
Author(s):  
Sujin Kim ◽  
Guen Young Lee ◽  
Jae Sung Lee
Keyword(s):  
Young Patients ◽  
High Sensitivity ◽  
P Value ◽  
Full Thickness ◽  
Ct Arthrography ◽  
Exact Test ◽  
Central Disc ◽  
Radiocarpal Joint ◽  
Triangular Fibrocartilage ◽  
Sensitivity Specificity

Objective: To compare the diagnostic performance of two-compartment wrist CT arthrography of the distal radioulnar and radiocarpal joints and unicompartment wrist CT arthrography of the radiocarpal joint in depiction of the triangular fibrocartilage tear. Methods: From January 2016 to December 2017, two-compartment CT arthrography of 74 consecutive patients (36 females, 38 males; mean age, 37.2 years) and unicompartment CT arthrography of 51 consecutive patients (18 females, 33 males; mean age, 40.1 years) were obtained. All CT arthrography images were independently and blindly evaluated by two radiologists for the presence of the triangular fibrocartilage tear by grade (partial or full thickness) per its locations: central disc proper, central-peripheral junction, proximal and distal laminae of its ulnar attachment. Fisher’s exact test was used for a statistical analysis, and a p-value less than 0.05 was considered as significant. The arthroscopic findings of 47 patients (34 patients with two-compartment CT arthrography and 13 patients with unicompartment CT arthrography) were evaluated for calculating sensitivity, specificity, and accuracy. Results: All partial and full thickness triangular fibrocartilage tears were identified more commonly by their location except for distal laminae on two-compartment CT arthrography than were unicompartment CT arthrography (p = 0.001–0.022). Two-compartment CT arthrography had high sensitivity (90.9–100%) and low specificity (33.3–76.5%) for detecting central disc proper and proximal lamina tears, comparing with unicompartment CT arthrography. Conclusion: Two-compartment wrist CT arthrography is more helpful for detecting triangular fibrocartilage tears than unicompartment wrist CT arthrography. Advances in knowledge: It could be important to evaluate the ulnar foveal insertion of the TFCC in clinical practice, which plays the most important role in DRUJ instability and ulnar-sided wrist pain. Two-compartment wrist CTA of the DRUJ and RCJ could improve diagnostic sensitivity in the TFC tear in terms of its location and torn degree over that of unicompartment wrist CTA of the RCJ. Two-compartment wrist CTA of the DRUJ and RCJ may be recommended as a diagnostic imaging, rather than unicompartment wrist CTA of the RCJ, when peripheral foveal tear of TFC is suspected, especially in young patients.

Evaluation of radiomics as a predictor of tumor hypoxia and response to anti-PD-1 mab treatment (IO) in recurrent/metastatic HNSCC patients (R/M).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 6045-6045
Author(s):  
Dan Paul Zandberg ◽  
Serafettin Zenkin ◽  
Murat AK ◽  
Priyadarshini Mamindla ◽  
Vishal Peddagangireddy ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Cross Validation ◽  
Tumor Hypoxia ◽  
Texture Features ◽  
Classification Model ◽  
P Value ◽  
Patient Cohort ◽  
Volume Of Interest ◽  
Feature Selection Approach ◽  
Sensitivity Specificity

6045 Background: There is a great need for non-invasive predictors of the tumor microenvironment and the efficacy of anti-PD-1 mAb treatment (IO) in R/M HNSCC patients. We previously showed that lower tumor hypoxia was associated with increased efficacy with IO ( Journal of Clinical Oncol. 38, no. 15_suppl (May 20, 2020) 6546) and now we evaluate the predictive value of radiomics in this same patient cohort. Methods: We studied radiomic signatures in a cohort of 36 patients with R/M HNSCC treated with IO. Treatment response was evaluated using RECIST 1.1. Patients were categorized as: Responders (R) ie CR, PR, SD and non-Responders (NR) i.e PD. As per our previous analysis (ref above) hypoxia was evaluated on archival FFPE samples via immunofluorescent imaging and defined by the ratio of percent area (% CAIX) / the mean intensity (Int) of carbonic anhydrase IX in tumor (%CAIX/Int). ImageJ software was used to determine %CAIX and Int. Feature extraction was performed on the pre-immunotherapy baseline CT scans. The lesions were segmented using 3D slicer v4.10.2 to create a volume of interest (VOI) for radiomic texture analysis (TA). A total of 400 features (10 histogram-based and 390 second-order texture features) were calculated from each extracted volume of interest (VOI). Radiomic features were obtained using a feature selection approach based on Least Absolute Shrinkage and Selection Operator (LASSO). Selected features were used to build a classification model, using XGboost, for prediction of tumor response to immunotherapy. Cross-validation was performed using the Leave One Out Cross Validation (LOOCV) approach for the XGBoost method to evaluate the robustness of the estimates and calculated accuracy, sensitivity, specificity and p-value. Results: Our patient cohort had a median age of 59, 69% male, 58% smokers. 61% received IO for platinum failure, 39% frontline. Primary site included 39% OC, 22% OPC (38% HPV positive), 17% Larynx, 5% hypopharynx, and 17% other. Radiomics applied to the primary HNSCC tumor highly predicted tumor hypoxia status with a sensitivity, specificity, and accuracy of 78%, 83%, and 81%, respectively, p = 0.0001. To predict response, we applied radiomics to both the primary HNSCC tumor and pathological lymph nodes; radiomics was also able to predict whether a patient would be a responder (N = 8) versus a non-responder (N = 28) to IO based on the pre-immunotherapy baseline CT scan. The sensitivity, specificity, and accuracy were 93%, 88%, and 92%, respectively, p = 0.02. Conclusions: Even in a small cohort, radiomics could predict response to IO and tumor hypoxia in R/M HNSCC patients. To our knowledge this is the first evaluation of this kind in this patient population. Further evaluation of radiomics as a predictor of efficacy with IO and the tumor microenvironment is warranted.

scholarly journals Accuracy of the hematological scoring system (HSS) for the diagnosis of neonatal sepsis in Tertiary Care Hospital.

2020 ◽  
Vol 27 (04) ◽  
pp. 742-745
Author(s):  
Muhammad Asghar Ali ◽  
Ali Hammad ◽  
Hafiz Muhammad Anwar
Keyword(s):  
Neonatal Sepsis ◽  
Scoring System ◽  
Tertiary Care ◽  
High Sensitivity ◽  
P Value ◽  
Care Hospital ◽  
Predictive Values ◽  
Early Diagnose ◽  
Sensitivity Specificity ◽  
Culture Positive

Objectives: Neonatal sepsis is a known and significant contributor to newborn morbidity and mortality. We conducted this study to find out the efficiency of hematological scoring system (HSS) in predicting neonatal sepsis. Study Design: Prospective study. Setting: Neonatology Unit of Civil Hospital, Bahawalpur. Period: 1st July 2018 to 31st December 2018. Materials & Methods: A total of 100 neonates having high probability of sepsis were admitted and evaluated in NICU, Institution’s pathological lab was the center for all the workups. Sensitivity, specificity, positive predictive values (PPVs) along with negative predictive values (NPVs) were calculated for different study parameters. P value < 0.05 was considered as significant. Results: Amongst a total of 100 neonates, 62 (62.0%) were males and 38 (38.0%) females. There were 32 (32.0%) preterm while 68 (68.0%) term neonates. Culture positive cases were found to be 33 (33.0%) whereas CRP was noted reactive in 62 (62.0%) cases. Neonatal age as preterm, culture positive neonates (p < 0.001) as well as CRP as reactive were found to be significantly associated with HSS > 5. Immature to total neutrophil ratio (I:T) as well as Immature to mature neutrophil ratio (I:M) had the highest sensitivity and specificity. Conclusion: HSS is a simple to use and efficient method that can be used to early diagnose and treat cases of neonatal sepsis. HSS has a high sensitivity as well specificity as high scores of HSS highlight sepsis.

TO SEPARATELY ASSESS THE DIAGNOSTIC POTENTIAL OF TVS & MRI IN THE TERMS OF SENSITIVITY AND SPECIFICITY BY CORRELATING THE IMAGING FINDINGS WITH HISTOPATHOLOGY

2020 ◽  
Vol 4 (6) ◽  
Author(s):  
Suraj Mathur
Keyword(s):  
Transvaginal Ultrasound ◽  
High Sensitivity ◽  
Imaging Evaluation ◽  
Medical College ◽  
Conventional Mri ◽  
Diagnostic Potential ◽  
Adc Mapping ◽  
Malignant Lesions ◽  
Sensitivity Specificity

This prospective study was done in the Department of Radio diagnosis Govt. Medical College, Kozhikode. A total of 65 patients who were referred to our department with clinical suspicion of endometrial lesions and incidentally detected endometrial lesions on ultrasonography underwent transvaginal ultrasound and subsequent Imaging evaluation of pelvis MRI has very high sensitivity (95%) and specificity (98%) and is almost as accurate (97%) as histopathology in differentiating benign from malignant lesions. Addition of DWI with ADC mapping to conventional MRI increases its accuracy even more. However there is inherent limitation to MRI in detecting carcinoma in situ and micrometastasis. Keywords: TVS, MRI, Sensitivity, Specificity, Histopathology.

Noninvasive Evaluation of Coronary Artery Bypass Grafts with 16-Slice Multidetector Computed Tomography

2012 ◽  
Vol 15 (1) ◽  
pp. 12 ◽  
Author(s):  
Levent Sahiner ◽  
Ali Oto ◽  
Kudret Aytemir ◽  
Tuncay Hazirolan ◽  
Musturay Karcaaltincaba ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Coronary Artery ◽  
Diagnostic Accuracy ◽  
Multidetector Computed Tomography ◽  
Coronary Artery Bypass ◽  
Predictive Value ◽  
Artery Bypass ◽  
Time Interval ◽  
Mdct Angiography ◽  
Sensitivity Specificity

<p><b>Background:</b> The aim of this study was to investigate the diagnostic accuracy of 16-slice multislice, multidetector computed tomography (MDCT) angiography for the evaluation of grafts in patients with coronary artery bypass grafting (CABG).</p><p><b>Methods:</b> Fifty-eight consecutive patients with CABG who underwent both MDCT and conventional invasive coronary angiography were included. The median time interval between the 2 procedures was 10 days (range, 1-32 days). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of MDCT for the detection of occluded grafts were calculated. The accuracy of MDCT angiography for detecting significant stenoses in patent grafts and the evaluability of proximal and distal anastomoses were also investigated.</p><p><b>Results:</b> Optimal diagnostic images could not be obtained for only 3 (2%) of 153 grafts. Evaluation of the remaining 150 grafts revealed values for sensitivity, specificity, PPV, NPV, and diagnostic accuracy of the MDCT angiography procedure for the diagnosis of occluded grafts of 87%, 97%, 94%, 93%, and 92%, respectively. All of the proximal anastomoses were optimally visualized. In 4 (8%) of 50 patent arterial grafts, however, the distal anastomotic region could not be evaluated because of motion and surgical-clip artifacts. The accuracy of MDCT angiography for the detection of significant stenotic lesions was relatively low (the sensitivity, specificity, PPV, and NPV were 67%, 98%, 50%, and 99%, respectively). The number of significant lesions was insufficient to reach a reliable conclusion, however.</p><p><b>Conclusion:</b> Our study showed that MDCT angiography with 16-slice systems has acceptable diagnostic performance for the evaluation of coronary artery bypass graft patency.</p>

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