scholarly journals Calcium Identification and Scoring Based on Echocardiography. An Exploratory Study on Aortic Valve Stenosis

2021 ◽  
Vol 11 (7) ◽  
pp. 598
Author(s):  
Luis B. Elvas ◽  
Ana G. Almeida ◽  
Luís Rosario ◽  
Miguel Sales Dias ◽  
João C. Ferreira
Keyword(s):  
Aortic Valve ◽  
Ct Scan ◽  
Pearson Correlation ◽  
Region Of Interest ◽  
Expert Assessment ◽  
Image Binarization ◽  
Real Patient ◽  
Margin Of Error ◽  
Pixel Value ◽  
Echocardiographic Images

Currently, an echocardiography expert is needed to identify calcium in the aortic valve, and a cardiac CT-Scan image is needed for calcium quantification. When performing a CT-scan, the patient is subject to radiation, and therefore the number of CT-scans that can be performed should be limited, restricting the patient’s monitoring. Computer Vision (CV) has opened new opportunities for improved efficiency when extracting knowledge from an image. Applying CV techniques on echocardiography imaging may reduce the medical workload for identifying the calcium and quantifying it, helping doctors to maintain a better tracking of their patients. In our approach, a simple technique to identify and extract the calcium pixel count from echocardiography imaging, was developed by using CV. Based on anonymized real patient echocardiographic images, this approach enables semi-automatic calcium identification. As the brightness of echocardiography images (with the highest intensity corresponding to calcium) vary depending on the acquisition settings, echocardiographic adaptive image binarization has been performed. Given that blood maintains the same intensity on echocardiographic images—being always the darker region—blood areas in the image were used to create an adaptive threshold for binarization. After binarization, the region of interest (ROI) with calcium, was interactively selected by an echocardiography expert and extracted, allowing us to compute a calcium pixel count, corresponding to the spatial amount of calcium. The results obtained from these experiments are encouraging. With this technique, from echocardiographic images collected for the same patient with different acquisition settings and different brightness, obtaining a calcium pixel count, where pixel values show an absolute pixel value margin of error of 3 (on a scale from 0 to 255), achieving a Pearson Correlation of 0.92 indicating a strong correlation with the human expert assessment of calcium area for the same images.

Abstract 12809: Pre-Procedural Aortic Valve Area Predicts Degree of Thrombocytopenia Following Trans-Catheter Aortic Valve Implantation

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Elizabeth Retzer ◽  
Corey Tabit ◽  
Jonathan Paul ◽  
Sandeep Nathan ◽  
Janet Friant ◽  
...  
Keyword(s):  
Aortic Valve ◽  
Antiplatelet Therapy ◽  
Pearson Correlation ◽  
P Value ◽  
Aortic Valve Area ◽  
Surgical Aortic Valve Replacement ◽  
Percutaneous Balloon ◽  
Aortic Valve Implantation ◽  
Valve Implantation ◽  
Valve Area

Introduction: Thrombocytopenia (TP) has been described following percutaneous balloon aortic valvuloplasty (BAV) and surgical aortic valve replacement (SAVR), but only recently noted following trans-catheter aortic valve implantation (TAVI). While transient, the TP may be severe leading to increased bleeding. Methods: We conducted a retrospective analysis of all patients undergoing TAVI with either a 23mm or 26mm Edwards Sapien valve (Edward Lifesciences, Irvine, California) at our institution.. The effect of multiple independent variables on % platelet change after TAVI were analyzed using paired and unpaired T-tests, two-way ANOVA, and Chi-square tests as appropriate. Platelet % change was correlated with aortic valve area using Pearson correlation. A p-value of <0.05 was considered statistically significant. Results: A total of 33 patients (54.5% male, median age 79.3, mean valve area 0.76 cm2) were included in this analysis. The degree of aortic valve stenosis significantly correlated with post-procedural TP severity (Figure 1). The degree of TP post TAVI was found to be significantly lower in those patients who received BAV prior to their TAVI procedure (p < 0.01). Conclusions: Post-TAVI TP correlates with the degree of pre-procedure aortic stenosis. Given the need for peri-procedural anticoagulation and post-procedural dual antiplatelet therapy, this finding can help identify patients at risk for symptomatic TP and may help guide post procedure antiplatelet therapy. Further studies are needed to elucidate the underlying mechanism.

scholarly journals Incidental abnormal CT scan findings during transcatheter aortic valve implantation assessment: incidence and implications

Open Heart ◽  
2018 ◽  
Vol 5 (2) ◽  
pp. e000855 ◽  
Author(s):  
Akshay Patel ◽  
Kajan Mahendran ◽  
Michael Collins ◽  
Mahmoud Abdelaziz ◽  
Saib Khogali ◽  
...  
Keyword(s):  
Aortic Valve ◽  
Ct Scan ◽  
Clinical Significance ◽  
Transcatheter Aortic Valve Implantation ◽  
Incidental Findings ◽  
Mortality Data ◽  
Transcatheter Aortic Valve ◽  
Significant Difference ◽  
Aortic Valve Implantation ◽  
Valve Implantation

ObjectivesThe aim of this retrospective series is to describe the prevalence and clinical significance of the incidental findings found during pre–transcatheter aortic valve implantation (TAVI) work-up and to ascertain the clinical course of such patients.MethodsConsecutive patients undergoing TAVI from 2013 to 2015 where a TAVI CT assessment was performed (n=138) were included in the study. All incidental findings that were not expected from the patient’s history were discussed at the TAVI multidisciplinary meeting in order to ascertain the clinical significance of said findings and whether they would alter the proposed course of treatment. Mortality data were determined by careful retrospective case note and follow-up appointment analysis.ResultsSeventy-eight patients (57%) were found to have incidental findings on pre-TAVI CT scan. The majority of patients had benign pathology with high incidence in particular of diverticular disease, pleural effusions, gallstones, hiatus hernia and degenerative spinal disease. Vascular pathology such as superior mesenteric, renal and iliac artery stenoses and abdominal aortic aneurysm was detected in seven patients. In terms of long-term mortality data, we found no significant difference between those with incidental findings and those without (p=0.48). Survival as assessed by Kaplan-Meier analysis showed no significant difference between those with and without incidental abnormal CT scan findings (p=0.98).ConclusionsIncidental findings with potential for malignancy are common in an elderly, comorbid population. Ultimately, clinical correlation and prognosis must be swiftly ascertained in order to streamline the patients down the appropriate management pathway while avoiding unnecessary delay for treatment of their aortic stenosis.

scholarly journals The deadly “bulging balloon” within the mediastinum: a case of a giant aortic root aneurysm in a young patient with Marfan syndrome

2020 ◽  
Author(s):  
JIAYU SHEN ◽  
Changping Gan ◽  
R.D.T. Rajaguru ◽  
Dou Yuan ◽  
ZHENGHUA XIAO
Keyword(s):  
Decision Making ◽  
Aortic Valve ◽  
Ct Scan ◽  
Young Patient ◽  
Marfan Syndrome ◽  
Aortic Root ◽  
Treatment Decision ◽  
Decision Making Process ◽  
Aortic Root Aneurysm ◽  
Treatment Decision Making

Abstract Introduction: Marfan syndrome (MFS) is a common heritable connective tissue disease involving multiple organs. Even though the clinical manifestations of MFS can be various, aortic root aneurysm is estimated as one of the most serious complications. We herein describe an individualized treatment decision-making process for a 23-year-old male with MFS, suffering from a giant but stable aortic root aneurysm which is extremely rare at his age. Case: The patient, a 23-year-old male with a family history of MFS, presented to our cardiovascular department because of progressive exertional chest distress, fatigue and occasional precordial pain. Physical examinations revealed six-foot-three inches of height, high myopia, and a diastolic murmur at the aortic valve area. Laboratory examinations for systemic vasculitis and infectious diseases were negative. The transthoracic echocardiography (TTE) and enhanced thoracic computed tomography (CT) scan revealed the existence of a giant aortic root aneurysm (125.1 mm in short-axis), severe aortic valve regurgitation, cardiac dilatation (LV; 99 mm in diastolic diameter) and a poor ejection fraction (EF; 18%). Considering the risk of rupture or dissection of the dilated aortic root, we successfully performed the Bentall procedure based on the intraoperative exploration results. Postoperative thoracic CT scan revealed a normal sized reconstructed aortic root, and the patient was discharged uneventfully 7 days later. Conclusion It is extremely rare to report such a giant aortic root aneurysm in a young patient. In the treatment decision-making process, the patient’s specific situation should be taken into consideration. The composite replacement of the aortic valve and ascending aorta should be performed if the patient is not suitable for valve-sparing operation.

The Reliability of Measuring Early Brain Edema with Computed Tomography

2021 ◽  
Vol 17 ◽  
Author(s):  
Yi-Fang Fan ◽  
Mi Shen ◽  
Xin-Xin Wang ◽  
Xiao-Yuan Liu ◽  
Yu-Ming Peng ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Brain Edema ◽  
Early Stage ◽  
Pearson Correlation ◽  
Intraclass Correlation ◽  
Region Of Interest ◽  
High Grade Glioma ◽  
High Grade ◽  
Magnetic Resonance Imaging Mri ◽  
Ct And Mri

Background: Postoperative brain edema is a common complication in patients with high-grade glioma after craniotomy. Both computed tomography (CT) and Magnetic Resonance Imaging (MRI) are applied to diagnose brain edema. Usually, MRI is considered to be better than CT for identifying brain edema. However, MRI is not generally applied in diagnosing acute cerebral edema in the early postoperative stage. Whether CT is reliable in detecting postoperative brain edema in the early stage is unknown. Objective: To investigate the agreement and correlation between CT and MRI for measuring early postoperative brain edema. Methods: Patients with high-grade glioma who underwent craniotomy in Beijing Tiantan hospital from January 2017 to October 2018 were retrospectively analyzed. The region of interest and operative cavity were manually outlined, and the volume of postoperative brain edema was measured on CT and MRI. Pearson correlation testing and the intraclass correlation coefficient (ICC) were used to evaluate the association and agreement between CT and MRI for detecting the volume of postoperative brain edema. Results: Twenty patients were included in this study. The interrater agreement was perfect for detecting brain edema (CT: κ=1, ICC=0.977, P<0.001; MRI: κ=0.866, ICC=0.963, P<0.001). A significant positive correlation and excellent consistency between CT and MRI were found for measuring the volume of brain edema (rater 1: r=0.97, ICC=0.934, P<0.001; rater 2: r=0.97, ICC=0.957, P<0.001). Conclusion: Substantial comparability between CT and MRI is demonstrated for detecting postoperative brain edema. It is reliable to use CT for measuring brain edema volume in the early stage after surgery.

Abstract 11653: The Qualitative Grading of Aortic Valve Calcification in Severe Aortic Stenosis is Weakly Associated With Aortic Valve Weight and is Gender Dependent

Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Dragos Alexandru ◽  
Florentina Petillo ◽  
Simcha Pollack ◽  
Nathaniel Reichek ◽  
Eddy Barasch
Keyword(s):  
Aortic Valve ◽  
Aortic Stenosis ◽  
Severe Aortic Stenosis ◽  
Pearson Correlation ◽  
Calcium Score ◽  
Aortic Valve Calcification ◽  
Test Analysis ◽  
Valve Calcification ◽  
Exact Test ◽  
The Difference

Background: In severe aortic stenosis (AS), qualitative estimation of aortic valve calcification (AVC) burden by echocardiography has diagnostic and prognostic value. Hypothesis: there is a weak association between a qualitative calcium score (QCS) by TEE and AV weight in severe AS. Methods: Between 2010-2014, of 719 pts who underwent surgical AVR for isolated severe AS, QCS was feasible in 483 (67%): mean age 76.7 ± 9.5 yrs, 59% males, EF 56 ±12%, AVAi 0.35 ±0.09 cm2/m2, AVW 2.45 ± 0.09 g, QCS 3.5± 0.57, 11% bicuspid valves . AVC was determined using short- and long-axis views and graded as mild (1) localized, small, nondense calcifications to severe (4) extensive thickening and calcification of all cusps. TEEs were done on the day of surgery and excised valves were weighed. Independent t-test, Fisher’s exact test, analysis of variance, and Pearson correlation were done as appropriate. Results: Intraclass correlations for intra and interobserver variability were 0.76 and 0.53 , respectively.The association between indices of AS severity and AVC burden, is stronger for AVW than for QCS (table).19 pts had QCS = 2, 183 = 3 and 280 = 4. A QCS of 2 to 4 corresponded to an AVW of 1 to 6 g. The correlation between QCS and AVW was 0.11, p=.01, and 0.09, p =.04 when controlling for age, sex and BSA. QCS-AVW association was gender dependent : for females (196), who had a lower severity of stenosis, r=0.23, p=0.001, for males (286), r=0.02, p=.68 with p =.02 for the difference. Conclusions: 1. In severe AS, QCS by TEE has limited reliability with no relationship with AVW in males and a weak one in females. 2. The utilization of QCS in severe AS even when employing TEE is weakly associated with total AVC burden and should probably be replaced by quantitative objective non- echocardiographic methods.

Abstract 14101: A Correction Score for Comparison of Aortic Calcification in Post-contrast and Non-contrast Measurements From Computed Tomography Scans

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Steven R Horbal ◽  
Edward Brown ◽  
Brian A Derstine ◽  
Peng Zhang ◽  
Andrea H Rossman ◽  
...  
Keyword(s):  
Pearson Correlation ◽  
Aortic Calcification ◽  
University Of Michigan ◽  
Variance Inflation Factor ◽  
Post Contrast ◽  
Abdominal Aortic ◽  
Pixel Value ◽  
Inflation Factor ◽  
The University ◽  
The Relationship

Introduction: Aortic calcification can be utilized to assess cardiovascular risk. While contrast is useful for vascular enhancement in diagnostic imaging, enhancement creates heterogeneity between post and non-contrast scans and limits their direct comparability. Hypothesis: We hypothesized that post and non-contrast aortic calcification measures will correlate, and a correction score can be developed for statistical comparability. Methods: Retrospective CT-scans were obtained from the University of Michigan. Participants (N=330) received abdominal scans with and without contrast enhancement within 120 calendar days. Analytic Morphomics was used to obtain vertebral-indexed measurements of aortic calcium area, and aortic wall obfuscation percentage. Calcification was specifically identified as regions with a given morphology and pixel value five standard deviations above the defined central lumen zone. Pearson correlation and multiple linear regression were used to explain the relationship between aortic measurements with and without contrast. Regressions include calcification percent (Model 1), and area (Model 2). Independent variables were non-contrast measurements and dependent variables were contrast measurements, age, and sex. Results: Correlations of calcification percent ranged from 0.86 at T11 and 0.94 and L2. Correlations of calcification area ranged from 0.66 at T12 to 0.84 at L3. In Model 1, for every percent increase in post-contrast calcification, non-contrast calcification percent increased by 11% (β=1.11, p <0.001, R2=0.85). In Model 2, for every mm2 increase in post-contrast calcification area, non-contrast calcification area increased by 0.45 mm2 (β=1.45, p <0.001, R2=0.69). Variance inflation factor for Model 1 was 1.08 and 1.07 for Model 2. Conclusion: In conclusion, this research proposes a correction score for comparisons of abdominal aortic calcification measurements in post-contrast and non-contrast scans.

scholarly journals A Comparative Study of Clinical vs. Digital Exophthalmometry Measurement Methods

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Tháıs de Sous Pereira ◽  
Cristina Hiromi Kuniyoshi ◽  
Cristiane de Almeida Leite ◽  
Eloisa M. M. S. Gebrim ◽  
Mário L. R. Monteiro ◽  
...  
Keyword(s):  
Ct Scan ◽  
Pearson Correlation ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Measurement Methods ◽  
Gold Standard Method ◽  
Mean Values ◽  
Ct Measurements ◽  
Mean Differences ◽  
No Gold Standard

Background. A number of orbital diseases may be evaluated based on the degree of exophthalmos, but there is still no gold standard method for the measurement of this parameter. In this study we compare two exophthalmometry measurement methods (digital photography and clinical) with regard to reproducibility and the level of correlation and agreement with measurements obtained with Computerized Tomography (CT) measurements. Methods. Seventeen patients with bilateral proptosis and 15 patients with normal orbits diseases were enrolled. Patients underwent orbital CT, Hertel exophthalmometry (HE) and standardized frontal and side facial photographs by a single trained photographer. Exophthalmometry measurements with HE, the digital photographs and axial CT scans were obtained twice by the same examiner and once by another examiner. Pearson correlation coefficient (PCC) was used to assess correlations between methods. Validity between methods was assessed by mean differences, interintraclass correlation coefficients (ICC’s), and Bland–Altman plots. Results. Mean values were significantly higher in the proptosis group (34 orbits) than in the normal group (30 orbits), regardless of the method. Within each group, mean digital exophthalmometry measurements (24.32 ± 5.17 mm and 18.62 ± 3.87 mm) were significantly greater than HE measurements (20.87 ± 2.53 mm and 17.52 ± 2.67 mm) with broader range of standard deviation. Inter-/intraclass correlation coefficients were 0.95/0.93 for clinical, 0.92/0.74 for digital, and 0.91/0.95 for CT measurements. Correlation coefficients between HE and CT scan measurements in both groups of subjects (r = 0.84 and r = 0.91, p<0.05) were greater than those between digital and CT scan measurements (r = 0.61 and r = 0.75, p<0.05). On the Bland–Altman plots, HE showed better agreement to CT measurements compared to the digital photograph method in both groups studied. Conclusions. Although photographic digital exophthalmometry showed strong correlation and agreement with CT scan measurements, it still performs worse than and is not as accurate as clinical Hertel exophthalmometry. This trail is registered with NCT01999790.

scholarly journals Textural analysis and lung function study: Predicting lung fitness for radiotherapy from a CT scan

BJR|Open ◽  
2019 ◽  
Vol 1 (1) ◽  
pp. bjro.20180001
Author(s):  
Iain Phillips ◽  
Veni Ezhil ◽  
Mohammad Hussein ◽  
Christopher South ◽  
Andrew Nisbet ◽  
...  
Keyword(s):  
Lung Function ◽  
Ct Scan ◽  
Region Of Interest ◽  
Lung Parenchyma ◽  
Forced Expiratory Volume ◽  
Ct Imaging ◽  
Radiotherapy Planning ◽  
Apical Region ◽  
Radical Radiotherapy ◽  
Unfit Patients

Objective: This study tested the hypothesis that shows advanced image analysis can differentiate fit and unfit patients for radical radiotherapy from standard radiotherapy planning imaging, when compared to formal lung function tests, FEV1 (forced expiratory volume in 1 s) and TLCO (transfer factor of carbon monoxide). Methods: An apical region of interest (ROI) of lung parenchyma was extracted from a standard radiotherapy planning CT scan. Software using a grey level co-occurrence matrix (GLCM) assigned an entropy score to each voxel, based on its similarity to the voxels around it. Results: Density and entropy scores were compared between a cohort of 29 fit patients (defined as FEV1 and TLCO above 50 % predicted value) and 32 unfit patients (FEV1 or TLCO below 50% predicted). Mean and median density and median entropy were significantly different between fit and unfit patients (p = 0.005, 0.0008 and 0.0418 respectively; two-sided Mann–Whitney test). Conclusion: Density and entropy assessment can differentiate between fit and unfit patients for radical radiotherapy, using standard CT imaging. Advances in knowledge: This study shows that a novel assessment can generate further data from standard CT imaging. These data could be combined with existing studies to form a multiorgan patient fitness assessment from a single CT scan.

scholarly journals Machine-Learning Based Hybrid-Feature Analysis for Liver Cancer Classification Using Fused (MR and CT) Images

2020 ◽  
Vol 10 (9) ◽  
pp. 3134 ◽  
Author(s):  
Samreen Naeem ◽  
Aqib Ali ◽  
Salman Qadri ◽  
Wali Khan Mashwani ◽  
Nasser Tairan ◽  
...  
Keyword(s):  
Machine Learning ◽  
Liver Cancer ◽  
Ct Scan ◽  
Region Of Interest ◽  
Hepatocellular Adenoma ◽  
Cancer Classification ◽  
Support Vector ◽  
Hybrid Features ◽  
Feature Selection Technique ◽  
Probability Of Error

The purpose of this research is to demonstrate the ability of machine-learning (ML) methods for liver cancer classification using a fused dataset of two-dimensional (2D) computed tomography (CT) scans and magnetic resonance imaging (MRI). Datasets of benign (hepatocellular adenoma, hemangioma, cyst) and malignant (hepatocellular carcinoma, hepatoblastoma, metastasis) liver cancer were acquired at Bahawal Victoria Hospital (BVH), Bahawalpur, Pakistan. The final dataset was generated by fusion of 1200 (100 × 6 × 2) MR and CT-scan images, 200 (100 MRI and 100 CT-scan) images size 512 × 512 for each class of cancer. The acquired dataset was preprocessed by employing the Gabor filters to reduce the noise and taking an automated region of interest (ROIs) using an Otsu thresholding-based segmentation approach. The preprocessed dataset was used to acquire 254 hybrid-feature data for each ROI, which is the combination of the histogram, wavelet, co-occurrence, and run-length features, while 10 optimized hybrid features were selected by employing (probability of error plus average correlation) feature selection technique. For classification, we deployed this optimized hybrid-feature dataset to four ML classifiers: multilayer perceptron (MLP), support vector machine (SVM), random forest (RF), and J48, using a ten fold cross-validation method. MLP showed an overall accuracy of (95.78% on MRI and 97.44% on CT). Unfortunately, the obtained results were not promising, and there were some limitations due to the different modalities of the dataset. Thereafter, a fusion of MRI and CT-scan datasets generated the fused optimized hybrid-feature dataset. The MLP has shown a promising accuracy of 99% among all the deployed classifiers.

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