Computed tomography scans image processing for nasal symptoms severity prediction

This paper aims to use a new technique of computed tomography (CT) scan image processing to correlate the image analysis with sinonasal symptoms. A retrospective cross-sectional study is conducted by analyzing the digital records of 50 patients who attended the ear, nose and throat (ENT) clinics at King Abdullah University Hospital, Jordan. The coronal plane CT scans are analyzed using our developed software. The purposes of this software are to calculate the surface area of the nasal passage at three different levels visible on coronal plane CT scans: i) the head of the inferior turbinate, ii) the head of the middle turbinate, and iii) the tail of the inferior turbinate. We employ image processing techniques to correlate the narrowing of nasal surface area with sinonasal symptoms. As a consequence, obstruction in the first level is correlated significantly with the symptoms of nasal obstruction while the narrowing in the second level is related to frontal headache. No other significant correlations are found with nasal symptoms at the third level. In our study, we find that image processing techniques can be very useful to predict the severity of common nasal symptoms and they can be used to suggest treatment and to follow up on the case progression.

Comparison of Image Quality and Spatial Resolution Between 18F, 68Ga and 64Cu Phantom Measurements Using a Digital Biograph Vision PET/CT

Background: The PET nuclide and reconstruction method can have a considerable influence on spatial resolution and image quality of PET/CT scans, which can, for example, influence the diagnosis in oncology. The individual impact of the positron energy of 18F, 68Ga and 64Cu on spatial resolution and image quality of PET/CT scans acquired using a clinical, digital scanner was compared. Furthermore, the impact of different reconstruction parameters on image quality and spatial resolution was evaluated for 18F-FDG PET/CT scans acquired with a scanner of the newest generation. Methods: PET/CT scans of a Jaszczak phantom and a NEMA PET body phantom, filled with 18F-FDG, 68Ga-HCl and 64Cu-HCl, respectively, were performed on a Siemens Biograph Vision. Images were assessed using spatial resolution and image quality (Recovery Coefficients (RC), coefficient of variation within the background, Contrast Recovery Coefficient (CRC), Contrast-Noise-Ratio (CNR), and relative count error in lung insert). In a subsequent analysis, the scan of the NEMA PET body phantom filled with 18F-FDG was reconstructed applying different parameters (with/without the application of Point Spread Function (PSF), Time of Flight (ToF) or post-filtering; matrix size). Spatial resolution and quantitative image quality were compared between reconstructions. Results: We found that image quality was comparable between 18F-FDG and 64Cu-HCl PET/CT measurements featuring similar maximal endpoint energy. In comparison, RC, CRC and CNR were worse in 68Ga-HCl data, despite similar count rates. Spatial resolution was up to 18 % worse in 68Ga-HCl compared to 18F-FDG images. Post-filtering of 18F-FDG acquisitions changed image quality the most and reduced spatial resolution by 52 % if a Gaussian filter with 5 mm FWHM was applied. ToF measurements especially improved the recovery of the smallest lesion (RCmean = 1.07 compared to 0.65 without ToF) and improved spatial resolution by 29 %.Conclusions: The positron energy of PET nuclides influences spatial resolution and image quality of digital PET/CT scans. Image quality of 68Ga-HCl PET/CT images was worse compared to 18F-FDG and 64Cu-HCl, respectively, despite similar count rates. Reconstruction parameters have a high impact on image quality and spatial resolution and should be considered when comparing images of different scanners or centers.

Pulmonary Sequelae in Patients After Recovery From Coronavirus Disease 2019: A Follow-Up Study With Chest CT

Objective: The pulmonary sequelae of coronavirus disease 2019 (COVID-19) have not been comprehensively evaluated. We performed a follow-up study analyzing chest computed tomography (CT) findings of COVID-19 patients at 3 and 6 months after hospital discharge.Methods: Between February 2020 and May 2020, a total of 273 patients with COVID-19 at the Shenzhen Third People's Hospital were recruited and followed for 6 months after discharge. Chest CT scanning was performed with the patient in the supine position at end-inspiration. A total of 957 chest CT scans was obtained at different timepoints. A semi-quantitative score was used to assess the degree of lung involvement.Results: Most chest CT scans showed bilateral lung involvement with peripheral location at 3 and 6 months follow-up. The most common CT findings were ground-glass opacity and parenchymal band, which were found in 136 (55.3%) and 94 (38.2%) of the 246 patients at 3 months follow-up, and 82 (48.2%) and 76 (44.7%) of 170 patients at 6 months follow-up, respectively. The number of lobes involved and the total CT severity score declined over time. The total CT score gradually increased with the increasement of disease severity at both 3 months follow-up (trend test P < 0.001) and 6 months follow-up (trend test P < 0.001). Patients with different disease severity represented diverse CT patterns over time.Conclusions: The most common CT findings were ground-glass opacity and parenchymal bands at the 3 and 6 months follow-up. Patients with different disease severity represent diverse CT manifestations, indicating the necessary for long-term follow-up monitoring of patients with severe and critical conditions.

Features on Computed Tomography That Correlate With Acute Appendicitis

Background: The purpose of this study is to investigate the relevant findings in adult patients admitted to Cabell Huntington Hospital who were diagnosed with acute appendicitis. Methods: Patients who had the postoperative diagnosis of acute appendicitis and a preoperative computed tomography (CT) scan from January 2011 through December 2016 were included in this retrospective chart review. Results: There were 592 patients. A thick, edematous appendix was the most common CT finding in acute appendicitis. The average diameter was 12.6 mm. The wall thickness correlated to the diameter of the appendix ( P < 0.001). For comparison, we reviewed the CT scans of 50 trauma patients who had normal abdominal CT scans. The average diameter of a normal appendix was 4.9 mm (SD 1.139) with a range of 4-7 mm. Interestingly, the admission white blood cell count ( P = 0.0372) as well as the thickness of the appendix ( P < 0.0001) were strongly associated with increased length of stay. Conclusions: An appendiceal diameter greater than 9 mm should be considered abnormal and associated with acute appendicitis. Appendiceal size, white blood cell count, and age correlate with length of stay. Early antibiotics and early surgical intervention may decrease length of stay.

Fatality Case in a Tuberculous Meningoencephalitis Patient Coinfected with COVID-19

: Tuberculous meningoencephalitis (TBM) is the most severe, life-threatening form of tuberculosis that contributes to as much as 5% of cases of extrapulmonary tuberculosis. Emerging at the end of 2019, COVID-19 has been shown to affect various organs, including the brain. In this case report, a 21-year-old woman diagnosed with TBM, being in the intensive phase of tuberculous therapy, came with dysphagia and dysphonia as new complaints felt one day before admission accompanied by a positive meningeal sign, diplopia, and cephalgia, which became heavier after previously getting better. Cough and fever followed this complaint two days before admission. About the laboratory results, the PCR was positive for COVID-19, and CT scans showed increased leptomeningeal enhancement when compared with CT scan one month earlier. The patient received intravenous dexamethasone, anti-tuberculosis drugs, phenytoin, aspirin, oseltamivir, and hydroxychloroquine. The patient died four days after being hospitalized due to respiratory failure. This case report shows the coinfection of COVID-19 and TBM resulting in a poor tuberculosis treatment response and outcome.

Exploring Response to Immunotherapy in Non-Small Cell Lung Cancer Using Delta-Radiomics

Delta-radiomics is a branch of radiomics in which features are confronted after time or after introducing an external factor (such as treatment with chemotherapy or radiotherapy) to extrapolate prognostic data or to monitor a certain condition. Immune checkpoint inhibitors (ICIs) are currently revolutionizing the treatment of non-small cell lung cancer (NSCLC); however, there are still many issues in defining the response to therapy. Contrast-enhanced CT scans of 33 NSCLC patients treated with ICIs were analyzed; altogether, 43 lung lesions were considered. The radiomic features of the lung lesions were extracted from CT scans at baseline and at first reassessment, and their variation (delta, Δ) was calculated by means of the absolute difference and relative reduction. This variation was related to the final response of each lesion to evaluate the predictive ability of the variation itself. Twenty-seven delta features have been identified that are able to discriminate radiologic response to ICIs with statistically significant accuracy. Furthermore, the variation of nine features significantly correlates with pseudo-progression.

Comparative Analysis of Root Canal Dentin Removal Capacity of Two NiTi Endodontic Reciprocating Systems for the Root Canal Treatment of Primary Molar Teeth. An In Vitro Study

The objective of the present study was to evaluate and compare the dentin removal capacity of Endogal Kids and Reciproc Blue NiTi alloy endodontic reciprocating systems for root canal treatments in primary second molar teeth via a micro-computed tomography (micro-CT) scan. Materials and Methods: Sixty root canal systems in fifteen primary second molar teeth were chosen and classified into one of the following study groups: A: EK3 Endogal Kids (n = 30) (EDG) and B. R25 Reciproc Blue (n = 30) (RB). Preoperative and postoperative micro-CT scans were uploaded into image processing software to analyze the changes in the volume of root canal dentin using a mathematical algorithm that enabled progressive differentiation between neighboring pixels after defining and segmenting the root canal systems in both micro-CT scans. Volumetric variations in the root canal system and the root canal third were calculated using a t-test for independent samples or a nonparametric Mann–Whitney–Wilcoxon test. Results: Statistically significant differences (p = 0.0066) in dentin removal capacity were found between the EDG (2.89 ± 1.26 mm3) and RB (1.22 ± 0.58 mm3) study groups for the coronal root canal third; however, no statistically significant differences were found for the middle (p = 0.4864) and apical (p = 0.6276) root canal thirds. Conclusions: Endogal and Reciproc Blue NiTi endodontic reciprocating systems showed similar capacity for the removal of root canal dentin, except for the coronal root canal third, in which the Reciproc Blue NiTi endodontic reciprocating system preserved more root canal dentin tissue.

Clinical Validation and Treatment Plan Evaluation Based on Auto-Delineation of the Clinical Target Volume for Prostate Cancer Radiotherapy

Purpose Clinical target volumes (CTV) and organs at risk (OAR) could be auto-contoured to save workload. The goal of this study was to assess a convolutional neural network (CNN) for totally automatic and accurate CTV and OAR in prostate cancer, while also comparing anticipated treatment plans based on auto-contouring CTV to clinical plans. Methods From January 2013 to January 2019, 217 computed tomography (CT) scans of patients with locally advanced prostate cancer treated at our hospital were collected and analyzed. CTV and OAR were delineated with a deep learning based method, which named CUNet. The performance of this strategy was evaluated using the mean Dice similarity coefficient (DSC), 95th percentile Hausdorff distance (95HD), and subjective evaluation. Treatment plans were graded using predetermined evaluation criteria, and % errors for clinical doses to the planned target volume (PTV) and organs at risk(OARs) were calculated. Results The defined CTVs had mean DSC and 95HD values of 0.84 and 5.04 mm, respectively. For one patient's CT scans, the average delineation time was less than 15 seconds. When CTV outlines from CUNetwere blindly chosen and compared to GT, the overall positive rate in clinicians A and B was 53.15% vs 46.85%, and 54.05% vs 45.95%, respectively (P>0.05), demonstrating that our deep machine learning model performed as good as or better than human demarcation Furthermore, 8 testing patients were chosen at random to design the predicted plan based on the auto-courtoring CTV and OAR, demonstrating acceptable agreement with the clinical plan: average absolute dose differences of D2, D50, D98, Dmean for PTV are within 0.74%, and average absolute volume differences of V45, V50 for OARs are within 3.4%. Without statistical significance (p>0.05), the projected findings are comparable to clinical truth. Conclusion The experimental results show that the CTV and OARs defined by CUNet for prostate cancer were quite close to the ground reality.CUNet has the potential to cut radiation oncologists' contouring time in half. When compared to clinical plans, the differences between estimated doses to CTV and OAR based on auto-courtoring were small, with no statistical significance, indicating that treatment planning for prostate cancer based on auto-courtoring has potential.