Assessing variability in non-contrast CT for the evaluation of stroke: The effect of CT image reconstruction conditions on AI-based CAD measurements of ASPECTS value and hypodense volume.

Purpose: To rule out hemorrhage, non-contrast CT (NCCT) scans are used for early evaluation of patients with suspected stroke. Recently, artificial intelligence tools have been developed to assist with determining eligibility for reperfusion therapies by automating measurement of the Alberta Stroke Program Early CT Score (ASPECTS), a 10-point scale with > 7 or ≤ 7 being a threshold for change in functional outcome prediction and higher chance of symptomatic hemorrhage, and hypodense volume. The purpose of this work was to investigate the effects of CT reconstruction kernel and slice thickness on ASPECTS and hypodense volume. Methods: The NCCT series image data of 87 patients imaged with a CT stroke protocol at our institution were reconstructed with 3 kernels (H10s-smooth, H40s-medium, H70h-sharp) and 2 slice thicknesses (1.5mm and 5mm) to create a reference condition (H40s/5mm) and 5 non-reference conditions. Each reconstruction for each patient was analyzed with the Brainomix e-Stroke software (Brainomix, Oxford, England) which yields an ASPECTS value and measure of total hypodense volume (mL). Results: An ASPECTS value was returned for 74 of 87 cases in the reference condition (13 failures). ASPECTS in non-reference conditions changed from that measured in the reference condition for 59 cases, 7 of which changed above or below the clinical threshold of 7 for 3 non-reference conditions. ANOVA tests were performed to compare the differences in protocols, Dunnett's post-hoc tests were performed after ANOVA, and a significance level of p < 0.05 was defined. There was no significant effect of kernel (p = 0.91), a significant effect of slice thickness (p < 0.01) and no significant interaction between these factors (p = 0.91). Post-hoc tests indicated no significant difference between ASPECTS estimated in the reference and any non-reference conditions. There was a significant effect of kernel (p < 0.01) and slice thickness (p < 0.01) on hypodense volume, however there was no significant interaction between these factors (p = 0.79). Post-hoc tests indicated significantly different hypodense volume measurements for H10s/1.5mm (p = 0.03), H40s/1.5mm (p < 0.01), H70h/5mm (p < 0.01). No significant difference was found in hypodense volume measured in the H10s/5mm condition (p = 0.96). Conclusion: Automated ASPECTS and hypodense volume measurements can be significantly impacted by reconstruction kernel and slice thickness.

Multiparametric Radiogenomic Model to Predict Survival in Patients with Glioblastoma.

BACKGROUND: Clinical, histopathological, and imaging variables have been associated with prognosis in patients with glioblastoma (GBM). We aimed to develop a multiparametric radiogenomic model incorporating MRI texture features, demographic data, and histopathological tumor biomarkers to predict prognosis in patients with GBM. METHODS: In this retrospective study, patients were included if they had confirmed diagnosis of GBM with histopathological biomarkers and pre-operative MRI. Tumor segmentation was performed, and texture features were extracted to develop a predictive radiomic model of survival (<18 months vs. ≥18 months) using multivariate analysis and Least Absolute Shrinkage and Selection Operator (LASSO) regularization to reduce the risk of overfitting. This radiomic model in combination with clinical and histopathological data was inserted into a backward stepwise logistic regression model to assess survival. The diagnostic performance of this model was reported for the training and external validation sets. RESULTS: A total of 116 patients were included for model development and 40 patients for external testing validation. The diagnostic performance (AUC/sensitivity/specificity) of the radiomic model generated from seven texture features in determination of ≥18 months survival was 0.71/69.0/70.3. Three variables remained as independent predictors of survival, including radiomics (p = 0.004), age (p = 0.039), and MGMT status (p = 0.025). This model yielded diagnostic performance (AUC/sensitivity/specificity) of 0.77/81.0/66.0 (training) and 0.89/100/78.6 (testing) in determination of survival ≥ 18 months. CONCLUSIONS: Results show that our radiogenomic model generated from radiomic features at baseline MRI, age, and MGMT status can predict survival ≥ 18 months in patients with GBM.

Cone-Beam Computed Tomography Assessment of Prevalence of Procedural Errors in Maxillary Posterior Teeth.

A range of procedural errors can occur when performing endodontic treatment on posterior teeth. These errors may decrease the success rate in endodontic practice. This study assessed the prevalence of procedural errors and the quality of endodontic treatments in maxillary molars and premolars using cone-beam computed tomography (CBCT). CBCT scans from two private radiology centers were assessed retrospectively to ensure the same calculated sample size of 327 teeth for each of the four maxillary posterior tooth types (a total of 1,308 endodontically treated teeth). Image sets were evaluated for procedural errors categorized as follows: obturation length (overfilling or underfilling by >2 mm short of the root apex), missed canals, perforations, strip perforations (with extrusion of material into the furcation area), separated instruments in the root canal space, and root fracture. Data were analyzed with SPSS version 20 (SPSS Inc., Chicago, IL, USA), and frequency data was assessed using the Monte Carlo test at the 0.05 level of significance. The procedural errors most commonly reported in the present study were from most frequent to least frequent: underfilled canals (50.0%), missed canals (27.5%), overfilled canals (12.5%), apical perforations (5.0%), separated instruments (3.1%), and root fractures (1.9%). No strip perforations (with extrusion of material into the furcation area) were seen in the study (0%). Underfilled and missed root canals were the most frequent procedural errors identified in the present study. These findings underline the importance of more consideration of critical working length management during all stages of root canal treatment, greater awareness of root canal anatomy, and the use of imaging and diagnostic devices that enhance the ability to identify and treat root canals both safely and effectively.

Automated assessment of ischemic core on non-contrast computed tomography: a multicenter comparative analysis with CT perfusion.

BACKGROUND: Application of machine learning (ML) algorithms has shown promising results in estimating ischemic core volumes using non-contrast CT (NCCT). OBJECTIVE: To assess the performance of the e-Stroke Suite software (Brainomix) in assessing ischemic core volumes on NCCT compared with CT perfusion (CTP) in patients with acute ischemic stroke. METHODS: In this retrospective multicenter study, patients with anterior circulation large vessel occlusions who underwent pretreatment NCCT and CTP, successful reperfusion (modified Thrombolysis in Cerbral Infarction ≥2b), and post-treatment MRI, were included from three stroke centers. Automated calculation of ischemic core volumes was obtained on NCCT scans using ML algorithm deployed by e-Stroke Suite and from CTP using Olea software (Olea Medical). Comparative analysis was performed between estimated core volumes on NCCT and CTP and against MRI calculated final infarct volume (FIV). RESULTS: A total of 111 patients were included. Estimated ischemic core volumes (mean±SD, mL) were 20.4±19.0 on NCCT and 19.9±18.6 on CTP, not significantly different (P=0.82). There was moderate (r=0.40) and significant (P<0.001) correlation between estimated core on NCCT and CTP. The mean difference between FIV and estimated core volume on NCCT and CTP was 29.9±34.6 mL and 29.6±35.0 mL, respectively (P=0.94). Correlations between FIV and estimated core volume were similar for NCCT (r=0.30, P=0.001) and CTP (r=0.36, P<0.001). CONCLUSIONS: Results show that ML-based estimated ischemic core volumes on NCCT are comparable to those obtained from concurrent CTP in magnitude and in degree of correlation with MR-assessed FIV.

Perfusion Collateral Index versus Hypoperfusion Intensity Ratio in Assessment of Collaterals in Patients with Acute Ischemic Stroke.

BACKGROUND AND PURPOSE: Perfusion-based collateral indices such as the perfusion collateral index and the hypoperfusion intensity ratio have shown promise in the assessment of collaterals in patients with acute ischemic stroke. We aimed to compare the diagnostic performance of the perfusion collateral index and the hypoperfusion intensity ratio in collateral assessment compared with angiographic collaterals and outcome measures, including final infarct volume, infarct growth, and functional independence. MATERIALS AND METHODS: Consecutive patients with acute ischemic stroke with anterior circulation proximal arterial occlusion who underwent endovascular thrombectomy and had pre- and posttreatment MRI were included. Using pretreatment MR perfusion, we calculated the perfusion collateral index and the hypoperfusion intensity ratio for each patient. The angiographic collaterals obtained from DSA were dichotomized to sufficient (American Society of Interventional and Therapeutic Neuroradiology [ASITN] scale 3-4) versus insufficient (ASITN scale 0-2). The association of collateral status determined by the perfusion collateral index and the hypoperfusion intensity ratio was assessed against angiographic collaterals and outcome measures. RESULTS: A total of 98 patients met the inclusion criteria. Perfusion collateral index values were significantly higher in patients with sufficient angiographic collaterals (P < .001), while there was no significant (P = .46) difference in hypoperfusion intensity ratio values. Among patients with good (mRS 0-2) versus poor (mRS 3-6) functional outcome, the perfusion collateral index of ≥ 62 was present in 72% versus 31% (P = .003), while the hypoperfusion intensity ratio of ≤0.4 was present in 69% versus 56% (P = .52). The perfusion collateral index and the hypoperfusion intensity ratio were both significantly predictive of final infarct volume, but only the perfusion collateral index was significantly (P = .03) associated with infarct growth. CONCLUSIONS: Results show that the perfusion collateral index outperforms the hypoperfusion intensity ratio in the assessment of collateral status, infarct growth, and determination of functional outcomes.

Cone-Beam Computed Tomography Assessment of Quality of Endodontic Treatment and Prevalence of Procedural Errors in Mandibular Molars.

Objectives: This study assessed the quality of endodontic treatment and the prevalence of procedural errors in permanent mandibular molars using cone-beam computed tomography (CBCT). Materials and Methods: This cross-sectional study was conducted on 328 CBCT scans (182 females and 146 males) of endodontically treated mandibular molars retrieved from the archives of two radiology centers in Ardabil city, Iran, in 2019. Mandibular molars were evaluated on sagittal, coronal, and axial sections regarding obturation length, obturation density (voids), missed canals, broken instruments, apical perforation, strip perforation, ledge formation, transportation, root fracture, root resorption, and periapical lesions by a senior dental student under the supervision of an oral and maxillofacial radiologist and an endodontist. Differences between the frequency of procedural errors and tooth type and gender were analyzed by the chi-square test. Results: The frequency of underfilling, missed canals, overfilling, voids, apical perforation, transportation, ledge formation, broken instruments, root fracture, strip perforation, root resorption, and periapical lesions was 34.8%, 17.4%, 16.8%, 14.3%, 7.3%, 6.1%, 4.3%, 3%, 1.2%, 0.6%, 5.5%, and 46%, respectively. The frequency of root fracture was significantly higher in females than in males (P < 0.05). The prevalence of underfilling was the highest in right second molars (47.2%), followed by right first molars, left second molars, and left first molars (P < 0.005). The frequency of transportation was maximum in right first molars (10%), followed by right second molars, left first molars, and left second molars (P < 0.04). Conclusion: Underfilling, missed canals, and overfilling were the most prevalent procedural errors in mandibular molars in our study population.

A Review on the Applications of Crowdsourcing in Human Pathology.

The advent of the digital pathology has introduced new avenues of diagnostic medicine. Among them, crowdsourcing has attracted researchers' attention in the recent years, allowing them to engage thousands of untrained individuals in research and diagnosis. While there exist several articles in this regard, prior works have not collectively documented them. We, therefore, aim to review the applications of crowdsourcing in human pathology in a semi-systematic manner. We first, introduce a novel method to do a systematic search of the literature. Utilizing this method, we, then, collect hundreds of articles and screen them against a predefined set of criteria. Furthermore, we crowdsource part of the screening process, to examine another potential application of crowdsourcing. Finally, we review the selected articles and characterize the prior uses of crowdsourcing in pathology.

Determining the lymphadenopathy characteristics of the mediastinum in lung CT scan of children with tuberculosis.

OBJECTIVE/BACKGROUND: Most tuberculosis cases in children are primary infection, with difficult and imprecise diagnosis mainly based on the existence of mediastinal lymphadenopathy. Here, we investigated the characteristics of mediastinal lymphadenopathy in lung computed tomography (CT) scans of children with tuberculosis. METHODS: This cross-sectional study was performed on 75 children with tuberculosis referred to Masih Daneshvari Hospital in Tehran, Iran, from 2009 to 2013. Their medical records were investigated, and CT-scan characteristics were extracted by a radiologist. RESULTS: Mean±standard deviation age of cases was 11.2±4.6years. CT-scan results indicated 94.7% of cases had lymphadenopathy, with lower paratracheal, upper paratracheal, hilar, and subcarinal forms observed in 81.7%, 69.1%, 53.5%, and 47.9% of cases as the most involved stations in lymph nodes, respectively. In 74.6% of patients with mediastinal lymphadenopathy, perilymph node fat inflammation (matting) was observed, with 52.11% exhibiting conglomeration. Bronchial pressure was observed in 4.23% of children with tuberculosis, and bilateral-, right-, and left-parenchymal involvement was observed in 42.7%, 25.3%, and 8% of these cases, respectively. Left- and right-pleural effusion and calcification was reported in 6.7%, 12%, and 5.6% of patients, respectively. Additionally, nearly 80% of patients exhibited mediastinal lymphadenopathy and lung-parenchyma involvement simultaneously. Lung-parenchyma involvement was significantly correlated with subcarinal (p<.001), hilar (p<.001), subaortic (p=.030), lower paratracheal (p=.037), and axillary (p=.006) stations. CONCLUSION: Situation of mediastinal lymphadenopathy and its synchronicity with lung-parenchyma involvement can help in differential diagnosis of pulmonary tuberculosis from other lung diseases.