Examining feature extraction and classification modules in machine learning for diagnosis of low-dose computed tomographic screening-detected in vivo lesions.

Purpose: Medical imaging-based machine learning (ML) for computer-aided diagnosis of in vivo lesions consists of two basic components or modules of (i) feature extraction from non-invasively acquired medical images and (ii) feature classification for prediction of malignancy of lesions detected or localized in the medical images. This study investigates their individual performances for diagnosis of low-dose computed tomography (CT) screening-detected lesions of pulmonary nodules and colorectal polyps. Approach: Three feature extraction methods were investigated. One uses the mathematical descriptor of gray-level co-occurrence image texture measure to extract the Haralick image texture features (HFs). One uses the convolutional neural network (CNN) architecture to extract deep learning (DL) image abstractive features (DFs). The third one uses the interactions between lesion tissues and X-ray energy of CT to extract tissue-energy specific characteristic features (TFs). All the above three categories of extracted features were classified by the random forest (RF) classifier with comparison to the DL-CNN method, which reads the images, extracts the DFs, and classifies the DFs in an end-to-end manner. The ML diagnosis of lesions or prediction of lesion malignancy was measured by the area under the receiver operating characteristic curve (AUC). Three lesion image datasets were used. The lesions' tissue pathological reports were used as the learning labels. Results: Experiments on the three datasets produced AUC values of 0.724 to 0.878 for the HFs, 0.652 to 0.965 for the DFs, and 0.985 to 0.996 for the TFs, compared to the DL-CNN of 0.694 to 0.964. These experimental outcomes indicate that the RF classifier performed comparably to the DL-CNN classification module and the extraction of tissue-energy specific characteristic features dramatically improved AUC value. Conclusions: The feature extraction module is more important than the feature classification module. Extraction of tissue-energy specific characteristic features is more important than extraction of image abstractive and characteristic features.

Predicting coronary artery severity in patients undergoing coronary computed tomographic angiography: Insights from pan-immune inflammation value and atherogenic index of plasma.

BACKGROUND AND AIMS: Coronary computed tomographic angiography (CCTA) is pivotal in diagnosing coronary artery disease (CAD). We explored the link between CAD severity and two biomarkers, Pan-Immune Inflammation Value (PIV) and Atherogenic Index of Plasma (AIP), in stable CAD patients. METHODS AND RESULTS: A retrospective observational study of 409 CCTA patients with stable angina pectoris. Logistic regression identified predictors of severe CAD, stratified by CAD-RADS score. Receiver Operating Characteristic (ROC) curves evaluated predictive performance. PIV and AIP were significant predictors of severe CAD (PIV: OR 1.002, 95% CI: 1.000-1.004, p < 0.021; AIP: OR 0.963, 95% CI: 0.934-0.993, p < 0.04). AUC values for predicting severe CAD were 0.563 (p < 0.001) for PIV and 0.625 (p < 0.05) for AIP. Combined with age, AUC improved to 0.662 (p < 0.02). CONCLUSIONS: PIV and AIP were associated with severe CAD, with AIP demonstrating superior predictive capability. Incorporating AIP into risk assessment could enhance CAD prediction, offering a cost-effective and accessible method for identifying individuals at high risk of coronary atherosclerosis.

Relationship between different clinical characteristics and pericoronary adipose tissue attenuation values quantified from coronary computed tomographic angiography (CCTA) in patients without coronary heart disease (CHD).

Background: Pericoronary adipose tissue (PCAT) is a sensor of vascular inflammation. Elevated PCAT attenuation values indicate the presence of coronary inflammation in patients. However, it is unclear which clinical characteristics are associated with increased PCAT attenuation values in patients without coronary heart disease (CHD). The study aims to investigate the relationship between increased PCAT attenuation values and clinical characteristics of patients without CHD. Methods: We recruited 785 eligible patients without CHD who underwent coronary computed tomographic angiography (CCTA). Clinical data were recorded for each patient, and PCAT attenuation values for the left anterior descending branch (LADPCAT), left circumflex branch (LCXPCAT), and right coronary artery (RCAPCAT) were quantified by CCTA using fully automated software. Univariate and multivariate analyses were performed to identify the associations between different clinical characteristics and elevated LADPCAT, LCXPCAT, and RCAPCAT. Results: Univariate analysis showed body mass index (BMI) to be positively associated with LADPCAT (rs=0.109), LCXPCAT (rs=0.076), and RCAPCAT (rs=0.083). Moreover, the duration of smoking, and drinking was positively associated with LADPCAT (rs=0.099, 0.165). Hyperlipidemia was positively associated with LADPCAT (rs=0.089) and RCAPCAT (rs=0.334), while statin use was negatively associated with RCAPCAT (rs=-0.145). Multivariate analysis showed that the significant determinants of LADPCAT were BMI (ß=0.359, P=0.001), duration of smoking (ß=2.612, P=0.002), drinking (ß=4.106, P<0.001), and hyperlipidemia (ß=1.664, P=0.027). LCXPCAT was associated with BMI (ß=0.218, P=0.024), while RCAPCAT was associated with hyperlipidemia (ß=6.110, P<0.001) and statin use (ß=-3.338, P<0.001). Conclusions: In patients without CHD, the PCAT attenuation values measured using CCTA were associated with various clinical characteristics. LADPCAT was associated with BMI, smoking duration, drinking, and hyperlipidemia. On the other hand, LCXPCAT was associated with BMI, while RCAPCAT was associated with hyperlipidemia and statin use.

Automated detection and classification of coronary atherosclerotic plaques on coronary CT angiography using deep learning algorithm.

Background: Coronary artery disease (CAD) is the leading cause of mortality worldwide. Recent advances in deep learning technology promise better diagnosis of CAD and improve assessment of CAD plaque buildup. The purpose of this study is to assess the performance of a deep learning algorithm in detecting and classifying coronary atherosclerotic plaques in coronary computed tomographic angiography (CCTA) images. Methods: Between January 2019 and September 2020, CCTA images of 669 consecutive patients with suspected CAD from Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine were included in this study. There were 106 patients included in the retrospective plaque detection analysis, which was evaluated by a deep learning algorithm and four independent physicians with varying clinical experience. Additionally, 563 patients were included in the analysis for plaque classification using the deep learning algorithm, and their results were compared with those of expert radiologists. Plaques were categorized as absent, calcified, non-calcified, or mixed. Results: The deep learning algorithm exhibited higher sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy {92% [95% confidence interval (CI): 89.5-94.1%], 87% (95% CI: 84.2-88.5%), 79% (95% CI: 76.1-82.4%), 95% (95% CI: 93.4-96.3%), and 89% (95% CI: 86.9-90.0%)} compared to physicians with ≤5 years of clinical experience in CAD diagnosis for the detection of coronary plaques. The algorithm's overall sensitivity, specificity, PPV, NPV, accuracy, and Cohen's kappa for plaque classification were 94% (95% CI: 92.3-94.7%), 90% (95% CI: 88.8-90.3%), 70% (95% CI: 68.3-72.1%), 98% (95% CI: 97.8-98.5%), 90% (95% CI: 89.8-91.1%) and 0.74 (95% CI: 0.70-0.78), indicating strong performance. Conclusions: The deep learning algorithm has demonstrated reliable and accurate detection and classification of coronary atherosclerotic plaques in CCTA images. It holds the potential to enhance the diagnostic capabilities of junior radiologists and junior intervention cardiologists in the CAD diagnosis, as well as to streamline the triage of patients with acute coronary symptoms.

Coronary computed tomographic angiography-derived anatomic and hemodynamic plaque characteristics in prediction of cardiovascular events.

This study investigated the association of anatomic and hemodynamic plaque characteristics based on deep learning coronary computed tomography angiography (CCTA) with high-risk plaques that caused subsequent major adverse cardiovascular events (MACE). A retrospective analysis was conducted on patients who underwent CCTA between 1 month and 3 years prior to the occurrence of a MACE. Deep learning and computational fluid dynamics algorithms based on CCTA were applied to extract adverse plaque characteristics (low-attenuation plaque, positive remodeling, napkin-ring sign, and spotty calcification), and hemodynamic parameters (fractional flow reserve derived by coronary computed tomographic angiography [FFRCT], change in FFRCT across the lesion [△FFRCT], wall shear stress [WSS], and axial plaque stress [APS]). Correlation analysis, logistic regression, and Cox proportional risk analysis were conducted to understand the relationship between these measures and the occurrence of MACE and assess the value of hemodynamic parameters in predicting the incidence of MACE events and their prognosis. Our study included 86 patients with a total of 134 vessels exhibiting plaque formation and 83 culprit vessels with a subsequent coronary event. Culprit vessels had percent diameter stenosis [%DS] (0.54 ± 0.16 vs. 0.62 ± 0.13, P = 0.003), larger non-calcified plaque volume (45.8 vs. 101.7, P < 0.001), larger low-attenuation plaque volume (3.6 vs. 14.5, P < 0.001), more lesions with ≥ 3 adverse plaque characteristics (APC) (4 vs.26, P = 0.002), and worse hemodynamic features of adverse plaque. FFRCT demonstrated better visualization of maximum achievable flow in the presence of coronary stenosis and better correlation with the stenosis severity, while maximum of wall shear stress (WSSmax) was highly correlated with low-attenuation plaques and APC. The inclusion of hemodynamic parameters improved the efficacy of the predictive model, and a high WSS suggested a higher probability of MACE. Hemodynamic parameters based on CCTA are significantly correlated with plaque morphology. Importantly, integrating CCTA-derived parameters can refine the predictive performance of MACE occurrence.

No-Reference-Based and Noise Level Evaluations of Cinematic Rendering in Bone Computed Tomography.

Cinematic rendering (CR) is a new 3D post-processing technology widely used to produce bone computed tomography (CT) images. This study aimed to evaluate the performance quality of CR in bone CT images using blind quality and noise level evaluations. Bone CT images of the face, shoulder, lumbar spine, and wrist were acquired. Volume rendering (VR), which is widely used in the field of diagnostic medical imaging, was additionally set along with CR. A no-reference-based blind/referenceless image spatial quality evaluator (BRISQUE) and coefficient of variation (COV) were used to evaluate the overall quality of the acquired images. The average BRISQUE values derived from the four areas were 39.87 and 46.44 in CR and VR, respectively. The difference between the two values was approximately 1.16, and the difference between the resulting values increased, particularly in the bone CT image, where metal artifacts were observed. In addition, we confirmed that the COV value improved by 2.20 times on average when using CR compared to VR. This study proved that CR is useful in reconstructing bone CT 3D images and that various applications in the diagnostic medical field will be possible.

Novel motion correction algorithm improves diagnostic performance of CT fractional flow reserve.

OBJECTIVES: This study aimed to investigate the diagnostic performance of computed tomography (CT) fractional flow reserve (CT-FFR) derived from standard images (STD) and images processed via first-generation (SnapShot Freeze, SSF1) and second-generation (SnapShot Freeze 2, SSF2) motion correction algorithms. METHODS: 151 patients who underwent coronary CT angiography (CCTA) and invasive coronary angiography (ICA)/FFR within 3 months were retrospectively included. CCTA images were reconstructed using an iterative reconstruction technique and then further processed through SSF1 and SSF2 algorithms. All images were divided into three groups: STD, SSF1, and SSF2. Obstructive stenosis was defined as a diameter stenosis of ≥ 50 % in the left main artery or ≥ 70 % in other epicardial vessels. Stenosis with an FFR of ≤ 0.8 or a diameter stenosis of ≥ 90 % (as revealed via ICA) was considered ischemic. In patients with multiple lesions, the lesion with lowest CT-FFR was used for patient-level analysis. RESULTS: The overall quality score in SSF2 group (median = 3.67) was markedly higher than that in STD (median = 3) and SSF1 (median = 3) groups (P < 0.001). The best correlation (r = 0.652, P < 0.001) and consistency (mean difference = 0.04) between the CT-FFR and FFR values were observed in the SSF2 group. At the per-lesion level, CT-FFRSSF2 outperformed CT-FFRSSF1 in diagnosing ischemic lesions (area under the curve = 0.887 vs. 0.795, P < 0.001). At the per-patient level, the SSF2 group also demonstrated the highest diagnostic performance. CONCLUSION: The SSF2 algorithm significantly improved CCTA image quality and enhanced its diagnostic performance for evaluating stenosis severity and CT-FFR calculations.

The Curious Case of a 'Maverick' Cementoblastoma!

Introduction: The Cementoblastoma is a benign ectomesenchymal odontogenic neoplasm of the jaw, arising from an exuberant production of cemental tissue continuous with the roots of teeth (usually mandibular posteriors), resulting in a calcified mass adherent with the root apices. Case Presentation: A curious case of a large Cementoblastoma, the size and shape of a ping pong ball, is presented, the first of its kind ever reported to involve the internal / medial / lingual aspect of the mandible, and presenting with unusual and deviant features. Discussion & Conclusion: The Cementoblastoma is usually associated with certain inherent and pathognomonic features, making it rather straightforward to identify and diagnose. Strikingly uncharacteristic clinical, radiographic and histologic attributes presented in this case, made this 'out of the ordinary' and 'Maverick'-like Cementoblastoma, arduous to diagnose, nevertheless, making it an interesting, informative and curious Case Study. This report has brought to light for the first time, several new facets of the Cementoblastoma.

Evaluation of resin infiltration for inhibiting initial caries progression: An in vitro study using Micro-Computed Tomographic analysis.

Objective: To evaluate the changes in lesion depth and mineral density of resin infiltration-treated white spot lesions against a simulated oral environment using thermal and acidic challenges in vitro. Materials and methods: Two enamel slabs were prepared from each buccal surface of permanent human premolars, for a total of 56 slabs. Artificial white spot lesions were induced. One specimen was treated with resin infiltration, while the other was used as an untreated control. A micro-CT was used to assess the lesion depth and mineral density of each specimen. Subsequently, all specimens were subjected to 10,000 cycles of thermocycling and pH cycling for 10 days before being re-evaluated using the micro-CT. Lesion depth and mineral density were examined and compared between before and after aging procedures within each group by the paired sample t-test. The independent samples t-test was utilized to compare lesion depth progression and percentage change of mineral density between groups. Results: After aging, there was both a significant lesion depth progression and a mineral loss in the control and resin infiltration groups. Mean lesion depth progression was 132.88 ± 4.18 µm for the control group and 52.31 ± 4.16 µm for resin infiltration group. Percentage mineral density loss as a percentage for the control and resin infiltration groups were 16.1 ± 0.64 % and 8.83 ± 0.30 %, respectively. The resin infiltration group demonstrated a significantly lower mean lesion depth progression and percentage changes in mineral loss compared to the control group. Conclusions: The lesion depth and mineral density changes in the resin infiltrated-treated group were lower than untreated white spot lesions after aging procedures using thermal and acidic challenges. Clinical significance: Resin infiltration is a promising approach to inhibit the progression of white spot lesions related to the initial stage of dental caries.

Comparative diagnostic efficacy of cranial CT, CTA, and DSA in subarachnoid hemorrhage management: A systematic review and meta-analysis.

INTRODUCTION: Subarachnoid hemorrhage (SAH) is a critical medical condition associated with high morbidity and mortality rates. Timely and accurate diagnosis is crucial for optimal patient outcomes. Cranial computed tomography (CT), computed tomography angiography (CTA), and digital subtraction angiography (DSA) are commonly used imaging modalities for diagnosing SAH, but their comparative diagnostic efficacy remains debated. METHODS: A systematic review and meta-analysis was conducted to evaluate the diagnostic performance of cranial CT, CTA, and DSA in identifying SAH. PubMed, Google scholar, Cochrane Library databases were searched for relevant studies published up to January 2024. Pooled sensitivity, specificity, and the summary receiver operating characteristic (SROC) curve were calculated using Review Manager 5.4. RESULTS: A total of 31 studies involving 10,287 patients were included in the analysis. The pooled sensitivity of cranial CT for detecting SAH was 94.7 % (95 % Confidence Interval, CI) with a specificity of 98.3 % (95 % CI). CTA demonstrated a pooled sensitivity of 94.1 % (95 % CI) and specificity of 93.4 % (95 % CI). DSA showed a pooled sensitivity of 87.7 % (95 % CI) and specificity of 95.8 % (95 % CI). The SROC curve demonstrated discriminatory ability for all modalities. CONCLUSION: Cranial CT, CTA, and DSA are valuable imaging modalities for diagnosing SAH, with high sensitivity and specificity. Cranial CT serves as an initial screening tool, while CTA offers superior sensitivity in detecting aneurysmal SAH. DSA remains essential in specific clinical scenarios. Further prospective studies are needed to validate these findings and refine diagnostic guidelines for SAH.

Cost-effectiveness analysis of routine computed tomography angiography (CTA) for lower extremity penetrating trauma.

BACKGROUND: Routine evaluation with CTA for patients with isolated lower extremity penetrating trauma and normal ankle-brachial-indices (ABI) remains controversial. While prior literature has found normal ABI's (≥0.9) and a normal clinical examination to be adequate for safe discharge, there remains concern for missed injuries which could lead to delayed surgical intervention and unnecessary morbidity. Our hypothesis was that routine CTA after isolated lower extremity penetrating trauma with normal ABIs and clinical examination is not cost-effective. METHODS: We performed a decision-analytic model to evaluate the cost-effectiveness of obtaining a CTA routinely compared to clinical observation and ABI evaluation in hemodynamically normal patients with isolated penetrating lower extremity trauma. Our base case was a patient that sustained penetrating lower extremity trauma with normal ABIs that received a CTA in the trauma bay. Costs, probability, and Quality-Adjusted Life Years (QALYs) were generated from published literature. RESULTS: Clinical evaluation only (no CTA) was cost-effective with a cost of $2056.13 and 0.98 QALYs gained compared to routine CTA which had increased costs of $7449.91 and lower QALYs 0.92. Using one-way sensitivity analysis, routine CTA does not become the cost-effective strategy until the cost of a missed injury reaches $210,075.83. CONCLUSIONS: Patients with isolated, penetrating lower extremity trauma with normal ABIs and clinical examination do not warrant routine CTA as there is no benefit with increased costs.

Heterogeneous-Structure-Based AuNBs@TiO2 Nano-Photosensitizers for Computed Tomography Imaging Guided NIR-II Photodynamic Therapy and Cancer Metastatic Prevention.

Photodynamic therapy (PDT) is a minimally invasive cancer treatment that, despite its significant attention, faces limitations in penetration depth, which restrict its effectiveness. Herein, it is found that gold nanobipyramid (AuNBs) coated with TiO2 can form a core-shell heterogeneous structure (AuNBs@TiO2) with strong absorption at second near infrared (NIR-II) region. A substantial quantity of reactive oxygen species (ROS), including singlet oxygen (1O2), superoxide anion radicals, and hydroxyl radicals, can be rapidly generated when subjecting the AuNBs@TiO2 aqueous suspension to 1064 nm laser irradiation. The quantum yield for sensitization of 1O2 by AuNBs@TiO2 is 0.36 at 1064 nm light excitation. In addition, the Au element as high-Z atoms in the nanosystem can improve the ability of computed tomographic (CT) imaging. As compared to commercial iohexol, the AuNBs@TiO2 nanoparticle exhibits significantly better CT imaging effect, which can be used to guide PDT. In addition, the nano-photosensitizer shows a remarkable therapeutic effect against established solid tumors and prevents tumor metastasis and potentiates immune checkpoint blockade therapy. More importantly, here the great potentials of AuNBs@TiO2 are highlighted as a theranostic platform for CT-guided cancer photodynamic immunotherapy.

Association of Coronary Computed Tomography-Defined Myocardial Bridge With Pre- and Post-Procedural Fractional Flow Reserve in Patients Undergoing Elective Percutaneous Coronary Intervention.

BACKGROUND: Myocardial bridge (MB) is a common coronary anomaly characterized by a tunneled course through the myocardium. Coronary computed tomography angiography (CCTA) can identify MB. The impact of MB detected by CCTA on coronary physiological parameters before and after percutaneous coronary intervention (PCI) is unknown.Methods and Results: We investigated 141 consecutive patients who underwent pre-PCI CCTA and fractional flow reserve (FFR)-guided elective PCI for de novo single proximal lesions in the left anterior descending artery (LAD). We compared clinical demographics and physiological parameters between patients with and without CCTA-defined MB. MB was identified in 46 (32.6%) patients using pre-PCI CCTA. The prevalence of diabetes was higher among patients with MB. Median post-PCI FFR values were significantly lower among patients with than without MB (0.82 [interquartile range 0.79-0.85] vs. 0.85 [interquartile range 0.82-0.89]; P=0.003), whereas pre-PCI FFR values were similar between the 2 groups. Multivariable linear regression analysis revealed that the presence of MB and greater left ventricular mass volume in the LAD territory were independently associated with lower post-PCI FFR values. Multivariable logistic regression analysis also revealed that the presence of MB and lower pre-PCI FFR values were independent predictors of post-PCI FFR values ≤0.80. CONCLUSIONS: CCTA-defined MB independently predicted both lower post-PCI FFR as a continuous variable and ischemic FFR as a categorical variable in patients undergoing elective PCI for LAD.

Anomalous origin of the coronary artery: prevalence and coronary artery disease in adults undergoing coronary tomographic angiography.

BACKGROUND: Anomalous aortic origin of a coronary artery (AAOCA) is a rare congenital coronary anomaly with the potential to cause adverse cardiac events. However, there is limited data on the association between AAOCA and coronary artery disease (CAD). Therefore, the aim of this study is to determine the prevalence and symptoms of patients with AAOCA, as well as investigate the correlation between AAOCA and CAD in a population referred for coronary computed tomographic angiography (CTA). METHODS AND RESULTS: All consecutive patients who underwent CTA from 2010 to 2021 were included. Characteristics, symptoms, coronary related adverse events and CTA information were reviewed by medical records. Separate multivariable cumulative logistic regressions were performed, using the stenosis severity in each of the four coronaries as individual responses and as a combined patient clustered response. Finally, we identified 207 adult patients with AAOCA, the prevalence of AAOCA is 0.23% (207/90,501). Moreover, this study found no significant association between AAOCA and CAD. AAOCA did not contribute to higher rates of hospitalization or adverse cardiac events, including calcification. CONCLUSION: AAOCA is a rare congenital disease that is not associated with increased presence of obstructive CAD in adults.

Evaluation of the non-alcoholic fatty liver fibrosis score in predicting short-term outcomes and severe coronary artery disease in patients undergoing coronary computed tomography angiography.

Introduction: The correlation between non-alcoholic fatty liver disease (NAFLD) and cardiovascular disease is well established. Aim: The objective of this study was to assess the short-term associations of the non-alcoholic fatty liver disease fibrosis score (NFS) with various outcomes, including mortality, severe coronary artery disease, myocardial infarction, and the need for coronary angiography, among patients who underwent coronary computed tomographic angiography (CCTA). Material and methods: In this study, we assessed 499 patients who underwent 640-slice CCTA and evaluated their liver fibrosis using the NFS. The NFS takes into account factors such as age, body mass index, impaired fasting glycemia or diabetes mellitus, aspartate aminotransferase/alanine aminotransferase ratio, platelets, and albumin. Our primary focus was myocardial infarction, the need for coronary angiography, and death. Additionally, we examined the association between NFS and severe coronary artery disease. Results: Patients with a higher NFS had a greater number of coronary angiography procedures and higher Agatston score (p < 0.001), with NFS and Agatston score emerging as independent predictors of severe coronary artery disease and the primary endpoint. An NFS value above -0.92 could predict the primary endpoint with 61% sensitivity and 63% specificity, while an NFS value above -0.88 could predict severe coronary artery disease with 62% sensitivity and 65% specificity. To analyze primary endpoints, the Kaplan-Meier method was used for survival analysis, with NFS groups compared using the log-rank test. During the follow-up period, patients with higher NFS were exposed to primary outcomes at an earlier period (p = 0.009). Conclusions: NFS is an effective predictor of major cardiovascular events such as death, myocardial infarction, severe coronary artery disease, and the need for coronary angiography. These findings underscore the importance of NFS as a valuable tool for risk assessment and early intervention in patients with suspected or confirmed coronary artery disease.

Incidence of acute kidney injury in patients with acute ischaemic stroke undergoing CT angiography (CTA) and CT perfusion (CTP): a systematic review and meta-analysis.

Background and purpose: We conducted a systematic review and meta-analysis to assess the incidence of acute kidney injury (AKI) in patients undergoing CT angiography (CTA) and CT perfusion (CTP) for acute ischaemic stroke (AIS). Concerns over contrast-induced nephropathy (CIN) often lead medical centres to mandate pre-imaging serum creatinine level assessments, causing unnecessary delays. We aim to confirm further the practice of conducting CTA/CTP without first testing creatinine. Methods: We searched PubMed, Cochrane Central and Scopus from inception until March 2023 for studies reporting on AKI in patients with AIS receiving CTA/CTP. Outcomes of interest were (1) the odds of AKI in patients receiving CTA/CTP versus non-contrast CT and (2) the overall incidence of AKI and haemodialysis in patients with AIS undergoing CTA/CTP. Results: Results were pooled using a random effects model. 13 studies were included (5 cohort and 8 single-arm studies) with 5104 patients in total, out of which 4347 patients received CTA/CTP and 757 patients received no contrast. In case-control studies, 4.8% (OR=0.66, 95% CI 0.35 to 1.22, Z=1.32, p=0.19) of patients who received CTA/CTP developed AKI, compared with 7.7% of patients in the control group. Temporary haemodialysis was required for two patients in the analysed studies. Conclusions: Non-randomised evidence suggests that CTA/CTP is not associated with a statistically significant increase in the risk of AKI in patients with stroke. Further well-designed prospective studies are required to explore potential risk factors of CIN in specific patient populations such as diabetes mellitus and chronic kidney disease.

Aberrant right coronary artery in an elderly Nigerian with recent dyspnoea detected on coronary CT angiogram.

An anomalous origin of the right coronary artery has been documented in up to 0.92% of the general population, which is more common than an anomalous origin of the left coronary artery. We present a case of an elderly hypertensive man who developed mild dyspnoea on exertion for 3 months with associated retro-sternal pain as well as occasional palpitation which all tend to subside at rest. An electrocardiogram showed evidence of left atrial enlargement. A coronary computed tomographic angiogram was acquired with a 160-slice scanner which revealed the right coronary artery to originate from the left aortic sinus with a retro-aortic pattern of anatomical course. Vascular wall calcifications were noted with multilevel luminal narrowing on the left anterior descending however distal opacification was adequate. Our case further depicts the reason for keeping in mind anatomical variations while evaluating cardiac pathologies even among Black Africans.

Mandibular Molar with Six Canals, a Rare Entity: A Case Report.

Background: The objective of this report was to highlight the importance of using a dental operating microscope (DOM) to locate supernumerary canals and diagnose variations in root canals using cone-beam computed tomographic (CBCT) images. Case Presentation: A 23-year-old male patient had reported with a pain for 1 months and was referred to evaluate symptomatic apical periodontitis for lower right first permanent molar. Root canal therapy was proposed and conducted with the use of DOM and CBCT. Conclusions: Proper diagnosis and careful clinico-radiological examination are necessary, and it is essential to reinforce the knowledge of the rare morphology of root canals for clinicians.

Estimation of radiographic joint space of the trapeziometacarpal joint with computed tomographic validation.

Purpose: Joint space width (JSW) is a common metric used to evaluate joint structure on plain radiographs. For the hand, quantitative techniques are available for evaluation of the JSW of finger joints; however, such techniques have been difficult to establish for the trapeziometacarpal (TMC) joint. This study aimed to develop a validated method for measuring the radiographic joint space of the healthy TMC joint. Approach: Computed tomographic scans were taken of 15 cadaveric hands. The location of a JSW analysis region on the articular surface of the first metacarpal was established in 3D space and standardized in a 2D projection. The standardized region was applied to simulated radiographic images. A correction factor was defined as the ratio of the CT-based and radiograph-based joint space measurements. Leave-one-out validation was used to correct the radiograph-based measurements. A t-test was used to evaluate the difference between CT-based and corrected radiograph-based measurements (α=0.05). Results: The CT-based and radiograph-based measurements of JSW were 3.61±0.72 mm and 2.18±0.40 mm, respectively. The correction factor for radiograph-based joint space was 1.69±0.41. Before correction, the difference between the CT-based and radiograph-based joint space was 1.43 mm [95% CI: 0.99-1.86 mm; p<0.001]. After correction, the difference was -0.11 mm [95% CI: -0.63-0.41 mm; p=0.669]. Conclusions: Corrected measurements of radiographic TMC JSW agreed well with CT-measured JSW. With in-vivo validation, the developed methodology has potential for automated and accurate radiographic measurement of TMC JSW.

Diagnosing Coronary Artery Disease in the Patient Presenting with Stable Ischemic Heart Disease: The Role of Anatomic versus Functional Testing.

There are unique advantages and disadvantages to functional versus anatomic testing in the work-up of patients who present with symptoms suggestive of obstructive coronary artery disease. Evaluation of these individuals starts with an assessment of pre-test probability, which guides subsequent testing decisions. The choice between anatomic and functional testing depends on this pre-test probability. In general, anatomic testing has particular utility among younger individuals and women; while functional testing can be helpful to rule-in ischemia and guide revascularization decisions. Ultimately, selection of the most appropriate test should be individualized to the patient and clinical scenario.