Lipoprotein subclasses are associated with Hepatic steatosis: insights from the prospective multicenter imaging study for the evaluation of chest pain (PROMISE) clinical trial.

Objectives: To determine the relationship between lipoprotein particle size/number with hepatic steatosis (HS), given its association with traditional lipoproteins and coronary atherosclerosis. Methods: Individuals with available CT data and blood samples enrolled in the PROMISE trial were studied. HS was defined based on CT attenuation. Lipoprotein particle size/number were measured by nuclear magnetic resonance spectroscopy. Principal components analysis (PCA) was used for dimensionality reduction. The association of PCA factors and individual lipoprotein particle size/number with HS were assessed in multivariable regression models. Associations were validated in an independent cohort of 59 individuals with histopathology defined HS. Results: Individuals with HS (n=410/1,509) vs those without (n=1,099/1,509), were younger (59±8 vs 61±8 years) and less often females (47.6 % vs 55.9 %). All PCA factors were associated with HS: factor 1 (OR:1.36, 95 %CI:1.21-1.53), factor 3 (OR:1.75, 95 %CI:1.53-2.02) and factor 4 (OR:1.49; 95 %CI:1.32-1.68) were weighted heavily with small low density lipoprotein (LDL) and triglyceride-rich (TRL) particles, while factor 2 (OR:0.86, 95 %CI:0.77-0.97) and factor 5 (OR:0.74, 95 %CI:0.65-0.84) were heavily loaded with high density lipoprotein (HDL) and larger LDL particles. These observations were confirmed with the analysis of individual lipoprotein particles in PROMISE. In the validation cohort, association between HS and large TRL (OR: 8.16, 95 %CI:1.82-61.98), and mean sizes of TRL- (OR: 2.82, 95 %CI:1.14-9.29) and HDL (OR:0.35, 95 %CI:0.13-0.72) were confirmed. Conclusions: Large TRL, mean sizes of TRL-, and HDL were associated with radiographic and histopathologic HS. The use of lipoprotein particle size/number could improve cardiovascular risk assessment in HS.

Hematocrit and lactate trends help predict outcomes in trauma independent of CT and other clinical parameters.

Background: Hematocrit and lactate have an established role in trauma as indicators of bleeding and cell death, respectively. The wide availability of CT imaging and clinical data poses the question of how these can be used in combination to predict outcomes. Purpose: To assess the utility of hematocrit or lactate trends in predicting intensive care unit (ICU) admission and hospital length of stay (LOS) in patients with torso trauma combined with clinical parameters and injury findings on CT. Materials and Methods: This was a single-center retrospective study of adults with torso trauma in one year. Trends were defined as a unit change per hour. CT findings and clinical parameters were explanatory variables. Outcomes were ICU admission and hospital LOS. Multivariate logistic and negative binomial regression models were used to calculate the odds ratio (OR) and incident rate ratio (IRR). Results: Among 840 patients, 561 (72% males, age 39 ± 18) were included, and 168 patients (30%) were admitted to the ICU. Decreasing hematocrit trend [OR 2.54 (1.41-4.58), p = 0.002] and increasing lactate trend [OR 3.85 (1.35-11.01), p = 0.012] were associated with increased odds of ICU admission. LOS median was 2 (IQR: 1-5) days. Decreasing hematocrit trend [IRR 1.37 (1.13-1.66), p = 0.002] and increasing lactate trend [2.02 (1.43-2.85), p < 0.001] were associated with longer hospital LOS. Conclusion: Hematocrit and lactate trends may be helpful in predicting ICU admission and LOS in torso trauma independent of organ injuries on CT, age, or admission clinical parameters.

Machine learning for malignant versus benign focal liver lesions on US and CEUS: a meta-analysis.

OBJECTIVES: To perform a meta-analysis of the diagnostic performance of learning (ML) algorithms (conventional and deep learning algorithms) for the classification of malignant versus benign focal liver lesions (FLLs) on US and CEUS. METHODS: Available databases were searched for relevant published studies through September 2022. Studies met eligibility criteria if they evaluate the diagnostic performance of ML for the classification of malignant and benign focal liver lesions on US and CEUS. The pooled per-lesion sensitivities and specificities for each modality with 95% confidence intervals were calculated. RESULTS: A total of 8 studies on US, 11 on CEUS, and 1 study evaluating both methods met the inclusion criteria with a total of 34,245 FLLs evaluated. The pooled sensitivity and specificity of ML for the malignancy classification of FLLs were 81.7% (95% CI, 77.2-85.4%) and 84.8% (95% CI, 76.0-90.8%) for US, compared to 87.1% (95% CI, 81.8-91.0%) and 87.0% (95% CI, 83.1-90.1%) for CEUS. In the subgroup analysis of studies that evaluated deep learning algorithms, the sensitivity and specificity of CEUS (n = 4) increased to 92.4% (95% CI, 88.5-95.0%) and 88.2% (95% CI, 81.1-92.9%). CONCLUSIONS: The diagnostic performance of ML algorithms for the malignant classification of FLLs was high for both US and CEUS with overall similar sensitivity and specificity. The similar performance of US may be related to the higher prevalence of DL models in that group.

Artificial intelligence CAD tools in trauma imaging: a scoping review from the American Society of Emergency Radiology (ASER) AI/ML Expert Panel.

BACKGROUND: AI/ML CAD tools can potentially improve outcomes in the high-stakes, high-volume model of trauma radiology. No prior scoping review has been undertaken to comprehensively assess tools in this subspecialty. PURPOSE: To map the evolution and current state of trauma radiology CAD tools along key dimensions of technology readiness. METHODS: Following a search of databases, abstract screening, and full-text document review, CAD tool maturity was charted using elements of data curation, performance validation, outcomes research, explainability, user acceptance, and funding patterns. Descriptive statistics were used to illustrate key trends. RESULTS: A total of 4052 records were screened, and 233 full-text articles were selected for content analysis. Twenty-one papers described FDA-approved commercial tools, and 212 reported algorithm prototypes. Works ranged from foundational research to multi-reader multi-case trials with heterogeneous external data. Scalable convolutional neural network-based implementations increased steeply after 2016 and were used in all commercial products; however, options for explainability were narrow. Of FDA-approved tools, 9/10 performed detection tasks. Dataset sizes ranged from < 100 to > 500,000 patients, and commercialization coincided with public dataset availability. Cross-sectional torso datasets were uniformly small. Data curation methods with ground truth labeling by independent readers were uncommon. No papers assessed user acceptance, and no method included human-computer interaction. The USA and China had the highest research output and frequency of research funding. CONCLUSIONS: Trauma imaging CAD tools are likely to improve patient care but are currently in an early stage of maturity, with few FDA-approved products for a limited number of uses. The scarcity of high-quality annotated data remains a major barrier.

Risk factors for cardiovascular disease among individuals with hepatic steatosis.

Cardiovascular disease (CVD) is the leading cause of mortality in adults with hepatic steatosis (HS). However, risk factors for CVD in HS are unknown. We aimed to identify factors associated with coronary artery disease (CAD) and incident major adverse cardiovascular events (MACE) in individuals with HS. We performed a nested cohort study of adults with HS detected on coronary computed tomography in the PROspective Multicenter Imaging Study for Evaluation of chest pain (PROMISE) trial. Obstructive CAD was defined as ≥50% coronary stenosis. MACE included hospitalization for unstable angina, nonfatal myocardial infarction, or all-cause death. Multivariate modeling, adjusted for age, sex, atherosclerotic CVD (ASCVD) risk score and body mass index, identified factors associated with obstructive CAD. Cox regression, adjusted for ASCVD risk score, determined the predictors of MACE. A total of 959 of 3,756 (mean age 59.4 years, 55.0% men) had HS. Obstructive CAD was present in 15.2% (145 of 959). Male sex (adjusted odds ratio [aOR] = 1.83, 95% confidence interval [CI] 1.18-1.2.84; p = 0.007), ASCVD risk score (aOR = 1.05, 95% CI 1.03-1.07; p < 0.001), and n-terminal pro-b-type natriuretic peptide (NT-proBNP; aOR = 1.90, 95% CI 1.38-2.62; p < 0.001) were independently associated with obstructive CAD. In the 25-months median follow-up, MACE occurred in 4.4% (42 of 959). Sedentary lifestyle (adjusted hazard ratio [aHR] = 2.53, 95% CI 1.27-5.03; p = 0.008) and NT-proBNP (aOR = 1.50, 95% CI 1.01-2.25; p = 0.046) independently predicted MACE. Furthermore, the risk of MACE increased by 3% for every 1% increase in ASCVD risk score (aHR = 1.03, 95% CI 1.01-1.05; p = 0.02). Conclusion: In individuals with HS, male sex, NT-pro-BNP, and ASCVD risk score are associated with obstructive CAD. Furthermore, ASCVD, NT-proBNP, and sedentary lifestyle are independent predictors of MACE. These factors, with further validation, may help risk-stratify adults with HS for incident CAD and MACE.

The Radiology: Artificial Intelligence Trainee Editorial Board: Initial Experience and Future Directions.

In 2019, the journal Radiology: Artificial Intelligence introduced its Trainee Editorial Board (TEB) to offer formal training in medical journalism to medical students, radiology residents and fellows, and research-career trainees. The TEB aims to build a community of radiologists, radiation oncologists, medical physicists, and researchers in fields related to artificial intelligence (AI) in radiology. The program presented opportunities to learn about the editorial process, improve skills in writing and reviewing, advance the field of AI in radiology, and help translate and disseminate AI research. To meet these goals, TEB members contribute actively to the editorial process from peer review to publication, participate in educational webinars, and create and curate content in a variety of forms. Almost all of the contact has been mediated through the web. In this article, we share initial experiences and identify future directions and opportunities.

Gamification in Radiology Training Module Developed During the Society for Imaging Informatics in Medicine Annual Meeting Hackathon.

The purpose of this manuscript is to report our experience in the 2021 SIIM Virtual Hackathon, where we developed a proof-of-concept of a radiology training module with elements of gamification. In the 50 h allotted in the hackathon, we proposed an idea, connected with colleagues from five different countries, and completed an operational proof-of-concept, which was demonstrated live at the hackathon showcase, competing with eight other teams. Our prototype involved participants annotating publicly available chest radiographs of patients with tuberculosis. We showed how we could give experience points to trainees based on annotation precision compared to ground truth radiologists' annotation, ranked in a live leaderboard. We believe that gamification elements could provide an engaging solution for radiology education. Our project was awarded first place out of eight participating hackathon teams.

How to Use YouTube for Radiology Education.

YouTube, the most commonly used free video-sharing platform globally, is increasingly being used as an educational tool in Radiology. Trainees worldwide now have the opportunity to learn about medical imaging at their own pace in the comfort of their homes, without geographical and financial constraints. Unfortunately, because YouTube is an easily accessible platform, it also incurs the risk of disseminating erroneous medical information or low-quality educational content. This article outlines the primary considerations when creating educational content on YouTube, including technical aspects, best practices, and measures to maximize effectiveness and success. Additionally, we discuss the current usage of the platform for Radiology education and its advantages and disadvantages and list some of the most popular Radiology YouTube channels.

Association of Hepatic Steatosis With Major Adverse Cardiovascular Events, Independent of Coronary Artery Disease.

BACKGROUND & AIMS: Hepatic steatosis has been associated with increased risk of major adverse cardiovascular events (MACE) but it is not clear whether steatosis is independently associated with risk of MACE. We investigated whether steatosis is associated with risk of MACE independently of the presence and extent of baseline coronary artery disease, assessed by comprehensive contrast-enhanced computed tomography angiography (CTA). METHODS: We conducted a nested cohort study of 3756 subjects (mean age, 60.6 years; 48.4% men) who underwent coronary CTA at 193 sites in North America, from July 2010 through September 2013, as part of the PROMISE study, which included noninvasive cardiovascular analyses of symptomatic outpatients without coronary artery disease. Independent core laboratory readers measured hepatic and splenic attenuation, using non-contrast computed tomography images to identify steatosis, and evaluated coronary plaques and stenosis in coronary CTA images. We collected data on participants' cardiovascular risk factors, presence of metabolic syndrome, and body mass index. The primary endpoint was an adjudicated composite of MACE (death, myocardial infarction, or unstable angina) during a median follow-up time of 25 months. RESULTS: Among the 959 subjects who had steatosis (25.5% of the cohort), 42 had MACE (4.4%), whereas among the 2797 subjects without steatosis, 73 had MACE (2.6%) (hazard ratio [HR] for MACE in subjects with steatosis, 1.69; 95% CI, 1.16-2.48; P = .006 for MACE in subjects with vs without steatosis). This association remained after adjustment for atherosclerotic cardiovascular disease risk scores, significant stenosis, and metabolic syndrome (adjusted HR, 1.72; 95% CI, 1.16-2.54; P = .007) or obesity (adjusted HR, 1.75; 95% CI, 1.19-2.59; P = .005). Steatosis remained independently associated with MACE after adjustment for all CTA measures of plaques and stenosis. CONCLUSIONS: Hepatic steatosis is associated with MACE independently of other cardiovascular risk factors or extent of coronary artery disease. Strategies to reduce steatosis might reduce risk of MACE. ClinicalTrials.gov no: NCT01174550.

Solitary intramuscular myofibroma in an adult: Case report and MR imaging findings.

Myofibroma is a benign, soft tissue neoplasm that predominantly affects infants and young children. Most occur in the skin or subcutaneous tissues, with a predilection for the head and neck regions. We describe the magnetic resonance (MR) imaging and histophathologic findings of a rare case of intramuscular myofibroma of the right deltoid in a healthy 30-year-old male. MR imaging revealed a well-circumscribed intramuscular mass, with isointense signal on T1-weighted images, hyperintense signal on T2-weighed images, and a "target-sign" with peripheral rim enhancement after gadolinium administration. The lesion was surgically excised with no complications, and the histopathologic analysis revealed the typical morphologic and histochemical markers of a myofibroma. We conclude that, although rare, myofibroma can be considered in the differential diagnosis of adults with lesions the above signal characteristics.

Early trends and predictors of renal function following computed tomography-guided percutaneous cryoablation of a renal mass in patients with and without prior renal impairment.

OBJECTIVE: To assess trends and predictors of the glomerular filtration rate (GFR) after renal mass cryoablation in patients with and without history of renal impairment. MATERIALS AND METHODS: This was a retrospective study of 39 patients who underwent computed tomography-guided percutaneous cryoablation of a renal mass, divided into two groups: those with prior renal impairment (PRI+); and those without prior renal impairment (PRI-). The GFR trend and the chronic kidney disease stage were evaluated at baseline, as well as at 1, 6, and 12 months after cryoablation. Predictors of GFR at 1 and 6 months were modeled with linear regression. RESULTS: In both groups, the mean GFR at 1 month and 6 months was significantly lower than at baseline (p < 0.001 and p = 0.01, respectively). Although the GFR was lower across all time points in the PRI+ group (-26.1; p < 0.001), the overall trend was not statistically different from that observed in the PRI- group (p = 0.89). Univariate analysis showed that the decline in GFR at 1 and 6 months correlated with the baseline GFR (0.77 and 0.63; p < 0.001 and p = 0.03, respectively) and with the size of the ablation zone (-7.6 and -12.84, respectively; p = 0.03 for both). However, in the multivariate model, baseline GFR was predictive only of GFR at 1 month (p < 0.001). CONCLUSION: The trend in GFR decline after cryoablation is similar for patients with and without a history of renal impairment. Baseline GFR predicts the mean GFR in the early post-cryoablation period.

OBJETIVO: Medir as tendências iniciais da função renal pela taxa de filtração glomerular (TFG) em pacientes com e sem comprometimento renal prévio após crioablação renal. MATERIAIS E MÉTODOS: Este é um estudo retrospectivo de 39 pacientes submetidos a crioablação percutânea guiada por tomografia computadorizada de massa renal. Os pacientes foram divididos em dois grupos: com comprometimento renal prévio (CRP+) e sem comprometimento renal prévio (CRP-). As tendências da TFG foram avaliadas nos tempos 0, 1, 6 e 12 meses com o estadiamento de doença renal crônica. Preditores da TFG em 1 e 6 meses foram modelados usando regressão linear. RESULTADOS: Em ambos os grupos houve declínio da TFG média após 1 e 6 meses (p < 0,001 e p = 0,01, respectivamente). Apesar de o grupo CRP+ demonstrar média menor da TFG em cada um dos tempos (−26,1; p < 0,001), a tendência de forma geral não foi estatisticamente diferente do grupo CRP- (p = 0,89). Análise univariada mostrou correlação da TFG no tempo 0 (0,77 e 0,63; p < 0,001 e p = 0,03, respectivamente) e tamanho da ablação (−7,6 e −12,84; p = 0,03), com declínio em 1 e 6 meses. Porém, no modelo multivariado, apenas a TFG no tempo 0 foi preditiva da TFG em 1 mês (p < 0,001). CONCLUSÃO: A curva de tendência de declínio da TFG após crioablação foi similar entre os pacientes dos grupos CRP+ e CRP-, sem mudanças no estadiamento de função renal. A TFG no tempo 0 foi preditiva da TFG média no período de crioablação inicial.

Early trends and predictors of renal function following computed tomography-guided percutaneous cryoablation of a renal mass in patients with and without prior renal impairment / Tendências iniciais e preditores de função renal após crioablação percutânea guiada por tomografia computadorizada de massa renal em pacientes com e sem comprometimento renal prévio

Abstract Objective: To assess trends and predictors of the glomerular filtration rate (GFR) after renal mass cryoablation in patients with and without history of renal impairment. Materials and Methods: This was a retrospective study of 39 patients who underwent computed tomography-guided percutaneous cryoablation of a renal mass, divided into two groups: those with prior renal impairment (PRI+); and those without prior renal impairment (PRI−). The GFR trend and the chronic kidney disease stage were evaluated at baseline, as well as at 1, 6, and 12 months after cryoablation. Predictors of GFR at 1 and 6 months were modeled with linear regression. Results: In both groups, the mean GFR at 1 month and 6 months was significantly lower than at baseline (p < 0.001 and p = 0.01, respectively). Although the GFR was lower across all time points in the PRI+ group (−26.1; p < 0.001), the overall trend was not statistically different from that observed in the PRI− group (p = 0.89). Univariate analysis showed that the decline in GFR at 1 and 6 months correlated with the baseline GFR (0.77 and 0.63; p < 0.001 and p = 0.03, respectively) and with the size of the ablation zone (−7.6 and −12.84, respectively; p = 0.03 for both). However, in the multivariate model, baseline GFR was predictive only of GFR at 1 month (p < 0.001). Conclusion: The trend in GFR decline after cryoablation is similar for patients with and without a history of renal impairment. Baseline GFR predicts the mean GFR in the early post-cryoablation period.

Resumo Objetivo: Medir as tendências iniciais da função renal pela taxa de filtração glomerular (TFG) em pacientes com e sem comprometimento renal prévio após crioablação renal. Materiais e Métodos: Este é um estudo retrospectivo de 39 pacientes submetidos a crioablação percutânea guiada por tomografia computadorizada de massa renal. Os pacientes foram divididos em dois grupos: com comprometimento renal prévio (CRP+) e sem comprometimento renal prévio (CRP-). As tendências da TFG foram avaliadas nos tempos 0, 1, 6 e 12 meses com o estadiamento de doença renal crônica. Preditores da TFG em 1 e 6 meses foram modelados usando regressão linear. Resultados: Em ambos os grupos houve declínio da TFG média após 1 e 6 meses (p < 0,001 e p = 0,01, respectivamente). Apesar de o grupo CRP+ demonstrar média menor da TFG em cada um dos tempos (−26,1; p < 0,001), a tendência de forma geral não foi estatisticamente diferente do grupo CRP- (p = 0,89). Análise univariada mostrou correlação da TFG no tempo 0 (0,77 e 0,63; p < 0,001 e p = 0,03, respectivamente) e tamanho da ablação (−7,6 e −12,84; p = 0,03), com declínio em 1 e 6 meses. Porém, no modelo multivariado, apenas a TFG no tempo 0 foi preditiva da TFG em 1 mês (p < 0,001). Conclusão: A curva de tendência de declínio da TFG após crioablação foi similar entre os pacientes dos grupos CRP+ e CRP-, sem mudanças no estadiamento de função renal. A TFG no tempo 0 foi preditiva da TFG média no período de crioablação inicial.

Amyloidosis in the head and neck: CT findings with clinicopathological correlation.

PURPOSE: To characterize the CT imaging features of head and neck amyloidosis and correlate with extent of disease and clinical outcomes. MATERIALS AND METHODS: This retrospective study included 80 patients with head and neck amyloidosis who underwent soft tissue neck CT imaging between November 2003 and April 2018. The CT imaging features including lesion distribution, morphology (focal, diffuse/circumferential, or combined), presence and pattern of calcification, (punctate or diffuse), and thickness of airway lesion were evaluated and compared with the extent of amyloidosis (localized or systemic), and clinical course (stable, no recurrence, or progression requiring repeated surgical treatment). RESULTS: Localized disease (83.8%, 67/80) was most common with AL type (97.6%, 41/42) representing nearly all cases of head and neck amyloidosis. The larynx was the most frequently affected organ (60.0%, 48/80), specifically the glottis (43.8%, 35/80). Calcification was seen in 65.0% of cases (52/80). Non-airway or tongue lesions were significantly associated with systemic (92.3%, 12/13) as opposed to localized amyloidosis (4.5%, 3/67; P < 0.001). Repeated surgical treatment was significantly associated with laryngeal amyloidosis (35.3%, 12/34; P = 0.002) and multi-centric disease (33.3%, 10/30; P = 0.048). Airway wall thickness in patients who required repeated surgical treatment was significantly greater than in patients with stable or no recurrent disease (P = 0.016). CONCLUSION: Knowledge of the imaging features of head and neck amyloidosis can aid the diagnosis, disease monitoring, and prediction of patients requiring repeated surgical intervention.

Prognostic Value of Coronary CTA in Stable Chest Pain: CAD-RADS, CAC, and Cardiovascular Events in PROMISE.

OBJECTIVES: The purpose of this study was to compare Coronary Artery Disease Reporting and Data System (CAD-RADS) to traditional stenosis categories and the coronary artery calcium score (CACS) for predicting cardiovascular events in patients with stable chest pain and suspected coronary artery disease (CAD). BACKGROUND: The 2016 CAD-RADS has been established to standardize the reporting of CAD on coronary CT angiography (CTA). METHODS: PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) trial participants' CTAs were assessed by a central CT core laboratory for CACS, traditional stenosis-based categories, and modified CAD-RADS grade including high-risk coronary plaque (HRP) features. Traditional stenosis categories and CAD-RADS grade were compared for the prediction of the composite endpoint of death, myocardial infarction, or hospitalization for unstable angina over a median follow-up of 25 months. Incremental prognostic value over traditional risk factors and CACS was assessed. RESULTS: In 3,840 eligible patients (mean age: 60.4 ± 8.2 years; 49% men), 3.0% (115) experienced events. CAD-RADS (concordance statistic [C-statistic] 0.747) had significantly higher discriminatory value than traditional stenosis-based assessments (C-statistic 0.698 to 0.717; all p for comparison ≤0.001). With no plaque (CAD-RADS 0) as the baseline, the hazard ratio (HR) for an event increased from 2.43 (95% confidence interval [CI]: 1.16 to 5.08) for CAD-RADS 1 to 21.84 (95% CI: 8.63 to 55.26) for CAD-RADS 4b and 5. In stepwise nested models, CAD-RADS added incremental prognostic value beyond ASCVD risk score and CACS (C-statistic 0.776 vs. 0.682; p < 0.001), and added incremental value persisted in all CACS strata. CONCLUSIONS: These data from a large representative contemporary cohort of patients undergoing coronary CTA for stable chest pain support the prognostic value of CAD-RADS as a standard reporting system for coronary CTA.

Using CT texture analysis to differentiate cystic and cystic-appearing odontogenic lesions.

PURPOSE: Cystic and cystic-appearing odontogenic lesions of the jaw may appear similar on CT imaging. Accurate diagnosis is often difficult although the relationship of the lesion to the tooth root or crown may offer a clue to the etiology. The purpose of this study was to evaluate CT texture analysis as an aid in differentiating cystic and cystic-appearing odontogenic lesions of the jaw. METHODS: This was an IRB-approved retrospective study including 42 pathology-proven dentigerous cysts, 37 odontogenic keratocysts, and 19 ameloblastomas. Each lesion was manually segmented on axial CT images, and textural features were analyzed using an in-house-developed Matlab-based texture analysis program that extracted 47 texture features from each segmented volume. Statistical analysis was performed comparing all pairs of the three types of lesions. RESULTS: Pairwise analysis revealed that nine histogram features, one GLCM feature, three GLRL features, two Laws features, four GLGM features and two Chi-square features showed significant differences between dentigerous cysts and odontogenic keratocysts. Four histogram features and one Chi-square feature showed significant differences between odontogenic keratocysts and ameloblastomas. Two histogram features showed significant differences between dentigerous cysts and ameloblastomas. CONCLUSIONS: CT texture analysis may be useful as a noninvasive method to obtain additional quantitative information to differentiate cystic and cystic-appearing odontogenic lesions of the jaw.

CT Texture Analysis and Machine Learning Improve Post-ablation Prognostication in Patients with Adrenal Metastases: A Proof of Concept.

INTRODUCTION: To assess the performance of pre-ablation computed tomography texture features of adrenal metastases to predict post-treatment local progression and survival in patients who underwent ablation using machine learning as a prediction tool. MATERIALS AND METHODS: This is a pilot retrospective study of patients with adrenal metastases undergoing ablation. Clinical variables were collected. Thirty-two texture features were extracted from manually segmented adrenal tumors. A univariate cox proportional hazard model was used for prediction of local progression and survival. A linear support vector machine (SVM) learning technique was applied to the texture features and clinical variables, with leave-one-out cross-validation. Receiver operating characteristic analysis and the area under the curve (AUC) were used to assess performance between using clinical variables only versus clinical variables and texture features. RESULTS: Twenty-one patients (61% male, age 64.1 ± 10.3 years) were included. Mean time to local progression was 29.8 months. Five texture features exhibited association with progression (p < 0.05). The SVM model based on clinical variables alone resulted in an AUC of 0.52, whereas the SVM model that included texture features resulted in an AUC 0.93 (p = 0.01). Mean overall survival was 35 months. Fourteen texture features were associated with survival in the univariate model (p < 0.05). While the trained SVM model based on clinical variables resulted in an AUC of 0.68, the SVM model that included texture features resulted in an AUC of 0.93 (p = 0.024). DISCUSSION: Pre-ablation texture analysis and machine learning improve local tumor progression and survival prediction in patients with adrenal metastases who undergo ablation.

Acute promyelocytic leukaemia presenting as necrotising fasciitis of the perineum (Fournier gangrene).

We present a case of an unusual presentation of acute promyelocytic leukaemia (APML), which presented with Fournier gangrene (FG). A 38-year-old man presented with malaise, groin swelling, anal bleeding, fever and was found to have FG. Initial workup revealed pancytopaenia, borderline low fibrinogen, prolonged international normalized ratio (INR), which raised the suspicion for leukaemia. The peripheral blood differential revealed leucopaenia with absolute neutropaenia and a 5% abnormal promyelocytes but no blasts, suspicious for APML. Bone marrow biopsy was performed and fluorescence in situ hydridization (FISH), karyotype and PCR confirmed a t(15;17) translocation, establishing a diagnosis of APML. After 1 month of therapy for intermediate risk APML with All-trans retinoic acid (ATRA) and arsenic trioxide (ATO), repeat chromosomal analysis and repeat bone marrow biopsy revealed no evidence of residual APML. After the consolidation phase was started with ATRA and ATO regimen, the wound healed after 2 months and the patient achieved complete remission.

The effect of emphysema on readmission and survival among smokers with heart failure.

Heart Failure (HF) and chronic obstructive pulmonary disease (COPD) are morbid diseases that often coexist. In patients with coexisting disease, COPD is an independent risk factor for readmission and mortality. However, spirometry is often inaccurate in those with active heart failure. Therefore, we investigated the association between the presence of emphysema on computed tomography (CT) and readmission rates in smokers admitted with heart failure (HF). The cohort included a consecutive group of smokers discharged with HF from a tertiary center between January 1, 2014 and April 1, 2014 who also had a CT of the chest for dyspnea. The primary endpoint was any readmission for HF before April 1, 2016; secondary endpoints were 30-day readmission for HF, length of stay and all-cause mortality. Over the study period, there were 225 inpatient smokers with HF who had a concurrent chest CT (155 [69%] males, age 69±11 years, ejection fraction [EF] 46±18%, 107 [48%] LVEF of < 50%). Emphysema on CT was present in 103 (46%) and these were older, had a lower BMI, more pack-years, less diabetes and an increased afterload. During a follow-up of 2.1 years, there were 110 (49%) HF readmissions and 55 (24%) deaths. When separated by emphysema on CT, any readmission, 30-day readmission, length of stay and mortality were higher among HF patients with emphysema. In multivariable regression, emphysema by CT was associated with a two-fold higher (adjusted HR 2.11, 95% CI 1.41-3.15, p < 0.001) risk of readmission and a trend toward increased mortality (adjusted HR 1.70 95% CI 0.86-3.34, p = 0.12). In conclusion, emphysema by CT is a frequent finding in smokers hospitalized with HF and is associated with adverse outcomes in HF. This under recognized group of patients with both emphysema and heart failure may benefit from improved recognition and characterization of their co-morbid disease processes and optimization of therapies for their lung disease.