Brain Network Allostasis after Chronic Alcohol Drinking Is Characterized by Functional Dedifferentiation and Narrowing.

Alcohol use disorder (AUD) causes complex alterations in the brain that are poorly understood. The heterogeneity of drinking patterns and the high incidence of comorbid factors compromise mechanistic investigations in AUD patients. Here we used male Marchigian Sardinian alcohol-preferring (msP) rats, a well established animal model of chronic alcohol drinking, and a combination of longitudinal resting-state fMRI and manganese-enhanced MRI to provide objective measurements of brain connectivity and activity, respectively. We found that 1 month of chronic alcohol drinking changed the correlation between resting-state networks. The change was not homogeneous, resulting in the reorganization of pairwise interactions and a shift in the equilibrium of functional connections. We identified two fundamentally different forms of network reorganization. First is functional dedifferentiation, which is defined as a regional increase in neuronal activity and overall correlation, with a concomitant decrease in preferential connectivity between specific networks. Through this mechanism, occipital cortical areas lost their specific interaction with sensory-insular cortex, striatal, and sensorimotor networks. Second is functional narrowing, which is defined as an increase in neuronal activity and preferential connectivity between specific brain networks. Functional narrowing strengthened the interaction between striatal and prefrontocortical networks, involving the anterior insular, cingulate, orbitofrontal, prelimbic, and infralimbic cortices. Importantly, these two types of alterations persisted after alcohol discontinuation, suggesting that dedifferentiation and functional narrowing rendered persistent network states. Our results support the idea that chronic alcohol drinking, albeit at moderate intoxicating levels, induces an allostatic change in the brain functional connectivity that propagates into early abstinence.SIGNIFICANCE STATEMENT Excessive consumption of alcohol is positioned among the top five risk factors for disease and disability. Despite this priority, the transformations that the nervous system undergoes from an alcohol-naive state to a pathologic alcohol drinking are not well understood. In our study, we use an animal model with proven translational validity to study this transformation longitudinally. The results show that shortly after chronic alcohol consumption there is an increase in redundant activity shared by brain structures, and the specific communication shrinks to a set of pathways. This functional dedifferentiation and narrowing are not reversed immediately after alcohol withdrawal but persist during early abstinence. We causally link chronic alcohol drinking with an early and abstinence-persistent retuning of the functional equilibrium of the brain.

Application of machine learning algorithms in thermal images for an automatic classification of lumbar sympathetic blocks.

PURPOSE: There are no previous studies developing machine learning algorithms in the classification of lumbar sympathetic blocks (LSBs) performance using infrared thermography data. The objective was to assess the performance of different machine learning algorithms to classify LSBs carried out in patients diagnosed with lower limbs Complex Regional Pain Syndrome as successful or failed based on the evaluation of thermal predictors. METHODS: 66 LSBs previously performed and classified by the medical team were evaluated in 24 patients. 11 regions of interest on each plantar foot were selected within the thermal images acquired in the clinical setting. From every region of interest, different thermal predictors were extracted and analysed in three different moments (minutes 4, 5, and 6) along with the baseline time (just after the injection of a local anaesthetic around the sympathetic ganglia). Among them, the thermal variation of the ipsilateral foot and the thermal asymmetry variation between feet at each minute assessed and the starting time for each region of interest, were fed into 4 different machine learning classifiers: an Artificial Neuronal Network, K-Nearest Neighbours, Random Forest, and a Support Vector Machine. RESULTS: All classifiers presented an accuracy and specificity higher than 70%, sensitivity higher than 67%, and AUC higher than 0.73, and the Artificial Neuronal Network classifier performed the best with a maximum accuracy of 88%, sensitivity of 100%, specificity of 84% and AUC of 0.92, using 3 predictors. CONCLUSION: These results suggest thermal data retrieved from plantar feet combined with a machine learning-based methodology can be an effective tool to automatically classify LSBs performance.

Clinical results of lumbar sympathetic blocks in lower limb complex regional pain syndrome using infrared thermography as a support tool.

AIM: To describe the clinical outcomes for a group of complex regional pain syndrome patients using infrared thermography as an intraprocedural support tool when undertaking fluoroscopy-guided lumbar sympathetic blocks. SUBJECTS: 27 patients with lower limb complex regional pain syndrome accompanied by severe pain and persistent functional impairment. METHODS: A series of three fluoroscopic-guided lumbar sympathetic blocks with local anesthetic and corticoids using infrared thermography as an intraprocedural support tool were performed. Clinical variables were collected at baseline, prior to each block, and one, three, and six months after blocks in a standardized checklist assessing each of the clinical categories of complex regional pain syndrome stipulated in the Budapest criteria. RESULTS: 23.75% of the blocks required more than one chance to achieve the desired thermal pattern and therefore to be considered as successful. A decrease in pain measured on a visual analogic scale was observed at all time points compared to pre-blockade data, but only 37% of the cases were categorized as responders, representing a ≥ 30% decrease in VAS, with the disappearance of pain at rest. An improvement of most of the clinical variables recorded was observed, such as tingling, edema, perception of thermal asymmetry, difference in coloring and sweating. There was a significant decrease of neuropathic pain and improvement of functional limitation. Logistic regression analysis showed the main variable to explain the probability of being a responder was immobilization time (odds ratio of 0.89). CONCLUSION: A series of fluoroscopy-guided lumbar sympathetic blocks controlled by infrared thermography in the treatment of lower limb CRPS showed a responder rate of 37%.

Sex Effect in the Decision to Perform Invasive Coronary Angiography in Patients With Chronic Coronary Syndrome After Undergoing Vasodilator Stress MRI.

BACKGROUND: Stress cardiac MRI permits comprehensive evaluation of patients with known or suspected chronic coronary syndromes (CCS). The impact of sex on the use of invasive cardiac angiography (ICA) after vasodilator stress cardiac MRI is unclear. PURPOSE: To evaluate the impact of sex on ICA use after vasodilator stress cardiac MRI. STUDY TYPE: Retrospective. POPULATION: A total of 6229 consecutive patients (age [mean ± standard deviation] 65.2 ± 11.5 years, 38.1% women). FIELD STRENGTH/SEQUENCE: A 5-T; a steady-state free-precession cine sequence; stress first-pass perfusion imaging; late enhancement imaging. ASSESSMENT: Patients underwent vasodilator stress cardiac MRI for known or suspected CCS. The ischemic burden (at stress first-pass perfusion imaging) was computed (17-segment model). STATISTICAL TESTS: Multivariate logistic regression was used to evaluate the potential differential association between ischemic burden and use of cardiac MRI-related ICA across sex. RESULTS: A total of 1109 (17.8%) patients were referred to ICA, among which there were significantly more men (762, 19.7%) than women (347, 14.6%). Overall, after multivariate adjustment, female sex was not associated with lower use of ICA (odds ratio [OR] = 0.99; confidence interval [CI] 95%: 0.84-1.18, P = 0.934). However, significant sex differences were detected across ischemic burden. Whereas women with nonischemic vasodilator stress cardiac MRI (0 ischemic segments) were less commonly submitted to ICA (OR = 0.49; CI 95%: 0.35-0.69) in patients with ischemia (>1 ischemic segment), adjusted use of ICA was more frequent in women than men (OR = 1.27; CI 95%: 1.1-1.5). DATA CONCLUSIONS: In patients with known or suspected CCS submitted to undergo vasodilator stress cardiac MRI, cardiac MRI-related ICA may be overused in men without ischemia. Furthermore, ICA referral in patients with negative ischemia resulted in greater odds of revascularization in men. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 5.

Magnetic Resonance Assessment of Left Ventricular Ejection Fraction at Any Time Post-Infarction for Prediction of Subsequent Events in a Large Multicenter STEMI Registry.

BACKGROUND: Magnetic resonance imaging (MRI) is the most accurate imaging technique for left ventricular ejection fraction (LVEF) quantification, but as yet the prognostic value of LVEF assessment at any time after ST-segment elevation myocardial infarction (STEMI) for subsequent major adverse cardiac event (MACE) prediction is uncertain. PURPOSE: To explore the prognostic impact of MRI-derived LVEF at any time post-STEMI to predict subsequent MACE (cardiovascular death or re-admission for acute heart failure). STUDY TYPE: Prospective. POPULATION: One thousand thirteen STEMI patients were included in a multicenter registry. FIELD STRENGTH/SEQUENCE: 1.5-T. Balanced steady-state free precession (cine imaging) and segmented inversion recovery steady-state free precession (late gadolinium enhancement) sequences. ASSESSMENT: Post-infarction MRI-derived LVEF (reduced [r]: <40%; mid-range [mr]: 40%-49%; preserved [p]: ≥50%) was sequentially quantified at 1 week and after >3 months of follow-up. STATISTICAL TESTS: Multi-state Markov model to determine the prognostic value of each LVEF state (r-, mr- or p-) at any time point assessed to predict subsequent MACE. A P-value <0.05 was considered to be statistically significant. RESULTS: During a 6.2-year median follow-up, 105 MACE (10%) were registered. Transitions toward improved LVEF predominated and only r-LVEF (at any time assessed) was significantly related to a higher incidence of subsequent MACE. The observed transitions from r-LVEF, mr-LVEF, and p-LVEF states to MACE were: 15.3%, 6%, and 6.7%, respectively. Regarding the adjusted transition intensity ratios, patients in r-LVEF state were 4.52-fold more likely than those in mr-LVEF state and 5.01-fold more likely than those in p-LVEF state to move to MACE state. Nevertheless, no significant differences were found in transitions from mr-LVEF and p-LVEF states to MACE state (P-value = 0.6). DATA CONCLUSION: LVEF is an important MRI index for simple and dynamic post-STEMI risk stratification. Detection of r-LVEF by MRI at any time during follow-up identifies a subset of patients at high risk of subsequent events. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.

Prognostic value of cardiac magnetic resonance early after ST-segment elevation myocardial infarction in older patients.

BACKGROUND: older patients with ST-segment elevation myocardial infarction (STEMI) represent a very high-risk population. Data on the prognostic value of cardiac magnetic resonance (CMR) in this scenario are scarce. METHODS: the registry comprised 247 STEMI patients over 70 years of age treated with percutaneous intervention and included in a multicenter registry. Baseline characteristics, echocardiographic parameters and CMR-derived left ventricular ejection fraction (LVEF, %), infarct size (% of left ventricular mass) and microvascular obstruction (MVO, number of segments) were prospectively collected. The additional prognostic power of CMR was assessed using adjusted C-statistic, net reclassification index (NRI) and integrated discrimination improvement index (IDI). RESULTS: during a 4.8-year mean follow-up, the number of first major adverse cardiac events (MACE) was 66 (26.7%): 27 all-cause deaths and 39 re-admissions for acute heart failure. Predictors of MACE were GRACE score (HR 1.03 [1.02-1.04], P < 0.001), CMR-LVEF (HR 0.97 [0.95-0.99] per percent increase, P = 0.006) and MVO (HR 1.24 [1.09-1.4] per segment, P = 0.001). Adding CMR data significantly improved MACE prediction compared to the model with baseline and echocardiographic characteristics (C-statistic 0.759 [0.694-0.824] vs. 0.685 [0.613-0.756], NRI = 0.6, IDI = 0.08, P < 0.001). The best cut-offs for independent variables were GRACE score > 155, LVEF < 40% and MVO ≥ 2 segments. A simple score (0, 1, 2, 3) based on the number of altered factors accurately predicted the MACE per 100 person-years: 0.78, 5.53, 11.51 and 78.79, respectively (P < 0.001). CONCLUSIONS: CMR data contribute valuable prognostic information in older patients submitted to undergo CMR soon after STEMI. The Older-STEMI-CMR score should be externally validated.

Increased network centrality of the anterior insula in early abstinence from alcohol.

Abnormal resting-state functional connectivity, as measured by functional magnetic resonance imaging (MRI), has been reported in alcohol use disorders (AUD), but findings are so far inconsistent. Here, we exploited recent developments in graph-theoretical analyses, enabling improved resolution and fine-grained representation of brain networks, to investigate functional connectivity in 35 recently detoxified alcohol dependent patients versus 34 healthy controls. Specifically, we focused on the modular organization, that is, the presence of tightly connected substructures within a network, and on the identification of brain regions responsible for network integration using an unbiased approach based on a large-scale network composed of more than 600 a priori defined nodes. We found significant reductions in global connectivity and region-specific disruption in the network topology in patients compared with controls. Specifically, the basal brain and the insular-supramarginal cortices, which form tightly coupled modules in healthy subjects, were fragmented in patients. Further, patients showed a strong increase in the centrality of the anterior insula, which exhibited stronger connectivity to distal cortical regions and weaker connectivity to the posterior insula. Anterior insula centrality, a measure of the integrative role of a region, was significantly associated with increased risk of relapse. Exploratory analysis suggests partial recovery of modular structure and insular connectivity in patients after 2 weeks. These findings support the hypothesis that, at least during the early stages of abstinence, the anterior insula may drive exaggerated integration of interoceptive states in AUD patients with possible consequences for decision making and emotional states and that functional connectivity is dynamically changing during treatment.

Low-Power Lossless Data Compression for Wireless Brain Electrophysiology.

Wireless electrophysiology opens important possibilities for neuroscience, especially for recording brain activity in more natural contexts, where exploration and interaction are not restricted by the usual tethered devices. The limiting factor is transmission power and, by extension, battery life required for acquiring large amounts of neural electrophysiological data. We present a digital compression algorithm capable of reducing electrophysiological data to less than 65.5% of its original size without distorting the signals, which we tested in vivo in experimental animals. The algorithm is based on a combination of delta compression and Huffman codes with optimizations for neural signals, which allow it to run in small, low-power Field-Programmable Gate Arrays (FPGAs), requiring few hardware resources. With this algorithm, a hardware prototype was created for wireless data transmission using commercially available devices. The power required by the algorithm itself was less than 3 mW, negligible compared to the power saved by reducing the transmission bandwidth requirements. The compression algorithm and its implementation were designed to be device-agnostic. These developments can be used to create a variety of wired and wireless neural electrophysiology acquisition systems with low power and space requirements without the need for complex or expensive specialized hardware.

Neuroimaging reveals functionally distinct neuronal networks associated with high-level alcohol consumption in two genetic rat models.

Human imaging data suggest that the motivational processes associated with alcohol reward are reflected in the patterns of neural activation after alcohol or alcohol-related cues. In animal models of alcohol drinking, however, the changes in brain activation during voluntary alcohol ingestion are poorly known. In order to improve the translational utility of animal models, we examined alcohol-induced functional brain activation in Alko Alcohol (AA) and Marchigian-Sardinian alcohol-preferring (msP) rats that drink voluntarily high levels of alcohol, but exhibit widely different neurochemical and behavioral traits cosegregated with alcohol preference. Brain imaging was performed using manganese-enhanced MRI (MEMRI), which is based on accumulation of Mn2+ ions in activated neurons, allowing the identification of functional neuronal networks recruited during specific behaviors in awake animals during a subsequent imaging session under anesthesia. MEMRI was performed following 4 weeks of voluntary alcohol drinking, using water drinking as the control. Despite similar levels of alcohol drinking, strikingly different alcohol-induced neuronal activity patterns were observed in AA and msP rats. Overall, functional activation in the AA rats was more widespread, involving large cortical areas and subcortical structures, such as the bed nucleus of the stria terminalis, preoptic area, hypothalamus, periaqueductal grey, and substantia nigra. In the msP rats, however, alcohol-related activation was largely confined to prefrontal cortical regions and insular cortex, and olfactory areas. Overlapping areas of activation found in both rat lines included the nucleus accumbens, prelimbic, orbital, and insular cortex. In conclusion, our data reveal strikingly different brain circuits associated with alcohol drinking in two genetically different rat lines and suggest innately different motivational and behavioral processes driving alcohol drinking. These findings have important implications for the use of these lines in translational alcohol research.

Quantitative Analysis of Real-Time Infrared Thermography for the Assessment of Lumbar Sympathetic Blocks: A Preliminary Study.

Lumbar sympathetic blocks (LSBs) are commonly performed to treat pain ailments in the lower limbs. LSBs involve injecting local anesthetic around the nerves. The injection is guided by fluoroscopy which is sometimes considered to be insufficiently accurate. The main aim was to analyze the plantar foot skin temperature data acquired while performing LSBs in patients with complex regional pain syndrome (CRPS) affecting the lower limbs. Forty-four LSBs for treating lower limb CRPS in 13 patients were assessed. Pain medicine physicians visualized the infrared thermography (IRT) video in real time and classified the performance depending on the observed thermal changes within the first 4 min. Thirty-two percent of the cases did not register temperature variations after lidocaine was injected, requiring the needle to be relocated. Differences between moments are indicated using the 95% confidence intervals of the differences (CI 95%), the Cohen effect size (ES) and the significance (p value). In successful cases, after injecting lidocaine, increases at minute 7 for the mean (CI 95% (1.4, 2.1 °C), p < 0.001 and ES = 0.5), at minute 5 for maximum temperature (CI 95% (2.3, 3.3 °C), p < 0.001 and ES = 0.6) and at minute 6 for SD (CI 95% (0.2, 0.3 °C), p < 0.001 and ES = 0.5) were observed. The results of our preliminary study showed that the measurement of skin temperature in real time by infrared thermography is valuable for assessing the success of lumbar sympathetic blocks.

Incubation of neural alcohol cue reactivity after withdrawal and its blockade by naltrexone.

During the first weeks of abstinence, alcohol craving in patients may increase or "incubate." We hypothesize that Naltrexone (NTX) blocks this incubation effect. Here, we compared NTX effects on neural alcohol cue reactivity (CR) over the first weeks of abstinence and on long-term clinical outcomes to standard treatment. Male alcohol-dependent patients (n = 55) and healthy controls (n = 35) were enrolled. Participants underwent baseline psychometric testing and functional magnetic resonance imaging (fMRI) assessment of mesolimbic alcohol CR. Patients participated in a standard treatment program with the option of adjuvant NTX. They received another scan after 2 weeks of treatment. We found higher CR in several brain regions in patients versus healthy controls. CR significantly increased over 2 weeks in the standard treatment group (n = 13) but not in the NTX group (n = 22). NTX significantly attenuated CR in the left putamen and reduced relapse risk to heavy drinking within 3 months of treatment. Additionally, increased CR in the left putamen and its course over time predicted both NTX response and relapse risk. Carrier status for the functional OPRM1 variant rs1799971:A > G was considered but had no effect on NTX efficacy. In conclusion, NTX was most effective in patients with high CR in the left putamen. While the results from our naturalistic study await further confirmation from prospective randomized trials, they support a potential role of neural CR as a biomarker in the development of precision medicine approaches with NTX.

Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis: a feasibility study.

OBJECTIVE: To examine the capability of MRI texture analysis to differentiate the primary site of origin of brain metastases following a radiomics approach. METHODS: Sixty-seven untreated brain metastases (BM) were found in 3D T1-weighted MRI of 38 patients with cancer: 27 from lung cancer, 23 from melanoma and 17 from breast cancer. These lesions were segmented in 2D and 3D to compare the discriminative power of 2D and 3D texture features. The images were quantized using different number of gray-levels to test the influence of quantization. Forty-three rotation-invariant texture features were examined. Feature selection and random forest classification were implemented within a nested cross-validation structure. Classification was evaluated with the area under receiver operating characteristic curve (AUC) considering two strategies: multiclass and one-versus-one. RESULTS: In the multiclass approach, 3D texture features were more discriminative than 2D features. The best results were achieved for images quantized with 32 gray-levels (AUC = 0.873 ± 0.064) using the top four features provided by the feature selection method based on the p-value. In the one-versus-one approach, high accuracy was obtained when differentiating lung cancer BM from breast cancer BM (four features, AUC = 0.963 ± 0.054) and melanoma BM (eight features, AUC = 0.936 ± 0.070) using the optimal dataset (3D features, 32 gray-levels). Classification of breast cancer and melanoma BM was unsatisfactory (AUC = 0.607 ± 0.180). CONCLUSION: Volumetric MRI texture features can be useful to differentiate brain metastases from different primary cancers after quantizing the images with the proper number of gray-levels. KEY POINTS: • Texture analysis is a promising source of biomarkers for classifying brain neoplasms. • MRI texture features of brain metastases could help identifying the primary cancer. • Volumetric texture features are more discriminative than traditional 2D texture features.

2D and 3D texture analysis to differentiate brain metastases on MR images: proceed with caution.

OBJECTIVE: To find structural differences between brain metastases of lung and breast cancer, computing their heterogeneity parameters by means of both 2D and 3D texture analysis (TA). MATERIALS AND METHODS: Patients with 58 brain metastases from breast (26) and lung cancer (32) were examined by MR imaging. Brain lesions were manually delineated by 2D ROIs on the slices of contrast-enhanced T1-weighted (CET1) images, and local binary patterns (LBP) maps were created from each region. Histogram-based (minimum, maximum, mean, standard deviation, and variance), and co-occurrence matrix-based (contrast, correlation, energy, entropy, and homogeneity) 2D, weighted average of the 2D slices, and true 3D TA were obtained on the CET1 images and LBP maps. RESULTS: For LBP maps and 2D TA contrast, correlation, energy, and homogeneity were identified as statistically different heterogeneity parameters (SDHPs) between lung and breast metastasis. The weighted 3D TA identified entropy as an additional SDHP. Only two texture indexes (TI) were significantly different with true 3D TA: entropy and energy. All these TIs discriminated between the two tumor types significantly by ROC analysis. For the CET1 images there was no SDHP at all by 3D TA. CONCLUSION: Our results indicate that the used textural analysis methods may help with discriminating between brain metastases of different primary tumors.

Structural and functional, empirical and modeled connectivity in the cerebral cortex of the rat.

Connectomics data from animal models provide an invaluable opportunity to reveal the complex interplay between structure and function in the mammalian brain. In this work, we investigate the relationship between structural and functional connectivity in the rat brain cortex using a directed anatomical network generated from a carefully curated meta-analysis of published tracing data, along with resting-state functional MRI data obtained from a group of 14 anesthetized Wistar rats. We found a high correspondence between the strength of functional connections, measured as blood oxygen level dependent (BOLD) signal correlations between cortical regions, and the weight of the corresponding anatomical links in the connectome graph (maximum Spearman rank-order correlation ρ=0.48). At the network-level, regions belonging to the same functionally defined community tend to form more mutual weighted connections between each other compared to regions located in different communities. We further found that functional communities in resting-state networks are enriched in densely connected anatomical motifs. Importantly, these higher-order structural subgraphs cannot be explained by lower-order topological properties, suggesting that dense structural patterns support functional associations in the resting brain. Simulations of brain-wide resting-state activity based on neural mass models implemented on the empirical rat anatomical connectome demonstrated high correlation between the simulated and the measured functional connectivity (maximum Pearson correlation ρ=0.53), further suggesting that the topology of structural connections plays an important role in shaping functional cortical networks.

Incidence, Outcomes, and Predictors of Ventricular Thrombus after Reperfused ST-Segment-Elevation Myocardial Infarction by Using Sequential Cardiac MR Imaging.

Purpose To characterize the incidence, outcomes, and predictors of left ventricular (LV) thrombus by using sequential cardiac magnetic resonance (MR) imaging after ST-segment-elevation myocardial infarction (STEMI). Materials and Methods Written informed consent was obtained from all patients, and the study protocol was approved by the committee on human research. In a cohort of 772 patients with STEMI, 392 (mean age, 58 years; range, 24-89 years) were retrospectively selected who were studied with cardiac MR imaging at 1 week and 6 months. Cardiac MR imaging guided the initiation and withdrawal of anticoagulants. Patients with LV thrombus at 6 months were restudied at 1 year. For predicting the occurrence of LV thrombus, a multiple regression model was applied. Results LV thrombus was detected in 27 of 392 patients (7%): 18 (5%) at 1 week and nine (2%) at 6 months. LV thrombus resolved in 22 of 25 patients (88%) restudied within the first year. During a mean follow-up of 181 weeks ± 168, patients with LV thrombus displayed a very low rate of stroke (0%), peripheral embolism (0%), and severe hemorrhage (n = 1, 3.7%). LV ejection fraction (LVEF) less than 50% (P < .001) and anterior infarction (P = .008) independently helped predict LV thrombus. The incidence of LV thrombus was as follows: (a) nonanterior infarction, LVEF 50% or greater (one of 135, 1%); (b) nonanterior infarction, LVEF less than 50% (one of 50, 2%); (c) anterior infarction, LVEF 50% or greater (two of 92, 2%); and (d) anterior infarction, LVEF less than 50% (23 of 115, 20%) (P < .001 for the trend). Conclusion Cardiac MR imaging contributes information for the diagnosis and therapy of LV thrombus after STEMI. Patients with simultaneous anterior infarction and LVEF less than 50% are at highest risk. © RSNA, 2017 Online supplemental material is available for this article.

Opportunistic screening for osteoporosis by routine CT in Southern Europe.

Feasibility evaluation of early detection of osteoporosis in oncologic patients by bone mineral density (BMD) on abdominal computed tomography (CT) scans performed for other clinical indications, by using dual-energy X-ray absorptiometry (DXA) as reference. Abdominal CT images can identify patients with osteoporosis BMD without additional radiation exposure or cost. INTRODUCTION: The purpose of the study is to evaluate the feasibility of early detection of osteoporosis by bone mineral density (BMD) on abdominal computed tomography (CT) scans performed in oncologic patients, comparing calibrated and uncalibrated measurements by using dual-energy X-ray absorptiometry (DXA) as reference. We also performed an external validation of a threshold of 160 Hounsfield units (HU), proposed as highly sensitive. METHODS: Cohort comprised CT-DXA pairs within a 6-month period performed for any indication on 326 consecutive adults, aged 62.4 ± 12.38 years (mean ± standard deviation). CT attenuation of trabecular bone in HU was measured at the axial cross sections of L1, L2, L3, and L4 vertebrae. Vertebral compression fractures were assessed by sagittal reconstruction view. Diagnostic performance measures and the area under the receiver operator characteristic curve (AUC) for diagnosing osteoporosis were calculated. RESULTS: BMD values were statistical significantly lower at any vertebral level from L1 to L4 for patients with osteoporosis defined by DXA (p < 0.001). Calibrated and uncalibrated BMD values were significantly correlated (R 2 = 0.833, p < 0.01). An uncalibrated L1 CT attenuation threshold of 160 HU was more than 90 % sensitive, and a threshold of 73 HU was more than 90 % specific for distinguishing osteoporosis BMD. Fifty-nine percent of patients with vertebral compression fracture had non-osteoporotic DXA T-scores. CONCLUSIONS: Abdominal CT images obtained for other reasons can identify patients with osteoporosis BMD without additional radiation exposure or cost. Uncalibrated values at L1 can detect more osteoporosis patients with spinal compression fractures than DXA in oncologic patients.

Multi-modal MRI classifiers identify excessive alcohol consumption and treatment effects in the brain.

Robust neuroimaging markers of neuropsychiatric disorders have proven difficult to obtain. In alcohol use disorders, profound brain structural deficits can be found in severe alcoholic patients, but the heterogeneity of unimodal MRI measurements has so far precluded the identification of selective biomarkers, especially for early diagnosis. In the present work we used a combination of multiple MRI modalities to provide comprehensive and insightful descriptions of brain tissue microstructure. We performed a longitudinal experiment using Marchigian-Sardinian (msP) rats, an established model of chronic excessive alcohol consumption, and acquired multi-modal images before and after 1 month of alcohol consumption (6.8 ± 1.4 g/kg/day, mean ± SD), as well as after 1 week of abstinence with or without concomitant treatment with the antirelapse opioid antagonist naltrexone (2.5 mg/kg/day). We found remarkable sensitivity and selectivity to accurately classify brains affected by alcohol even after the relative short exposure period. One month drinking was enough to imprint a highly specific signature of alcohol consumption. Brain alterations were regionally specific and affected both gray and white matter and persisted into the early abstinence state without any detectable recovery. Interestingly, naltrexone treatment during early abstinence resulted in subtle brain changes that could be distinguished from non-treated abstinent brains, suggesting the existence of an intermediate state associated with brain recovery from alcohol exposure induced by medication. The presented framework is a promising tool for the development of biomarkers for clinical diagnosis of alcohol use disorders, with capacity to further inform about its progression and response to treatment.

Prediction of Reverse Remodeling at Cardiac MR Imaging Soon after First ST-Segment-Elevation Myocardial Infarction: Results of a Large Prospective Registry.

PURPOSE: To assess predictors of reverse remodeling by using cardiac magnetic resonance (MR) imaging soon after ST-segment-elevation myocardial infarction (STEMI). MATERIALS AND METHODS: Written informed consent was obtained from all patients, and the study protocol was approved by the institutional committee on human research, ensuring that it conformed to the ethical guidelines of the 1975 Declaration of Helsinki. Five hundred seven patients (mean age, 58 years; age range, 24-89 years) with a first STEMI were prospectively studied. Infarct size and microvascular obstruction (MVO) were quantified at late gadolinium-enhanced imaging. Reverse remodeling was defined as a decrease in left ventricular (LV) end-systolic volume index (LVESVI) of more than 10% from 1 week to 6 months after STEMI. For statistical analysis, a simple (from a clinical perspective) multiple regression model preanalyzing infarct size and MVO were applied via univariate receiver operating characteristic techniques. RESULTS: Patients with reverse remodeling (n = 211, 42%) had a lesser extent (percentage of LV mass) of 1-week infarct size (mean ± standard deviation: 18% ± 13 vs 23% ± 14) and MVO (median, 0% vs 0%; interquartile range, 0%-1% vs 0%-4%) than those without reverse remodeling (n = 296, 58%) (P < .001 in pairwise comparisons). The independent predictors of reverse remodeling were infarct size (odds ratio, 0.98; 95% confidence interval [CI]: 0.97, 0.99; P = .04) and MVO (odds ratio, 0.92; 95% CI: 0.86, 0.99; P = .03). Once infarct size and MVO were dichotomized by using univariate receiver operating characteristic techniques, the only independent predictor of reverse remodeling was the presence of simultaneous nonextensive infarct-size MVO (infarct size < 30% of LV mass and MVO < 2.5% of LV mass) (odds ratio, 3.2; 95% CI: 1.8, 5.7; P < .001). CONCLUSION: Assessment of infarct size and MVO with cardiac MR imaging soon after STEMI enables one to make a decision in the prediction of reverse remodeling.

Brain metastases detection on MR by means of three-dimensional tumor-appearance template matching.

PURPOSE: To develop and evaluate a method for an automatic detection of brain metastases in MR images. MATERIALS AND METHODS: Nineteen patients were scanned using a 1.5 Tesla MR scanner. Two radiologists and a radiation oncologist marked the location of the brain metastases. The training group consisted of eight patients harboring 20 metastases. First, three-dimensional (3D) tumor-appearance templates were cross-correlated with MR brain images to evaluate their similarity, and a correlation threshold was established for metastasis candidates. Afterward, a method to reduce false positive rate (FPR) was applied: each detected object was segmented and its degree of anisotropy (DA) was obtained, removing the elongated structures with a DA above the optimal value from the receiver operating characteristic curve. Finally, the method was statistically validated in two groups: 11 patients with 42 brain metastases and 11 patients without metastases. RESULTS: The method led to a sensitivity of 80% and an FPR per slice of 0.023 and 2.75 per patient in the training group. In the first validation group, a sensitivity of 88.10% and an FPR per slice of 0.05 corresponding to 6.91 false positives per patient were obtained. DA implementation decreased 3.5 times FPR compared with templates alone. It improved the radiologist's performance in metastases less than 10 mm from 89-93% to 100%. In the second validation group the FPR was 0.04 per slice and 5.18 per patient. CONCLUSION: This method demonstrates that 3D template matching applying DA technique has high sensitivity and low FPR for detecting brain metastases in MR images. J. Magn. Reson. Imaging 2016;44:642-652.

Support vector machine classification of brain metastasis and radiation necrosis based on texture analysis in MRI.

PURPOSE: To develop a classification model using texture features and support vector machine in contrast-enhanced T1-weighted images to differentiate between brain metastasis and radiation necrosis. METHODS: Texture features were extracted from 115 lesions: 32 of them previously diagnosed as radiation necrosis, 23 as radiation-treated metastasis and 60 untreated metastases; including a total of 179 features derived from six texture analysis methods. A feature selection technique based on support vector machine was used to obtain a subset of features that provide optimal performance. RESULTS: The highest classification accuracy evaluated over test sets was achieved with a subset of ten features when the untreated metastases were not considered; and with a subset of seven features when the classifier was trained with untreated metastases and tested on treated ones. Receiver operating characteristic curves provided area-under-the-curve (mean ± standard deviation) of 0.94 ± 0.07 in the first case, and 0.93 ± 0.02 in the second. CONCLUSION: High classification accuracy (AUC > 0.9) was obtained using texture features and a support vector machine classifier in an approach based on conventional MRI to differentiate between brain metastasis and radiation necrosis.