Combining Early Ischemic Change and Collateral Extent for Functional Outcomes After Endovascular Therapy: An Analysis From AcT Trial.

BACKGROUND: Early ischemic change and collateral extent are colinear with ischemic core volume (ICV). We investigated the relationship between a combined score using the Alberta Stroke Program Early Computed Tomography Score and multiphase computed tomography angiography (mCTA) collateral extent, named mCTA-ACE score, on functional outcomes in endovascular therapy-treated patients. METHODS: We performed a post hoc analysis of a subset of endovascular therapy-treated patients from the Alteplase Compared to Tenecteplase trial which was conducted between December 2019 and January 2022 at 22 centers across Canada. Ten-point mCTA collateral corresponding to M2 to M6 regions of the Alberta Stroke Program Early Computed Tomography Score grid was evaluated as 0 (poor), 1 (moderate), or 2 (normal) and additively combined with the 10-point Alberta Stroke Program Early Computed Tomography Score to produce a 20-point mCTA-ACE score. We investigated the association of mCTA-ACE score with modified Rankin Scale score ≤2 and return to prestroke level of function at 90 to 120 days using mixed-effects logistic regression. In the subset of patients who underwent baseline computed tomography perfusion imaging, we compared the mCTA-ACE score and ICV for outcome prediction. RESULTS: Among 1577 intention-to-treat population in the trial, 368 (23%; 179 men; median age, 73 years) were included, with Alberta Stroke Program Early Computed Tomography Score, mCTA collateral, and combination of both (mCTA-ACE score: median [interquartile range], 8 [7-10], 9 [8-10], and 17 [16-19], respectively). The probability of modified Rankin Scale score ≤2 and return to prestroke level of function increased for each 1-point increase in mCTA-ACE score (odds ratio, 1.16 [95% CI, 1.06-1.28] and 1.22 [95% CI, 1.06-1.40], respectively). Among 173 patients in whom computed tomography perfusion data was assessable, the mCTA-ACE score was inversely correlated with ICV (ρ=-0.46; P<0.01). The mCTA-ACE score was comparable to ICV to predict a modified Rankin Scale score ≤2 and return to prestroke level of function (C statistics 0.71 versus 0.69 and 0.68 versus 0.64, respectively). CONCLUSIONS: The mCTA-ACE score had a significant positive association with functional outcomes after endovascular therapy and had a similar predictive performance as ICV.

Distal Embolization in Relation to Radiological Thrombus Characteristics, Treatment Details, and Functional Outcome.

BACKGROUND: Distal embolization (DE) is a common complication of endovascular treatment (EVT). We investigated the association of radiological thrombus characteristics and treatment details with DE. METHODS: Patients with thin-slice (≤2.5 mm) baseline noncontrast computed tomography and computed tomography angiography from the ESCAPE-NA1 trial (Efficacy and Safety of Nerinetide for the Treatment of Acute Ischemic Stroke) were included. Thrombus annotation was performed manually on coregistered scans by experienced readers. We assessed thrombus location, distance from internal carotid artery terminus, length, perviousness, absolute attenuation, and hyperdense artery sign. In addition, we evaluated balloon guide catheter use during EVT, first-line EVT approach, the number of thrombectomy passes, and prior intravenous thrombolysis administration. DE was defined as the occurrence of emboli distal to the target artery or in new territories during EVT. The association between thrombus characteristics, treatment details, and DE was evaluated using descriptive statistics and multivariable mixed-effects logistic regression, resulting in adjusted odds ratios (aOR) with 95% CI. Interaction between IVT and radiological thrombus characteristics was assessed by adding interaction terms in separate models. RESULTS: In total, 496 out of 1105 (44.9%) ESCAPE-NA1 patients were included. DE was detected in 251 out of 496 patients (50.6%). Patients with DE had longer thrombi (median, 28.5 [interquartile range, 20.8-42.3] mm versus 24.4 [interquartile range, 17.1-32.4] mm; P<0.01). There were no statistically significant differences in the other thrombus characteristics. Factors associated with DE were thrombus length (aOR, 1.02 [95% CI, 1.01-1.04]), balloon guide catheter use (aOR, 0.49 [95% CI, 0.29-0.85]), and number of passes (aOR, 1.24 [95% CI, 1.04-1.47]). In patients with hyperdense artery sign, IVT was associated with reduced odds of DE (aOR, 0.55 [95% CI, 0.31-0.97]), P for interaction=0.04. CONCLUSIONS: DE was associated with longer thrombi, no balloon guide catheter use, and more EVT passes. IVT was associated with a reduced risk of DE in patients with hyperdense artery sign. These findings may support treatment decisions on IVT and EVT approaches.

Self-calibrating dual-sensing electrochemical sensors for accurate detection of carbon dioxide in blood.

A paper-based electrochemical dual-function biosensor capable of determining pH and TCO2 was synthesized for the first time using an iridium oxide pH electrode and an all-solid-state ion electrode (ASIE). In the study, to obtain highly reliable results, the biosensor was equipped with a real-time pH correction function before TCO2 measurements. Compared to traditional liquid-filling carbon dioxide detection sensors, the utilization of ferrocene endows our novel sensor with abundant positive sites, and thus greatly improves its performance. Conversely, the introduction of MXene with conductivity close to that of metals reduces electrode resistance, which is beneficial for accelerating the electrochemical reaction of the sensor and reducing LOD. After optimization, the detection range of TCO2 is 0.095 nM-0.66 M, with a detection limit of as low as 0.023 nM. In addition, the sensor was used in real serum sample-spiked recovery experiments and comparison experiments with existing clinical blood gas analyzers, which confirmed the effectiveness of its clinical application. This study provides a method for the rational design of paper-based electrochemical biosensors and a new approach for the clinical detection of blood carbon dioxide.

Risk Stratification for Oropharyngeal Squamous Cell Carcinoma Using Texture Analysis on CT - A Step Beyond HPV Status.

Background and Purpose: Human papillomavirus-associated oropharyngeal squamous cell carcinoma (OPSCC) is increasingly prevalent. Despite the overall more favorable outcome, the observed heterogeneous treatment response within this patient group highlights the need for additional means to prognosticate and guide clinical decision-making. Promising prediction models using radiomics from primary OPSCC have been derived. However, no model/s using metastatic lymphadenopathy exist to allow prognostication in those instances when the primary tumor is not seen. The aim of our study was to evaluate whether radiomics using metastatic lymphadenopathy allows for the development of a useful risk assessment model comparable to the primary tumor and whether additional knowledge of the HPV status further improves its prognostic efficacy. Materials and Methods: 80 consecutive patients diagnosed with stage III-IV OPSCC between February 2009 and October 2015, known human papillomavirus status, and pre-treatment CT images were retrospectively identified. Manual segmentation of primary tumor and metastatic lymphadenopathy was performed and the extracted texture features were used to develop multivariate assessment models to prognosticate treatment response. Results: Texture analysis of either the primary or metastatic lymphadenopathy from pre-treatment enhanced CT images can be used to develop models for the stratification of treatment outcomes in OPSCC patients. AUCs range from .78 to .85 for the various OPSCC groups tested, indicating high predictive capability of the models. Conclusions: This preliminary study can form the basis multi-centre trial that may help optimize treatment and improve quality of life in patients with OPSCC in the era of personalized medicine.

Variability assessment of manual segmentations of ischemic lesion volume on 24-h non-contrast CT.

PURPOSE: Infarct lesion volume (ILV) may serve as an imaging biomarker for clinical outcomes in the early post-treatment stage in patients with acute ischemic stroke. The aim of this study was to evaluate the inter- and intra-rater reliability of manual segmentation of ILV on follow-up non-contrast CT (NCCT) scans. METHODS: Fifty patients from the Prove-IT study were randomly selected for this analysis. Three raters manually segmented ILV on 24-h NCCT scans, slice by slice, three times. The reference standard for ILV was generated by the Simultaneous Truth And Performance Level estimation (STAPLE) algorithm. Intra- and inter-rater reliability was evaluated, using metrics of intraclass correlation coefficient (ICC) regarding lesion volume and the Dice similarity coefficient (DSC). RESULTS: Median age of the 50 subjects included was 74.5 years (interquartile range [IQR] 67-80), 54% were women, median baseline National Institutes of Health Stroke Scale was 18 (IQR 11-22), median baseline ASPECTS was 9 (IQR 6-10). The mean reference standard ILV was 92.5 ml (standard deviation (SD) ± 100.9 ml). The manually segmented ILV ranged from 88.2 ± 91.5 to 135.5 ± 119.9 ml (means referring to the variation between readers, SD within readers). Inter-rater ICC was 0.83 (95%CI: 0.76-0.88); intra-rater ICC ranged from 0.85 (95%CI: 0.72-0.92) to 0.95 (95%CI: 0.91-0.97). The mean DSC among the three readers ranged from 65.5 ± 22.9 to 76.4 ± 17.1% and the mean overall DSC was 72.8 ± 23.0%. CONCLUSION: Manual ILV measurements on follow-up CT scans are reliable to measure the radiological outcome despite some variability.

Multiphase CTA-derived tissue maps aid in detection of medium vessel occlusions.

PURPOSE: Medium vessel occlusions (MeVOs) can be challenging to detect on imaging. Multiphase computed tomography angiography (mCTA) has been shown to improve large vessel occlusion (LVO) detection and endovascular treatment (EVT) selection. The aims of this study were to determine if mCTA-derived tissue maps can (1) accurately detect MeVOs and (2) predict infarction on 24-h follow-up imaging with comparable accuracy to CT perfusion (CTP). METHODS: Two readers assessed mCTA tissue maps of 116 ischemic stroke patients (58 MeVOs, 58 non-MeVOs) and determined by consensus: (1) MeVO (yes/no) and (2) occlusion site, blinded to clinical or imaging data. Sensitivity, specificity, and area under the curve (AUC) for MeVO detection were estimated in comparison to reference standards of (1) expert readings of baseline mCTA and (2) CTP maps. Volumetric and spatial agreement between mCTA- and CTP-predicted infarcts was assessed using concordance/intraclass correlation and Dice coefficients. Interrater agreement for MeVO detection on mCTA tissue maps was estimated with Cohen's kappa. RESULTS: MeVO detection from mCTA-derived tissue maps had a sensitivity of 91% (95% CI: 80-97), specificity of 82% (95% CI: 70-90), and AUC of 0.87 (95% CI: 0.80-0.93) compared to expert reads of baseline mCTA. Interrater reliability was good (0.72, 95% CI: 0.60-0.85). Compared to CTP maps, sensitivity was 87% (95% CI: 75-95), specificity was 78% (95%CI: 65-88), and AUC was 0.83 (95% CI: 0.76-0.90). The mean difference between mCTA- and CTP-predicted final infarct volume was 4.8 mL (limits of agreement: - 58.5 to 68.1) with a Dice coefficient of 33.5%. CONCLUSION: mCTA tissue maps can be used to reliably detect MeVO stroke and predict tissue fate.

Validation of a machine learning software tool for automated large vessel occlusion detection in patients with suspected acute stroke.

PURPOSE: CT angiography (CTA) is the imaging standard for large vessel occlusion (LVO) detection in patients with acute ischemic stroke. StrokeSENS LVO is an automated tool that utilizes a machine learning algorithm to identify anterior large vessel occlusions (LVO) on CTA. The aim of this study was to test the algorithm's performance in LVO detection in an independent dataset. METHODS: A total of 400 studies (217 LVO, 183 other/no occlusion) read by expert consensus were used for retrospective analysis. The LVO was defined as intracranial internal carotid artery (ICA) occlusion and M1 middle cerebral artery (MCA) occlusion. Software performance in detecting anterior LVO was evaluated using receiver operator characteristics (ROC) analysis, reporting area under the curve (AUC), sensitivity, and specificity. Subgroup analyses were performed to evaluate if performance in detecting LVO differed by subgroups, namely M1 MCA and ICA occlusion sites, and in data stratified by patient age, sex, and CTA acquisition characteristics (slice thickness, kilovoltage tube peak, and scanner manufacturer). RESULTS: AUC, sensitivity, and specificity overall were as follows: 0.939, 0.894, and 0.874, respectively, in the full cohort; 0.927, 0.857, and 0.874, respectively, in the ICA occlusion cohort; 0.945, 0.914, and 0.874, respectively, in the M1 MCA occlusion cohort. Performance did not differ significantly by patient age, sex, or CTA acquisition characteristics. CONCLUSION: The StrokeSENS LVO machine learning algorithm detects anterior LVO with high accuracy from a range of scans in a large dataset.

Determinants of Leptomeningeal Collateral Status Variability in Ischemic Stroke Patients.

BACKGROUND: Collateral status is an indicator of a favorable outcome in stroke. Leptomeningeal collaterals provide alternative routes for brain perfusion following an arterial occlusion or flow-limiting stenosis. Using a large cohort of ischemic stroke patients, we examined the relative contribution of various demographic, laboratory, and clinical variables in explaining variability in collateral status. METHODS: Patients with acute ischemic stroke in the anterior circulation were enrolled in a multi-center hospital-based observational study. Intracranial occlusions and collateral status were identified and graded using multiphase computed tomography angiography. Based on the percentage of affected territory filled by collateral supply, collaterals were graded as either poor (0-49%), good (50-99%), or optimal (100%). Between-group differences in demographic, laboratory, and clinical factors were explored using ordinal regression models. Further, we explored the contribution of measured variables in explaining variance in collateral status. RESULTS: 386 patients with collateral status classified as poor (n = 64), good (n = 125), and optimal (n = 197) were included. Median time from symptom onset to CT was 120 (IQR: 78-246) minutes. In final multivariable model, male sex (OR 1.9, 95% CIs [1.2, 2.9], p = 0.005) and leukocytosis (OR 1.1, 95% CIs [1.1, 1.2], p = 0.001) were associated with poor collaterals. Measured variables only explained 44.8-53.0% of the observed between-patient variance in collaterals. CONCLUSION: Male sex and leukocytosis are associated with poorer collaterals. Nearly half of the variance in collateral flow remains unexplained and could be in part due to genetic differences.

Computed Tomography Perfusion-Based Machine Learning Model Better Predicts Follow-Up Infarction in Patients With Acute Ischemic Stroke.

BACKGROUND AND PURPOSE: Prediction of infarct extent among patients with acute ischemic stroke using computed tomography perfusion is defined by predefined discrete computed tomography perfusion thresholds. Our objective is to develop a threshold-free computed tomography perfusion-based machine learning (ML) model to predict follow-up infarct in patients with acute ischemic stroke. METHODS: Sixty-eight patients from the PRoveIT study (Measuring Collaterals With Multi-Phase CT Angiography in Patients With Ischemic Stroke) were used to derive a ML model using random forest to predict follow-up infarction voxel by voxel, and 137 patients from the HERMES study (Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke Trials) were used to test the derived ML model. Average map, Tmax, cerebral blood flow, cerebral blood volume, and time variables including stroke onset-to-imaging and imaging-to-reperfusion time, were used as features to train the ML model. Spatial and volumetric agreement between the ML model predicted follow-up infarct and actual follow-up infarct were assessed. Relative cerebral blood flow <0.3 threshold using RAPID software and time-dependent Tmax thresholds were compared with the ML model. RESULTS: In the test cohort (137 patients), median follow-up infarct volume predicted by the ML model was 30.9 mL (interquartile range, 16.4-54.3 mL), compared with a median 29.6 mL (interquartile range, 11.1-70.9 mL) of actual follow-up infarct volume. The Pearson correlation coefficient between 2 measurements was 0.80 (95% CI, 0.74-0.86, P<0.001) while the volumetric difference was -3.2 mL (interquartile range, -16.7 to 6.1 mL). Volumetric difference with the ML model was smaller versus the relative cerebral blood flow <0.3 threshold and the time-dependent Tmax threshold (P<0.001). CONCLUSIONS: A ML using computed tomography perfusion data and time estimates follow-up infarction in patients with acute ischemic stroke better than current methods.

Clinical characteristics, medical service utilization, and expenditure for colorectal cancer in China, 2005 to 2014: Overall design and results from a multicenter retrospective epidemiologic survey.

BACKGROUND: Colorectal cancer (CRC) is the third most common cancer in China, however, publicly available, descriptive information on the clinical epidemiology of CRC is limited. METHODS: Patients diagnosed with primary CRC during 2005 through 2014 were sampled from 13 tertiary hospitals in 9 provinces across China. Data related to sociodemographic characteristics, the use of diagnostic technology, treatment adoption, and expenditure were extracted from individual medical records. RESULTS: In the full cohort of 8465 patients, the mean ± SD age at diagnosis was 59.3 ± 12.8 years, 57.2% were men, and 58.7% had rectal cancer. On average, 14.4% of patients were diagnosed with stage IV disease, and this proportion increased from 13.5% in 2005 to 20.5% in 2014 (P value for trend < .05). For diagnostic techniques, along with less use of x-rays (average, 81.6%; decreased from 90.0% to 65.7%), there were increases in the use of computed tomography (average, 70.4%; increased from 4.5% to 90.5%) and magnetic resonance imaging (average, 8.8%; increased from 0.1% to 20.4%) over the study period from 2005 to 2014. With regard to treatment, surgery alone was the most common (average, 50.1%), but its use decreased from 51.3% to 39.8% during 2005 through 2014; and the use of other treatments increased simultaneously, such as chemotherapy alone (average, 4.1%; increased from 4.1% to 11.9%). The average medical expenditure per patient was 66,291 Chinese Yuan (2014 value) and increased from 47,259 to 86,709 Chinese Yuan. CONCLUSIONS: The increasing proportion of late-stage diagnoses presents a challenge for CRC control in China. Changes in diagnostic and treatment options and increased expenditures are clearly illustrated in this study. Coupled with the recent introduction of screening initiatives, these data provide an understanding of changes over time and may form a benchmark for future related evaluations of CRC interventions in China.

Radiologic Patterns of Intracranial Hemorrhage and Clinical Outcome after Endovascular Treatment in Acute Ischemic Stroke: Results from the ESCAPE-NA1 Trial.

Background Intracranial hemorrhage is a known complication after endovascular treatment in patients with acute ischemic stroke due to large vessel occlusion, but the association between radiologic hemorrhage severity and outcome is controversial. Purpose To investigate the prevalence and impact on outcome of intracranial hemorrhage and hemorrhage severity after endovascular stroke treatment. Materials and Methods The Efficacy and Safety of Nerinetide for the Treatment of Acute Ischemic Stroke (ESCAPE-NA1) trial enrolled participants with acute large vessel occlusion stroke who underwent endovascular treatment from March 1, 2017, to August 12, 2019. Evidence of any intracranial hemorrhage, hemorrhage multiplicity, and radiologic severity, according to the Heidelberg classification (hemorrhagic infarction type 1 [HI1], hemorrhagic infarction type 2 [HI2], parenchymal hematoma type 1 [PH1], and parenchymal hematoma type 2 [PH2]) was assessed at CT or MRI 24 hours after endovascular treatment. Good functional outcome, defined as a modified Rankin score of 0-2 at 90 days, was compared between participants with intracranial hemorrhage and those without intracranial hemorrhage at follow-up imaging and between hemorrhage subtypes. Poisson regression was performed to obtain adjusted effect size estimates for the presence of any intracranial hemorrhage and hemorrhage subtypes at good functional outcome. Results Of 1097 evaluated participants (mean age, 69 years ± 14 [standard deviation]; 551 men), any degree of intracranial hemorrhage was observed in 372 (34%). Good outcomes were less often achieved among participants with hemorrhage than among those without hemorrhage at follow-up imaging (164 of 372 participants [44%] vs 500 of 720 [69%], respectively; P < .01). After adjusting for baseline variables and infarct volume, intracranial hemorrhage was not associated with decreased chances of good outcome (adjusted risk ratio [RR] = 0.91 [95% CI: 0.82, 1.02], P = .10), but there was a graded relationship of radiologic hemorrhage severity and outcomes, whereby PH1 (RR = 0.77 [95% CI: 0.61, 0.97], P = .03) and PH2 (RR = 0.41 [95% CI: 0.21, 0.81], P = .01) were associated with decreased chances of good outcome. Conclusion Any degree of intracranial hemorrhage after endovascular treatment was seen in one-third of participants. A graded association existed between radiologic hemorrhage severity and outcome. Hemorrhagic infarction was not associated with outcome, whereas parenchymal hematoma was strongly associated with poor outcome, independent of infarct volume. © RSNA, 2021 Clinical trial registration no. NCT01778335 Online supplemental material is available for this article.

A Detailed Analysis of Infarct Patterns and Volumes at 24-hour Noncontrast CT and Diffusion-weighted MRI in Acute Ischemic Stroke Due to Large Vessel Occlusion: Results from the ESCAPE-NA1 Trial.

Background The effect of infarct pattern on functional outcome in acute ischemic stroke is incompletely understood. Purpose To investigate the association of qualitative and quantitative infarct variables at 24-hour follow-up noncontrast CT and diffusion-weighted MRI with 90-day clinical outcome. Materials and Methods The Safety and Efficacy of Nerinetide in Subjects Undergoing Endovascular Thrombectomy for Stroke, or ESCAPE-NA1, randomized controlled trial enrolled patients with large-vessel-occlusion stroke undergoing mechanical thrombectomy from March 1, 2017, to August 12, 2019. In this post hoc analysis of the trial, qualitative infarct variables (predominantly gray [vs gray and white] matter involvement, corticospinal tract involvement, infarct structure [scattered vs territorial]) and total infarct volume were assessed at 24-hour follow-up noncontrast CT or diffusion-weighted MRI. White and gray matter infarct volumes were assessed in patients by using follow-up diffusion-weighted MRI. Infarct variables were compared between patients with and those without good outcome, defined as a modified Rankin Scale score of 0-2 at 90 days. The association of infarct variables with good outcome was determined with use of multivariable logistic regression. Separate regression models were used to report effect size estimates with adjustment for total infarct volume. Results Qualitative infarct variables were assessed in 1026 patients (mean age ± standard deviation, 69 years ± 13; 522 men) and quantitative infarct variables were assessed in a subgroup of 358 of 1026 patients (mean age, 67 years ± 13; 190 women). Patients with gray and white matter involvement (odds ratio [OR] after multivariable adjustment, 0.19; 95% CI: 0.14, 0.25; P < .001), corticospinal tract involvement (OR after multivariable adjustment, 0.06; 95% CI: 0.04, 0.10; P < .001), and territorial infarcts (OR after multivariable adjustment, 0.22; 95% CI: 0.14, 0.32; P < .001) were less likely to achieve good outcome, independent of total infarct volume. Conclusion Infarct confinement to the gray matter, corticospinal tract sparing, and scattered infarct structure at 24-hour noncontrast CT and diffusion-weighted MRI were highly predictive of good 90-day clinical outcome, independent of total infarct volume. Clinical trial registration no. NCT02930018 © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Mossa-Basha in this issue.

Clinical outcomes of isolated deep grey matter infarcts after endovascular treatment of large vessel occlusion stroke.

PURPOSE: There are few data on the prevalence and impact of isolated deep grey matter infarction in acute stroke. In this study, we aimed to investigate the prevalence of isolated deep grey matter infarcts and their impact on the outcome. METHODS: Infarcts on 24-h follow-up imaging (non-contrast head CT or diffusion-weighted MRI) in the ESCAPE-NA1 trial were categorized into predominantly deep grey matter infarcts vs. infarcts involving additional territories ("other infarcts"). Total infarct volume was manually segmented. Baseline characteristics and proportions of good outcome (primary outcome, defined as modified Rankin Score [mRS] 0-2 at 90 days), excellent outcome (mRS 0-1) and mortality were compared between patients with and without predominantly deep grey matter infarcts. Multivariable logistic regression with adjustment for baseline variables and total infarct volume was used to determine a possible association of predominantly deep grey matter infarcts and clinical outcome. RESULTS: Predominantly deep grey matter infarcts were seen in 316/1026 patients (30.8%). Compared to other patients, their ASPECTS was higher, collateral status and reperfusion quality were better and time to treatment was shorter. Good outcome was seen in 239/316 (75.6%) with vs. 374/704 (53.1%) without predominantly deep grey matter infarcts. After adjusting for baseline variables and total infarct volume, predominantly deep grey matter infarcts were independently associated with excellent outcome (adjOR: 1.45 [CI95: 1.04-2.02]), but not with good outcome (adjOR: 1.24 [CI95: 0.86-1.80]) or mortality (adjOR: 0.73 [CI95:0.39-1.35]) CONCLUSION: Predominantly deep grey matter infarct patterns were seen in 1/3rd of patients and were significantly associated with increased chances of excellent outcome, independent of patient baseline status and infarct size.

Deficiency of Macf1 in osterix expressing cells decreases bone formation by Bmp2/Smad/Runx2 pathway.

Microtubule actin cross-linking factor 1 (Macf1) is a spectraplakin family member known to regulate cytoskeletal dynamics, cell migration, neuronal growth and cell signal transduction. We previously demonstrated that knockdown of Macf1 inhibited the differentiation of MC3T3-E1 cell line. However, whether Macf1 could regulate bone formation in vivo is unclear. To study the function and mechanism of Macf1 in bone formation and osteogenic differentiation, we established osteoblast-specific Osterix (Osx) promoter-driven Macf1 conditional knockout mice (Macf1f/f Osx-Cre). The Macf1f/f Osx-Cre mice displayed delayed ossification and decreased bone mass. Morphological and mechanical studies showed deteriorated trabecular microarchitecture and impaired biomechanical strength of femur in Macf1f/f Osx-Cre mice. In addition, the differentiation of primary osteoblasts isolated from calvaria was inhibited in Macf1f/f Osx-Cre mice. Deficiency of Macf1 in primary osteoblasts inhibited the expression of osteogenic marker genes (Col1, Runx2 and Alp) and the number of mineralized nodules. Furthermore, deficiency of Macf1 attenuated Bmp2/Smad/Runx2 signalling in primary osteoblasts of Macf1f/f Osx-Cre mice. Together, these results indicated that Macf1 plays a significant role in bone formation and osteoblast differentiation by regulating Bmp2/Smad/Runx2 pathway, suggesting that Macf1 might be a therapeutic target for bone disease.

Machine Learning for Detecting Early Infarction in Acute Stroke with Non-Contrast-enhanced CT.

Background Identifying the presence and extent of infarcted brain tissue at baseline plays a crucial role in the treatment of patients with acute ischemic stroke (AIS). Patients with extensive infarction are unlikely to benefit from thrombolysis or thrombectomy procedures. Purpose To develop an automated approach to detect and quantitate infarction by using non-contrast-enhanced CT scans in patients with AIS. Materials and Methods Non-contrast-enhanced CT images in patients with AIS (<6 hours from symptom onset to CT) who also underwent diffusion-weighted (DW) MRI within 1 hour after AIS were obtained from May 2004 to July 2009 and were included in this retrospective study. Ischemic lesions manually contoured on DW MRI scans were used as the reference standard. An automatic segmentation approach involving machine learning (ML) was developed to detect infarction. Randomly selected nonenhanced CT images from 157 patients with the lesion labels manually contoured on DW MRI scans were used to train and validate the ML model; the remaining 100 patients independent of the derivation cohort were used for testing. The ML algorithm was quantitatively compared with the reference standard (DW MRI) by using Bland-Altman plots and Pearson correlation. Results In 100 patients in the testing data set (median age, 69 years; interquartile range [IQR]: 59-76 years; 59 men), baseline non-contrast-enhanced CT was performed within a median time of 48 minutes from symptom onset (IQR, 27-93 minutes); baseline MRI was performed a median of 38 minutes (IQR, 24-48 minutes) later. The algorithm-detected lesion volume correlated with the reference standard of expert-contoured lesion volume in acute DW MRI scans (r = 0.76, P < .001). The mean difference between the algorithm-segmented volume (median, 15 mL; IQR, 9-38 mL) and the DW MRI volume (median, 19 mL; IQR, 5-43 mL) was 11 mL (P = .89). Conclusion A machine learning approach for segmentation of infarction on non-contrast-enhanced CT images in patients with acute ischemic stroke showed good agreement with stroke volume on diffusion-weighted MRI scans. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Nael in this issue.

From Molecular Reconstruction of Mesoscopic Functional Conductive Silk Fibrous Materials to Remote Respiration Monitoring.

Turning insulating silk fibroin materials into conductive ones turns out to be the essential step toward achieving active silk flexible electronics. This work aims to acquire electrically conductive biocompatible fibers of regenerated Bombyx mori silk fibroin (SF) materials based on carbon nanotubes (CNTs) templated nucleation reconstruction of silk fibroin networks. The electronical conductivity of the reconstructed mesoscopic functional fibers can be tuned by the density of the incorporated CNTs. It follows that the hybrid fibers experience an abrupt increase in conductivity when exceeding the percolation threshold of CNTs >35 wt%, which leads to the highest conductivity of 638.9 S m-1 among organic-carbon-based hybrid fibers, and 8 times higher than the best available materials of the similar types. In addition, the silk-CNT mesoscopic hybrid materials achieve some new functionalities, i.e., humidity-responsive conductivity, which is attributed to the coupling of the humidity inducing cyclic contraction of SFs and the conductivity of CNTs. The silk-CNT materials, as a type of biocompatible electronic functional fibrous material for pressure and electric response humidity sensing, are further fabricated into a smart facial mask to implement respiration condition monitoring for remote diagnosis and medication.

Confirmatory Study of Time-Dependent Computed Tomographic Perfusion Thresholds for Use in Acute Ischemic Stroke.

Background and Purpose- Computed tomographic perfusion (CTP) thresholds associated with follow-up brain infarction may differ by time from symptom onset to imaging and reperfusion. We confirm CTP thresholds over time to imaging and reperfusion in patients with acute ischemic stroke from the HERMES collaboration (Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke Trials) data. Methods- Patients with occlusion on CT angiography were acutely imaged with CTP. Noncontrast CT and magnetic resonance-diffusion weighted imaging at 24 to 48 hours defined follow-up infarction. Reperfusion was assessed on conventional angiogram. Tmax, cerebral blood flow (CBF), and cerebral blood volume maps were derived from delay-insensitive CTP postprocessing. These parameters were analyzed using receiver operator characteristics to derive optimal thresholds based on time from stroke onset-to-CTP or to reperfusion. ANOVA and linear regression were used to test whether the derived CTP thresholds were different by time. Results- One hundred thirty-seven patients were included. Tmax thresholds of >15.7 s and >15.8 s and absolute CBF thresholds of <8.9 and <7.5 mL·min-1·100 g-1 for gray matter and white matter respectively were associated with infarct if reperfusion was achieved <90 minutes from CTP with stroke onset-to-CTP <180 minutes. The discriminative ability of cerebral blood volume was modest. There were no statistically significant relationships between stroke onset-to-CTP time and Tmax, CBF, and cerebral blood volume thresholds (all P>0.05). A statistically significant relationship was observed between CTP-to-reperfusion time and the optimal thresholds for Tmax (P<0.001) and CBF (P<0.001). Similar but more modest relationship was noted for onset-to-reperfusion time and optimal thresholds for CBF (P≤0.01). Conclusions- CTP thresholds based on stroke onset and imaging time and taking into account time needed for reperfusion may improve infarct prediction in patients with acute ischemic stroke.

Hierarchical Structure of Silk Materials Versus Mechanical Performance and Mesoscopic Engineering Principles.

A comprehensive review on the five levels of hierarchical structures of silk materials and the correlation with macroscopic properties/performance of the silk materials, that is, the toughness, strain-stiffening, etc., is presented. It follows that the crystalline binding force turns out to be very important in the stabilization of silk materials, while the ß-crystallite networks or nanofibrils and the interactions among helical nanofibrils are two of the most essential structural elements, which to a large extent determine the macroscopic performance of various forms of silk materials. In this context, the characteristic structural factors such as the orientation, size, and density of ß-crystallites are very crucial. It is revealed that the formation of these structural elements is mainly controlled by the intermolecular nucleation of ß-crystallites. Consequently, the rational design and reconstruction of silk materials can be implemented by controlling the molecular nucleation via applying sheering force and seeding (i.e., with carbon nanotubes). In general, the knowledge of the correlation between hierarchical structures and performance provides an understanding of the structural reasons behind the fascinating behaviors of silk materials.

A Biodegradable and Stretchable Protein-Based Sensor as Artificial Electronic Skin for Human Motion Detection.

Due to the natural biodegradability and biocompatibility, silk fibroin (SF) is one of the ideal platforms for on-skin and implantable electronic devices. However, the development of SF-based electronics is still at a preliminary stage due to the SF film intrinsic brittleness as well as the solubility in water, which prevent the fabrication of SF-based electronics through traditional techniques. In this article, a flexible and stretchable silver nanofibers (Ag NFs)/SF based electrode is synthesized through water-free procedures, which demonstrates outstanding performance, i.e., low sheet resistance (10.5 Ω sq-1 ), high transmittance (>90%), excellent stability even after bending cycles >2200 times, and good extensibility (>60% stretching). In addition, on the basis of such advanced (Ag NFs)/SF electrode, a flexible and tactile sensor is further fabricated, which can simultaneously detect pressure and strain signals with a large monitoring window (35 Pa-700 kPa). Besides, this sensor is air-permeable and inflammation-free, so that it can be directly laminated onto human skins for long-term health monitoring. Considering the biodegradable and skin-comfortable features, this sensor may become promising to find potential applications in on-skin or implantable health-monitoring devices.

Mesoscopic-Functionalization of Silk Fibroin with Gold Nanoclusters Mediated by Keratin and Bioinspired Silk Synapse.

Silk fibroin (SF) offers great opportunities in manufacturing biocompatible/partially biodegradable devices with environmental benignity and biomedical applications. To obtain active SF devices of next generation, this work is to demonstrate a new functionalization strategy of the mesoscopic functionalization for soft materials. Unlike the atomic functionalization of solid materials, the meso-functionalization is to incorporate meso-dopants, i.e., functional molecules or nanomaterials, quantum dots, into the mesoscopic networks of soft materials. In this work, wool keratin (WK) molecules were adopted as mediating molecules to incorporate gold nanoclusters (AuNCs), into the mesoscopic networks of SF. It follows from our analyses that the ß-crystallites between WK and SF molecules establish the binding between WK@AuNCs and the SF networks. The incorporated WK@AuNCs are electron rich and serve as electronically charged nano particles to bridge the growth of Ag filaments in bio-degradable WK@AuNCs-SF memristors. The meso-functionalization can greatly enhance the performance of SF materials and endows them with new functionalities. This can be highlighted by biocompatible/partly degradable WK@AuNCs functionalized SF resistive random-access memories, having the enhanced resistive switching memory performance, and the unique synapse characteristics and the capability of synapse learning compared with neat SF devices, and of great importance in nonvolatile memory, analog circuits, and neuromorphic applications.