Jason Hom

Reperfusion Is a More Accurate Predictor of Follow-Up Infarct Volume Than Recanalization: A Proof of Concept Using CT in Acute Ischemic Stroke Patients

Background and Purpose— The purpose of this study was to compare recanalization and reperfusion in terms of their predictive value for imaging outcomes (follow-up infarct volume, infarct growth, salvaged penumbra) and clinical outcome in acute ischemic stroke patients. Material and Methods— Twenty-two patients admitted within 6 hours of stroke onset were retrospectively included in this study. These patients underwent a first stroke CT protocol including CT-angiography (CTA) and perfusion-CT (PCT) on admission, and similar imaging after treatment, typically around 24 hours, to assess recanalization and reperfusion. Recanalization was assessed by comparing arterial patency on admission and posttreatment CTAs; reperfusion, by comparing the volumes of CBV, CBF, and MTT abnormality on admission and posttreatment PCTs. Collateral flow was graded on the admission CTA. Follow-up infarct volume was measured on the discharge noncontrast CT. The groups of patients with reperfusion, no reperfusion, recanalization, and no recanalization were compared in terms of imaging and clinical outcomes. Results— Reperfusion (using an MTT reperfusion index >75%) was a more accurate predictor of follow-up infarct volume than recanalization. Collateral flow and recanalization were not accurate predictors of follow-up infarct volume. An interaction term was found between reperfusion and the volume of the admission penumbra >50 mL. Conclusion— Our study provides evidence that reperfusion is a more accurate predictor of follow-up infarct volume in acute ischemic stroke patients than recanalization. We recommend an MTT reperfusion index >75% to assess therapy efficacy in future acute ischemic stroke trials that use perfusion-CT.

Blood-brain barrier permeability assessed by perfusion ct predicts symptomatic hemorrhagic transformation and malignant edema in acute ischemic stroke

Symptomatic hemorrhagic transformation and malignant edema are the most feared complications of cerebral infarction, particularly after systemic thrombolysis; why are patients prone to develop them? These investigators retrospectively analyzed data obtained from 32 patients and gave special attention to the permeability of the blood-brain barrier (as measured by perfusion CT). Six patients developed SHT and/or ME and most had received either intravenous or intra-arterial tPA plus mechanical clot retrieval. Abnormal admission BBB permeability measurements were 100% sensitive and 79% specific in identifying patients who developed these dreaded complications. Also, all of these patients were older than 65 years of age. BACKGROUND AND PURPOSE: SHT and ME are feared complications in patients with acute ischemic stroke. They occur >10 times more frequently in tPA-treated versus placebo-treated patients. Our goal was to evaluate the sensitivity and specificity of admission BBBP measurements derived from PCT in predicting the development of SHT and ME in patients with acute ischemic stroke. MATERIALS AND METHODS: We retrospectively analyzed a dataset consisting of 32 consecutive patients with acute ischemic stroke with appropriate admission and follow-up imaging. We calculated admission BBBP by using delayed-acquisition PCT data and the Patlak model. Collateral flow was assessed on the admission CTA, while recanalization and reperfusion were assessed on the follow-up CTA and PCT, respectively. SHT and ME were defined according to ECASS III criteria. Clinical data were obtained from chart review. In our univariate and forward selection−based multivariate analysis for predictors of SHT and ME, we incorporated both clinical and imaging variables, including age, admission NIHSS score, admission blood glucose level, admission blood pressure, time from symptom onset to scanning, treatment type, admission PCT–defined infarct volume, admission BBBP, collateral flow, recanalization, and reperfusion. Optimal sensitivity and specificity for SHT and ME prediction were calculated by using ROC analysis. RESULTS: In our sample of 32 patients, 3 developed SHT and 3 developed ME. Of the 3 patients with SHT, 2 received IV tPA, while 1 received IA tPA and treatment with the Merci device; of the 3 patients with ME, 2 received IV tPA, while 1 received IA tPA and treatment with the Merci device. Admission BBBP measurements above the threshold were 100% sensitive and 79% specific in predicting SHT and ME. Furthermore, all patients with SHT and ME—and only those with SHT and ME—had admission BBBP measurements above the threshold, were older than 65 years of age, and received tPA. Admission BBBP, age, and tPA were the independent predictors of SHT and ME in our forward selection−based multivariate analysis. Of these 3 variables, only BBBP measurements and age were known before making the decision of administering tPA and thus are clinically meaningful. CONCLUSIONS: Admission BBBP, a pretreatment measurement, was 100% sensitive and 79% specific in predicting SHT and ME.

Multiparametric MRI and CT Models of Infarct Core and Favorable Penumbral Imaging Patterns in Acute Ischemic Stroke

Background and Purpose— Objective imaging methods to identify optimal candidates for late recanalization therapies are needed. The study goals were (1) to develop magnetic resonance imaging (MRI) and computed tomography (CT) multiparametric, voxel-based predictive models of infarct core and penumbra in acute ischemic stroke patients, and (2) to develop patient-level imaging criteria for favorable penumbral pattern based on good clinical outcome in response to successful recanalization. Methods— An analysis of imaging and clinical data was performed on 2 cohorts of patients (one screened with CT, the other with MRI) who underwent successful treatment for large vessel, anterior circulation stroke. Subjects were divided 2:1 into derivation and validation cohorts. Pretreatment imaging parameters independently predicting final tissue infarct and final clinical outcome were identified. Results— The MRI and CT models were developed and validated from 34 and 32 patients, using 943 320 and 1 236 917 voxels, respectively. The derivation MRI and 2-branch CT models had an overall accuracy of 74% and 80%, respectively, and were independently validated with an accuracy of 71% and 79%, respectively. The imaging criteria of (1) predicted infarct core ⩽90 mL and (2) ratio of predicted infarct tissue within the at-risk region ⩽70% identified patients as having a favorable penumbral pattern with 78% to 100% accuracy. Conclusions— Multiparametric voxel-based MRI and CT models were developed to predict the extent of infarct core and overall penumbral pattern status in patients with acute ischemic stroke who may be candidates for late recanalization therapies. These models provide an alternative approach to mismatch in predicting ultimate tissue fate.

Dynamic Perfusion CT Assessment of the Blood-Brain Barrier Permeability: First Pass versus Delayed Acquisition

BACKGROUND AND PURPOSE: The Patlak model has been applied to first-pass perfusion CT (PCT) data to extract information on blood-brain barrier permeability (BBBP) to predict hemorrhagic transformation in patients with acute stroke. However, the Patlak model was originally described for the delayed steady-state phase of contrast circulation. The goal of this study was to assess whether the first pass or the delayed phase of a contrast bolus injection better respects the assumptions of the Patlak model for the assessment of BBBP in patients with acute stroke by using PCT. MATERIALS AND METHODS: We retrospectively identified 125 consecutive patients (29 with acute hemispheric stroke and 96 without) who underwent a PCT study by using a prolonged acquisition time up to 3 minutes. The Patlak model was applied to calculate BBBP in ischemic and nonischemic brain tissue. Linear regression of the Patlak plot was performed separately for the first pass and for the delayed phase of the contrast bolus injection. Patlak linear regression models for the first pass and the delayed phase were compared in terms of their respective square root mean squared errors (√MSE) and correlation coefficients (R) by using generalized estimating equations with robust variance estimation. RESULTS: BBBP values calculated from the first pass were significantly higher than those from the delayed phase, both in nonischemic brain tissue (2.81 mL × 100 g−1 × min−1 for the first pass versus 1.05 mL × 100 g−1 × min−1 for the delayed phase, P < .001) and in ischemic tissue (7.63 mL × 100 g−1 × min−1 for the first pass versus 1.31 mL × 100 g−1 × min−1 for the delayed phase, P < .001). Compared with regression models from the first pass, Patlak regression models obtained from the delayed data were of better quality, showing significantly lower √MSE and higher R. CONCLUSION: Only the delayed phase of PCT acquisition respects the assumptions of linearity of the Patlak model in patients with and without stroke.

Optimal Duration of Acquisition for Dynamic Perfusion CT Assessment of Blood-Brain Barrier Permeability Using the Patlak Model

BACKGROUND AND PURPOSE: A previous study demonstrated the need to use delayed acquisition rather than first-pass data for accurate blood-brain barrier permeability surface product (BBBP) calculation from perfusion CT (PCT) according to the Patlak model, but the optimal duration of the delayed acquisition has not been established. Our goal was to determine the optimal duration of the delayed PCT acquisition to obtain accurate BBBP measurements while minimizing potential motion artifacts and radiation dose. MATERIALS AND METHODS: We retrospectively identified 23 consecutive patients with acute ischemic anterior circulation stroke who underwent a PCT study with delayed acquisition. The Patlak model was applied for the full delayed acquisition (90–240 seconds) and also for truncated analysis windows (90–210, 90–180, 90–150, 90–120 seconds). Linear regression of Patlak plots was performed separately for the full and truncated analysis windows, and the slope of these regression lines was used to indicate BBBP. The full and truncated analysis windows were compared in terms of the resulting BBBP values and the quality of the Patlak fitting. RESULTS: BBBP values in the infarct and penumbra were similar for the full 90- to 240-second acquisition (95% confidence intervals for the infarct and penumbra: 1.62–2.47 and 1.75–2.41 mL ×100 g−1 × min−1, respectively) and the 90- to 210-second analysis window (1.82–2.76 and 2.01–2.74 mL × 100 g−1 × min−1, respectively). BBBP values increased significantly with shorter acquisitions. The quality of the Patlak fit was excellent for the full 90- to 240-second and 90- to 210-second acquisitions, but it degraded with shorter acquisitions. CONCLUSIONS: The duration for the delayed PCT acquisition should be at least 210 seconds, because acquisitions shorter than 210 seconds lead to significantly overestimated BBBP values.

Validation of In Vivo Magnetic Resonance Imaging Blood–Brain Barrier Permeability Measurements by Comparison With Gold Standard Histology

Background and Purpose— We sought to validate the blood–brain barrier permeability measurements extracted from perfusion-weighted MRI through a relatively simple and frequently applied model, the Patlak model, by comparison with gold standard histology in a rat model of ischemic stroke. Methods— Eleven spontaneously hypertensive rats and 11 Wistar rats with unilateral 2-hour filament occlusion of the right middle cerebral artery underwent imaging during occlusion at 4 hours and 24 hours after reperfusion. Blood–brain barrier permeability was imaged by gradient echo imaging after the first pass of the contrast agent bolus and quantified by a Patlak analysis. Blood–brain barrier permeability was shown on histology by the extravasation of Evans blue on fluorescence microscopy sections matching location and orientation of MR images. Cresyl-violet staining was used to detect and characterize hemorrhage. Landmark-based elastic image registration allowed a region-by-region comparison of permeability imaging at 24 hours with Evans blue extravasation and hemorrhage as detected on histological slides obtained immediately after the 24-hour image set. Results— Permeability values in the nonischemic tissue (marginal mean±SE: 0.15±0.019 mL/min[Combining Dot Above]100 g) were significantly lower compared to all permeability values in regions of Evans blue extravasation or hemorrhage. Permeability values in regions of weak Evans blue extravasation (0.23±0.016 mL/min[Combining Dot Above]100 g) were significantly lower compared to permeability values of in regions of strong Evans blue extravasation (0.29±0.020 mL/min[Combining Dot Above]100 g) and macroscopic hemorrhage (0.35±0.049 mL/min[Combining Dot Above]100 g). Permeability values in regions of microscopic hemorrhage (0.26±0.024 mL/min[Combining Dot Above]100 g) only differed significantly from values in regions of nonischemic tissue (0.15±0.019 mL/min[Combining Dot Above]100 g). Conclusions— Areas of increased permeability measured in vivo by imaging coincide with blood–brain barrier disruption and hemorrhage observed on gold standard histology.

Accuracy and anatomical coverage of perfusion CT assessment of the blood-brain barrier permeability: one bolus versus two boluses.

Purpose: To assess whether blood-brain barrier permeability (BBBP) values, extracted with the Patlak model from the second perfusion CT (PCT) contrast bolus, are significantly lower than the values extracted from the first bolus in the same patient. Materials and Methods: 125 consecutive patients (29 with acute hemispheric stroke and 96 without stroke) who underwent a PCT study using a prolonged acquisition time up to 3 min were retrospectively identified. The Patlak model was applied to calculate the rate of contrast leakage out of the vascular compartment. Patlak plots were created from the arterial and parenchymal time enhancement curves obtained in multiple regions of interest drawn in ischemic brain tissue and in nonischemic brain tissue. The slope of a regression line fit to the Patlak plot was used as an indicator of BBBP. Square roots of the mean squared errors and correlation coefficients were used to describe the quality of the linear regression model. This was performed separately for the first and the second PCT bolus. Results from the first and the second bolus were compared in terms of BBBP values and the quality of the linear model fitted to the Patlak plot, using generalized estimating equations with robust variance estimation. Results: BBBP values from the second bolus were not lower than BBBP values from the first bolus in either nonischemic brain tissue [estimated mean with 95% confidence interval: 1.42 (1.10–1.82) ml·100 g–1·min–1 for the first bolus versus 1.64 (1.31–2.05) ml·100 g–1·min–1 for the second bolus, p = 1.00] or in ischemic tissue [1.04 (0.97–1.12) ml·100 g–1·min–1 for the first bolus versus 1.19 (1.11–1.28) ml·100 g–1·min–1 for the second bolus, p = 0.79]. Compared to regression models from the first bolus, the Patlak regression models obtained from the second bolus were of similar or slightly better quality. This was true both in nonischemic and ischemic brain tissue. Conclusion: The contrast material from the first bolus of contrast for PCT does not negatively influence measurements of BBBP values from the second bolus. The second bolus can thus be used to increase anatomical coverage of BBBP assessment using PCT.

Delay Correction for the Assessment of Blood-Brain Barrier Permeability Using First-Pass Dynamic Perfusion CT

SUMMARY: Hemorrhagic transformation is a serious potential complication of ischemic stroke with damage to the BBB as one of the contributing mechanisms. BBB permeability measurements extracted from PCT by using the Patlak model can provide a valuable assessment of the extent of BBB damage. Unfortunately, Patlak assumptions require extended PCT acquisition, increasing the risk of motion artifacts. A necessary correction is presented for obtaining accurate BBB permeability measurements from first-pass PCT.

The State of Medical Student Performance Evaluations: Improved Transparency or Continued Obfuscation?

Purpose The medical student performance evaluation (MSPE), a letter summarizing academic performance, is included in each medical student’s residency application. The extent to which medical schools follow Association of American Medical Colleges (AAMC) recommendations for comparative and transparent data is not known. This study’s purpose was to describe the content, interpretability, and transparency of MSPEs. Method This cross-sectional study examined one randomly selected MSPE from every Liaison Committee on Medical Education–accredited U.S. medical school from which at least one student applied to the Stanford University internal medical residency program during the 2013–2014 application cycle. The authors described the number, distribution, and range of key words and clerkship grades used in the MSPEs and the proportions of schools with missing or incomplete data. Results The sample included MSPEs from 117 (89%) of 131 medical schools. Sixty schools (51%) provided complete information about clerkship grade and key word distributions. Ninety-six (82%) provided comparative data for clerkship grades, and 71 (61%) provided complete key word data. Key words describing overall performance were extremely heterogeneous, with a total of 72 used and great variation in the assignment of the top designation (median: 24% of students; range: 1%–60%). There was also great variation in the proportion of students awarded the top internal medicine clerkship grade (median: 29%; range: 2%–90%). Conclusions The MSPE is a critical component of residency applications, yet data contained within MSPEs are incomplete and variable. Approximately half of U.S. medical schools do not follow AAMC guidelines for MSPEs.

Hospitalist intervention for appropriate use of telemetry reduces length of stay and cost

BACKGROUND Telemetry monitoring is a widely used, labor-intensive, and often-limited resource. Little is known of the effectiveness of methods to guide appropriate use. OBJECTIVE Our intervention for appropriate use included: (1) a hospitalist-led, daily review of bed utilization, (2) hospitalist-driven education module for trainees, (3) quarterly feedback of telemetry usage, and (4) financial incentives. DESIGN/METHODS Hospitalists were encouraged to discuss daily telemetry utilization on rounds. A module on appropriate telemetry usage was taught by hospitalists during the intervention period (January 2013-August 2013) on medicine wards. Pre- and post-evaluations measured changes regarding telemetry use. We compared hospital bed-use data between the baseline period (January 2012-December 2012), intervention period, and extension period (September 2014-March 2015). During the intervention period, hospital bed-use data were sent to the hospitalist group quarterly. Financial incentives were provided after a decrease in hospitalist telemetry utilization. SETTING Stanford Hospital, a 444-bed, academic medical center in Stanford, California. RESULTS Hospitalists saw reductions for both length of stay (LOS) (2.75 vs 2.13 days, P = 0.005) and total cost (22.5% reduction) for telemetry bed utilization in the intervention period. Nonhospitalists telemetry bed utilization remained unchanged. We saw significant improvements in trainee knowledge of the most cost-saving action (P = 0.002) and the least cost-saving action (P = 0.003) in the pre- and post-evaluation analyses. Results were sustained in the hospitalist group, with telemetry LOS of 1.93 days in the extension period. CONCLUSIONS A multipronged, hospitalist-driven intervention to improve appropriate use of telemetry reduces LOS and cost, and increases knowledge of cost-saving actions among trainees.