Inter-scanner variability in Hounsfield unit measured by CT of the brain and effect on gray-to-white matter ratio

Analysis of Cerebral CT Based on Supervised Machine Learning as a Predictor of Outcome After Out-of-Hospital Cardiac Arrest

BACKGROUND AND OBJECTIVES

In light of limited intensive care capacities and a lack of accurate prognostic tools to advise caregivers and family members responsibly, this study aims to determine whether automated cerebral CT (CCT) analysis allows prognostication after out-of-hospital cardiac arrest.

METHODS

In this monocentric, retrospective cohort study, a supervised machine learning classifier based on an elastic net regularized logistic regression model for gray matter alterations on nonenhanced CCT obtained after cardiac arrest was trained using 10-fold cross-validation and tested on a hold-out sample (random split 75%/25%) for outcome prediction. Following the literature, a favorable outcome was defined as a cerebral performance category of 1-2 and a poor outcome of 3-5. The diagnostic accuracy was compared with established and guideline-recommended prognostic measures within the sample, that is, gray matter-white matter ratio (GWR), neuron-specific enolase (NSE), and neurofilament light chain (NfL) in serum.

RESULTS

Of 279 adult patients, 132 who underwent CCT within 14 days of cardiac arrest with good imaging quality were identified. Our approach discriminated between favorable and poor outcomes with an area under the curve (AUC) of 0.73 (95% CI 0.59-0.82). Thus, the prognostic power outperformed the GWR (AUC 0.66, 95% CI 0.56-0.76). The biomarkers NfL, measured at days 1 and 2, and NSE, measured at day 2, exceeded the reliability of the imaging markers derived from CT (AUC NfL day 1: 0.87, 95% CI 0.75-0.99; AUC NfL day 2: 0.90, 95% CI 0.79-1.00; AUC NSE day: 2 0.78, 95% CI 0.62-0.94).

DISCUSSION

Our data show that machine learning-assisted gray matter analysis of CCT images offers prognostic information after out-of-hospital cardiac arrest. Thus, CCT gray matter analysis could become a reliable and time-independent addition to the standard workup with serum biomarkers sampled at predefined time points. Prospective studies are warranted to replicate these findings.

Regional Brain Net Water Uptake in Computed Tomography after Cardiac Arrest - A Novel Biomarker for Neuroprognostication

BACKGROUND

Selective water uptake by neurons and glial cells and subsequent brain tissue oedema are key pathophysiological processes of hypoxic-ischemic encephalopathy (HIE) after cardiac arrest (CA). Although brain computed tomography (CT) is widely used to assess the severity of HIE, changes of brain radiodensity over time have not been investigated. These could be used to quantify regional brain net water uptake (NWU), a potential prognostic biomarker.

METHODS

We conducted an observational prognostic accuracy study including a derivation (single center cardiac arrest registry) and a validation (international multicenter TTM2 trial) cohort. Early (<6 h) and follow-up (>24 h) head CTs of CA patients were used to determine regional NWU for grey and white matter regions after co-registration with a brain atlas. Neurological outcome was dichotomized as good versus poor using the Cerebral Performance Category Scale (CPC) in the derivation cohort and Modified Rankin Scale (mRS) in the validation cohort.

RESULTS

We included 115 patients (81 derivation, 34 validation) with out-of-hospital (OHCA) and in-hospital cardiac arrest (IHCA). Regional brain water content remained unchanged in patients with good outcome. In patients with poor neurological outcome, we found considerable regional water uptake with the strongest effect in the basal ganglia. NWU >8% in the putamen and caudate nucleus predicted poor outcome with 100% specificity (95%-CI: 86-100%) and 43% (moderate) sensitivity (95%-CI: 31-56%).

CONCLUSION

This pilot study indicates that NWU derived from serial head CTs is a promising novel biomarker for outcome prediction after CA. NWU >8% in basal ganglia grey matter regions predicted poor outcome while absence of NWU indicated good outcome. NWU and follow-up CTs should be investigated in larger, prospective trials with standardized CT acquisition protocols.

Association between quantitative analysis of cerebral edema using CT imaging and neurological outcomes in cardiac arrest survivors

BACKGROUND

To determine if the density distribution proportion of Hounsfield unit (HUdp) in head computed tomography (HCT) images can be used to quantitatively measure cerebral edema in survivors of out-of-hospital cardiac arrest (OHCA).

METHODS

This retrospective observational study included adult comatose OHCA survivors who underwent HCT within 6 h (first) and 72-96 h (second), all performed using the same CT scanner. Semi-automated quantitative analysis was used to identify differences in HUdp at specific HU ranges across the intracranial component based on neurological outcome. Cerebral edema was defined as the increased displacement of the sum of HUdp values (ΔHUdp) at a specific range between two HCT scans. Poor neurological outcome was defined as cerebral performance categories 3-5 at 6 months after OHCA.

RESULTS

Twenty-three (42%) out of 55 patients had poor neurological outcome. Significant HUdp differences were observed between good and poor neurological outcomes in the second HCT scan at HU = 1-14, 23-35, and 39-56 (all P < 0.05). Only the ΔHUdp = 23-35 range showed a significant increase and correlation in the poor neurological outcome group (4.90 vs. -0.72, P < 0.001) with the sum of decreases in the other two ranges (r = 0.97, P < 0.001). Multivariate logistic regression analysis demonstrated a significant association between ΔHUdp = 23-35 range and poor neurological outcomes (adjusted OR, 1.12; 95% CI: 1.02-1.24; P = 0.02).

CONCLUSION

In this cohort study, the increased displacement in ΔHUdp = 23-35 range is independently associated with poor neurological outcome and provides a quantitative assessment of cerebral edema formation in OHCA survivors.

Changes in temporal muscle dimensions and their clinical impact in out-of-hospital cardiac arrest survivors

Objective

This study investigates temporal muscle atrophy in out-of-hospital cardiac arrest patients post-resuscitation, seeking associations with neurological outcomes and factors associated with atrophy.

Methods

Using data from six Japanese intensive care units, adult patients' post-resuscitation who underwent head computed tomography scans on admission and two to five days post-admission were assessed. Temporal muscle area, thickness, and density were quantified from a single cross-sectional image. Patients were categorized into 'atrophy' or 'no atrophy' groups based on median daily temporal muscle atrophy rates. The primary outcome was changes in temporal muscle dimensions between admission and follow-up two to five days later. Secondary outcomes included assessing the impact of temporal muscle atrophy on 30-day survival, as well as identifying any clinical factors associated with temporal muscle atrophy.

Results

A total of 185 patients were analyzed. Measurements at follow-up revealed significant decreases in temporal muscle area (214 vs. 191 mm2, p < 0.001), thickness (4.9 vs. 4.7 mm, p < 0.001), and density (46 vs. 44 HU, p < 0.001) compared to those at admission. The median daily rate for temporal muscle area atrophy was 2.0% per day. There was no significant association between temporal muscle atrophy and 30-day survival (hazard ratios, 0.71; 95% CI, 0.41-1.23, p = 0.231). Multivariable logistic regression found no clinical factors significantly associated with temporal muscle atrophy.

Conclusions

Temporal muscle atrophy in post-resuscitation patients occurs rapidly at 2.0% per day. However, there was no significant association with 30-day mortality or any identified clinical factors. Further investigation into its long-term functional implications is warranted.

Aberration correction in abdominal histotripsy

In transabdominal histotripsy, ultrasound pulses are focused on the body to noninvasively destroy soft tissues via cavitation. However, the ability to focus is limited by phase aberration, or decorrelation of the ultrasound pulses due to spatial variation in the speed of sound throughout heterogeneous tissue. Phase aberration shifts, broadens, and weakens the focus, thereby reducing the safety and efficacy of histotripsy therapy. This paper reviews and discusses aberration effects in histotripsy and in related therapeutic ultrasound techniques (e.g., high intensity focused ultrasound), with an emphasis on aberration by soft tissues. Methods for aberration correction are reviewed and can be classified into two groups: model-based methods, which use segmented images of the tissue as input to an acoustic propagation model to predict and compensate phase differences, and signal-based methods, which use a receive-capable therapy array to detect phase differences by sensing acoustic signals backpropagating from the focus. The relative advantages and disadvantages of both groups of methods are discussed. Importantly, model-based methods can correct focal shift, while signal-based methods can restore substantial focal pressure, suggesting that both methods should be combined in a 2-step approach. Aberration correction will be critical to improving histotripsy treatments and expanding the histotripsy treatment envelope to enable non-invasive, non-thermal histotripsy therapy for more patients.

The Role of CT Angiography to Predict the Shamblin Group in Carotid Body Tumors

Carotid body tumors (CBTs) are uncommon benign head and neck neoplasms. Surgical resection is the treatment of choice for CBTs. However, the anatomical structures adjacent to the tumor tissue may encounter serious injuries during the surgery. Shamblin grading system is a surgical intra-operative scoring system to determine the risks associated with the surgery. Therefore, we aimed to evaluate the correlation of pre-surgical imaging parameters with Shamblin grades and intra-operative complications. In this cross sectional study, we enrolled 36 patients with CBTs. Preoperative cervical CT angiography was acquired in each participant and following parameters were reported in each case: Tumor volume, tumor distance to the base of the skull (TDBS), tumor contact with the internal carotid artery (ICA), and external carotid artery (ECA) and tumor density. Finally, we assessed the relation of pre-surgical imaging parameters with Shamblin grades, and intra-operative complications. Only tumor volume was significantly correlated with Shamblin grades (P < 0.05). The tumor contact with ECA was marginally correlated with Shamblin grades (P = 0.103); however, other imaging parameters were not significantly correlating with Shamblin grades. There was a statistically significant correlation between ICA contact and tumor volume with ECA injury. In addition, the tumor density significantly correlated with cranial nerves injury. The results of STATA analysis were indicative for 69.44% accordance between radiologic typing and Shamblin grading system. We found that tumor volume correlates significantly with Shamblin grading system, and there is significant correlation between tumor ICA contact, and tumor density and intra-operative complications.

The Effect of Craniofacial Manual Lymphatic Drainage after Moderate Traumatic Brain Injury

Previous studies suggest that craniofacial manual lymphatic drainage (MLD) facilitates brain fluids clearance, reducing intracranial pressure and reabsorbing chronic subdural hematoma. This study aimed to explore the effect of craniofacial MLD in combination with pharmacological treatment for improving cranial pain intensity, vital signs, and cerebral edema (Hounsfield units, HUs) in moderate traumatic brain injury (mTBI). Patient 1 received pharmacological therapy, while patient 2 received both pharmacological and craniocervical MLD treatment. Patient 2 showed decreased cranial pain intensity and systolic blood pressure (66%-11.11%, respectively) after two 30 min daily sessions of treatment for three days. HUs in the caudate nucleus of both hemispheres (left 24.64%-right 28.72%) and in the left temporal cortical gray matter increased (17.8%). An increase in HU suggests a reduction in cerebral edema and vice versa. For patient 1, there were no changes in cranial pain intensity, but a slight increase in the systolic blood pressure was observed (0%-3.27%, respectively). HUs decreased in the temporal cortical (14.98%) and caudate nucleus gray matter (9.77%) of the left and right cerebral hemispheres (11.96%-16.74%, respectively). This case study suggests that craniofacial MLD combined with pharmacological treatment could reduce cerebral edema, decrease head pain intensity, and maintain vital signs in normal physiologic values in patients with mTBI.

Brain injury markers in blood predict signs of hypoxic ischaemic encephalopathy on head computed tomography after cardiac arrest

BACKGROUND/AIM

Signs of hypoxic ischaemic encephalopathy (HIE) on head computed tomography (CT) predicts poor neurological outcome after cardiac arrest. We explore whether levels of brain injury markers in blood could predict the likelihood of HIE on CT.

METHODS

Retrospective analysis of CT performed at 24-168 h post cardiac arrest on clinical indication within the Target Temperature Management after out-of-hospital cardiac arrest-trial. Biomarkers prospectively collected at 24- and 48 h post-arrest were analysed for neuron specific enolase (NSE), neurofilament light (NFL), total-tau and glial fibrillary acidic protein (GFAP). HIE was assessed through visual evaluation and quantitative grey-white-matter ratio (GWR) was retrospectively calculated on Swedish subjects with original images available.

RESULTS

In total, 95 patients were included. The performance to predict HIE on CT (performed at IQR 73-116 h) at 48 h was similar for all biomarkers, assessed as area under the receiving operating characteristic curve (AUC) NSE 0.82 (0.71-0.94), NFL 0.79 (0.67-0.91), total-tau 0.84 (0.74-0.95), GFAP 0.79 (0.67-0.90). The predictive performance of biomarker levels at 24 h was AUC 0.72-0.81. At 48 h biomarker levels below Youden Index accurately excluded HIE in 77.3-91.7% (negative predictive value) and levels above Youden Index correctly predicted HIE in 73.3-83.7% (positive predictive value). NSE cut-off at 48 h was 48 ng/ml. Elevated biomarker levels irrespective of timepoint significantly correlated with lower GWR.

CONCLUSION

Biomarker levels can assess the likelihood of a patient presenting with HIE on CT and could be used to select suitable patients for CT-examination during neurological prognostication in unconscious cardiac arrest patients.

Evaluation of the quantitative performance of non-enhanced dual-energy CT X-map in detecting acute ischemic brain stroke: A model observer study using computer simulation

PURPOSE

A simulation study was performed to evaluate the quantitative performance of X-map images-derived from non-enhanced (NE) dual-energy computed tomography (DECT)-in detecting acute ischemic stroke (AIS) compared with that of NE-DECT mixed images.

METHODS

A virtual phantom, 150 mm in diameter, filled with tissues comprising various gray- and white-matter proportions was used to generate pairs of NE-head images at 80 kV and Sn150 kV at three dose levels (20, 40, and 60 mGy). The phantom included an inserted low-contrast object, 15 mm in diameter, with four densities (0%, 5%, 10%, and 15%) mimicking ischemic edema. Mixed and X-map images were generated from these sets of images and compared in terms of detectability of ischemic edema using a channelized Hotelling observer (CHO). The area under the curve (AUC) of the receiver operating characteristic that generated CHO for each condition was used as a figure of merit.

RESULTS

The AUCs of X-map images were always significantly higher than those of mixed images (P < 0.001). The improvement in AUC for X-map images compared with that for mixed images at edema densities was 9.2%-12.6% at 20 mGy, 10.1%-17.7% at 40 mGy, and 14.0%-19.4% at 60 mGy. At any edema density, X-map images at 20 mGy resulted in higher AUCs than mixed images acquired at any other dose level (P < 0.001), which corresponded to a 66% dose reduction on X-map images.

CONCLUSIONS

The simulation study confirmed that NE-DECT X-map images have superior capability of detecting AIS than NE-DECT mixed images.

Inter-rater agreement between humans and computer in quantitative assessment of computed tomography after cardiac arrest

Background

Head computed tomography (CT) is used to predict neurological outcome after cardiac arrest (CA). The current reference standard includes quantitative image analysis by a neuroradiologist to determine the Gray-White-Matter Ratio (GWR) which is calculated via the manual measurement of radiodensity in different brain regions. Recently, automated analysis methods have been introduced. There is limited data on the Inter-rater agreement of both methods.

Methods

Three blinded human raters (neuroradiologist, neurologist, student) with different levels of clinical experience retrospectively assessed the Gray-White-Matter Ratio (GWR) in head CTs of 95 CA patients. GWR was also quantified by a recently published computer algorithm that uses coregistration with standardized brain spaces to identify regions of interest (ROIs). We calculated intraclass correlation (ICC) for inter-rater agreement between human and computer raters as well as area under the curve (AUC) and sensitivity/specificity for poor outcome prognostication.

Results

Inter-rater agreement on GWR was very good (ICC 0.82–0.84) between all three human raters across different levels of expertise and between the computer algorithm and neuroradiologist (ICC 0.83; 95% CI 0.78–0.88). Despite high overall agreement, we observed considerable, clinically relevant deviations of GWR measurements (up to 0.24) in individual patients. In our cohort, at a GWR threshold of 1.10, this did not lead to any false poor neurological outcome prediction.

Conclusion

Human and computer raters demonstrated high overall agreement in GWR determination in head CTs after CA. The clinically relevant deviations of GWR measurement in individual patients underscore the necessity of additional qualitative evaluation and integration of head CT findings into a multimodal approach to prognostication of neurological outcome after CA.

Prognostic accuracy of head computed tomography for prediction of functional outcome after out-of-hospital cardiac arrest: Rationale and design of the prospective TTM2-CT-substudy

Background

Head computed tomography (CT) is a guideline recommended method to predict functional outcome after cardiac arrest (CA), but standardized criteria for evaluation are lacking. To date, no prospective trial has systematically validated methods for diagnosing hypoxic-ischaemic encephalopathy (HIE) on CT after CA. We present a protocol for validation of pre-specified radiological criteria for assessment of HIE on CT for neuroprognostication after CA.

Methods/design

This is a prospective observational international multicentre substudy of the Targeted Hypothermia versus Targeted Normothermia after out-of-hospital cardiac arrest (TTM2) trial. Patients still unconscious 48 hours post-arrest at 13 participating hospitals were routinely examined with CT. Original images will be evaluated by examiners blinded to clinical data using a standardized protocol. Qualitative assessment will include evaluation of absence/presence of "severe HIE". Radiodensities will be quantified in pre-specified regions of interest for calculation of grey-white matter ratios (GWR) at the basal ganglia level. Functional outcome will be dichotomized into good (modified Rankin Scale 0-3) and poor (modified Rankin Scale 4-6) at six months post-arrest. Prognostic accuracies for good and poor outcome will be presented as sensitivities and specificities with 95% confidence intervals (using pre-specified cut-offs for quantitative analysis), descriptive statistics (Area Under the Receiver Operating Characteristics Curve), inter- and intra-rater reliabilities according to STARD guidelines.

Conclusions

The results from this prospective trial will validate a standardized approach to radiological evaluations of HIE on CT for prediction of functional outcome in comatose CA patients.The TTM2 trial and the TTM2 CT substudy are registered at ClinicalTrials.gov NCT02908308 and NCT03913065.

A pilot study of methods for prediction of poor outcome by head computed tomography after cardiac arrest

INTRODUCTION

In Sweden, head computed tomography (CT) is commonly used for prediction of neurological outcome after cardiac arrest, as recommended by guidelines. We compare the prognostic ability and interrater variability of routine and novel CT methods for prediction of poor outcome.

METHODS

Retrospective study including patients from Swedish sites within the Target Temperature Management after out-of-hospital cardiac arrest trial examined with CT. Original images were assessed by two independent radiologists blinded from clinical data with eye-balling without pre-specified criteria, and with a semi-quantitative assessment. Grey-white-matter ratios (GWR) were quantified using models with 4-20 manually placed regions of interest. Prognostic abilities and interrater variability were calculated for prediction of poor outcome (modified Rankin Scale 4-6 at six months) for early (<24h) and late (≥24h) examinations.

RESULTS

68/106 (64%) of included patients were examined <24h post-arrest. Eye-balling predicted poor outcome with 89-100% specificity and 15-78% sensitivity. GWR <24h predicted neurological outcome with unsatisfactory to satisfactory Area Under the Receiver Operating Characteristics Curve (AUROC: 0.54-0.64). GWR ≥24h yielded very good to excellent AUROC (0.80-0.93). Sensitivities increased >2-3 fold in examinations performed after 24h compared to early examinations. Combining eye-balling with GWR<1.15 predicted poor outcome without false positives with sensitivities remaining acceptable.

CONCLUSION

In our cohort, qualitative and quantitative CT methods predicted poor outcome with high specificity and low to moderate sensitivity. Sensitivity increased relevantly after the first 24 hours after CA. Interrater variability poses a problem and indicates the need to standardise brain CT evaluation to increase the methodś safety.

Applying Taguchi Methodology to Optimize the Brain Image Quality of 128-Sliced CT: A Feasibility Study

Injuries due to traffic accidents have been significant causes of death in Taiwan and traffic accidents have been most common in recent years. Brain computed tomography (CT) examinations can improve imaging quality and increase the value of an imaging diagnosis. The image quality of the brain gray/white matter was optimized using the Taguchi design with an indigenous polymethylmethacrylate (PMMA) slit gauge to imitate the adult brain and solid water phantoms. The two gauges without coating contrast media were located inside the center of a plate to simulate the brain and scanned to obtain images for further analysis. Five major parameters—CT slice thickness, milliampere-seconds, current voltage, filter type, and field of view—were optimized. Analysis of variance was used to determine individual interactions among all control parameters. The optimal experimental acquisition/settings were: slice thickness 2.5 mm, 300 mAs, 140 kVp, smooth filter, and FOV 200 mm2. Signal-to-noise was improved by 106% (p < 0.001) over a routine examination. The effective dose (HE) is approximately 1.33 mSv. Further clinical verification and the image quality of the ACR 464 head phantom is also discussed.

Gray-White Matter Ratio at the Level of the Basal Ganglia as a Predictor of Neurologic Outcomes in Cardiac Arrest Survivors: A Literature Review

Loss of gray-white matter discrimination is the primary early imaging finding within of cranial computed tomography in cardiac arrest survivors, and this has been also regarded as a novel predictor for evaluating neurologic outcome. As displayed clearly on computed tomography and based on sensitivity to hypoxia, the gray-white matter ratio at basal ganglia (GWR-BG) region was frequently detected to assess the neurologic outcome by several studies. The specificity of GWR-BG is 72.4 to 100%, while the sensitivity is significantly different. Herein we review the mechanisms mediating cerebral edema following cardiac arrest, demonstrate the determination procedures with respect to GWR-BG, summarize the related researches regarding GWR-BG in predicting neurologic outcomes within cardiac arrest survivors, and discuss factors associated with predicting the accuracy of this methodology. Finally, we describe the effective measurements to increase the sensitivity of GWR-BG in predicting neurologic outcome.

Differences in the gray-to-white matter ratio according to different computed tomography scanners for outcome prediction in post-cardiac arrest patients receiving target temperature management

The gray-to-white matter ratio (GWR) has been used to identify brain damage in comatose patients after cardiac arrest. However, Hounsfield units (HUs), the measurement of brain density on computed tomography (CT) images, may vary depending on the machine type or parameter. Therefore, differences in CT scanners may affect the GWR in post-cardiac arrest patients. We performed a retrospective study on comatose post-cardiac arrest patients who visited the hospital from 2007 to 2017. Two CT, Lightspeed and SOMATOM, scanners were used. Two observers independently measured the HUs of the caudate nucleus, putamen, posterior internal capsule, and corpus callosum using regions of interest. We compared the GWR calculated from the HUs measured at different CT scanners. The analysis of different scanners showed statistically significant differences in the measured HUs and GWR. The HUs and GWR of Lightspeed were measured lower than SOMATOM. The difference between the two CT scanners was also evident in groups divided by neurological prognosis. The area under the curve of the receiver operating characteristic curve to predict poor outcomes of Lightspeed was 0.798, and the cut-off value for 100% specificity was 1.172. The SOMATOM was 0.855, and the cut-off value was 1.269. The difference in scanners affects measurements and performance characteristics of the GWR in post-cardiac arrest patients. Therefore, when applying the results of the GWR study to clinical practice, reference values for each device should be presented, and an integrated plan should be prepared.

Automated Assessment of Brain CT After Cardiac Arrest-An Observational Derivation/Validation Cohort Study

Objectives

Prognostication of outcome is an essential step in defining therapeutic goals after cardiac arrest. Gray-white-matter ratio obtained from brain CT can predict poor outcome. However, manual placement of regions of interest is a potential source of error and interrater variability. Our objective was to assess the performance of poor outcome prediction by automated quantification of changes in brain CTs after cardiac arrest.

Design

Observational, derivation/validation cohort study design. Outcome was determined using the Cerebral Performance Category upon hospital discharge. Poor outcome was defined as death or unresponsive wakefulness syndrome/coma. CTs were automatically decomposed using coregistration with a brain atlas.

Setting

ICUs at a large, academic hospital with circulatory arrest center.

Patients

We identified 433 cardiac arrest patients from a large previously established database with brain CTs within 10 days after cardiac arrest.

Interventions

None.

Measurements and Main Results

Five hundred sixteen brain CTs were evaluated (derivation cohort n = 309, validation cohort n = 207). Patients with poor outcome had significantly lower radiodensities in gray matter regions. Automated GWR_si (putamen/posterior limb of internal capsule) was performed with an area under the curve of 0.86 (95%-CI: 0.80-0.93) for CTs taken later than 24 hours after cardiac arrest (similar performance in the validation cohort). Poor outcome (Cerebral Performance Category 4-5) was predicted with a specificity of 100% (95% CI, 87-100%, derivation; 88-100%, validation) at a threshold of less than 1.10 and a sensitivity of 49% (95% CI, 36-58%, derivation) and 38% (95% CI, 27-50%, validation) for CTs later than 24 hours after cardiac arrest. Sensitivity and area under the curve were lower for CTs performed within 24 hours after cardiac arrest.

Conclusions

Automated gray-white-matter ratio from brain CT is a promising tool for prediction of poor neurologic outcome after cardiac arrest with high specificity and low-to-moderate sensitivity. Prediction by gray-white-matter ratio at the basal ganglia level performed best. Sensitivity increased considerably for CTs performed later than 24 hours after cardiac arrest.

Early head CT in post-cardiac arrest patients: A helpful tool or contributor to self-fulfilling prophecy?

OBJECTIVE

Neuroprognostication guidelines suggest that early head computed tomography (HCT) might be useful in the evaluation of cardiac arrest (CA) patients following return of spontaneous circulation. We aimed to determine the impact of early HCT, performed within the first 6 h following CA, on decision-making following resuscitation.

METHODS

We identified a cohort of initially unconscious post-CA patients at a tertiary care academic medical center from 2012 to 2017. Variables pertaining to demographics, CA details, post-CA care, including neuroimaging and neurophysiologic testing, were abstracted retrospectively from the electronic medical records. Changes in management resulting from HCT findings were recorded. Blinded board-certified neurointensivists adjudicated HCT findings related to hypoxic-ischemic brain injury (HIBI) burden. The gray-white matter ratio (GWR) was also calculated.

RESULTS

Of 302 patients, 182 (60.2%) underwent HCT within six hours of CA (early HCT group). Approximately 1 in 4 early HCTs were abnormal (most commonly HIBI changes; 78.7%, n = 37), which resulted in a change in management in nearly half of cases (46.8%, n = 22). The most common changes in management were de-escalation in care [including transition to do not resuscitate status), withholding targeted temperature management, and withdrawal of life sustaining therapy (WLST)]. In cases with radiographic HIBI, mean [standard deviation] GWR was lower (1.20 [0.10] vs 1.30 [0.09], P < 0.001) and progression to brain death was higher (44.4% vs 2.9%; P < 0.001). The inter-rater reliability (IRR) of early HCT to determine presence of HIBI between radiology and three neurointensivists had a wide range (κ 0.13-0.66).

CONCLUSION

Early HCT identified abnormalities in 25% of cases and frequently influenced therapeutic decisions. Neuroimaging interpretation discrepancies between radiology and neurointensivists are common and agreement on severity of HIBI on early HCT is poor (k 0.11).

Treatment planning system and beam data validation for the ZAP-X: A novel self-shielded stereotactic radiosurgery system

PURPOSE

To evaluate the treatment planning system (TPS) performance of the ZAP-X stereotactic radiosurgery (SRS) system through nondosimetric, dosimetric, and end-to-end (E2E) tests.

METHODS

A comprehensive set of TPS commissioning and validation tests was developed using published guidelines. Nondosimetric validation tests included information transfer, computed tomography-magnetic resonance (CT-MR) image registration, structure/contouring, geometry, dose tools, and CT density. Dosimetric validation included comparisons between TPS and water tank/Solid Water measurements for various geometries and beam arrangements and end-to-end (E2E) tests. Patient-specific quality assurance was performed with an ion chamber in the Lucy phantom and with Gafchromic EBT3 film in the CyberKnife head phantom. RadCalc was used for independent verification of monitor units. Additional E2E tests were performed using the RPC Gamma Knife thermoluminescent dosimeter (TLD) phantom, MD Anderson SRS head phantom, and PseudoPatient gel phantom for independent absolute dose verification.

RESULTS

CT-MR image registrations with known translational and rotational offsets were within tolerance (<0.5 × maximum voxel dimension). Slice thickness and distance accuracy were within 0.1 mm, and volume accuracy was within 0 to 0.11 cm³ . Treatment planning system volume measurement uncertainty was within 0.1 to 0.4 cm³ . Ion chamber point-dose measurements for a single beam in a water phantom agreed to TPS-calculated values within ±4% for collimator diameters 10 to 25 mm, and ±6% for 7.5 mm, for all measured depths (7, 50, 100, 150, and 200 mm). In homogeneous Solid Water, point-dose measurements agreed to within ±4% for cones sizes 7.5 to 25 mm. With 1-cm high/low density inserts, measurements were within ±4.2% for cone sizes 10 to 25 mm. Film-based E2E using 4/5-mm cones resulted in a gamma passing rate (%GP) of 99.8% (2%/1.5 mm). Point-dose measurements in a Lucy phantom with an ion chamber using 36 beams distributed along three noncoplanar arcs agreed to within ±4% for cone sizes 10 to 25 mm. The RPC Gamma Knife TLD phantom yielded passing results with a measured-to-expected TLD dose ratio of 1.02. The MD Anderson SRS head phantom yielded passing results, with 4% TLD agreement and %GP of 95%/93% (5%/3 mm) for coronal/sagittal film planes. The RTsafe gel phantom gave %GP of >95% (5%/2 mm) for all four targets. For our first 58 patients, film-based patient-specific quality assurance has resulted in an average %GP of 98.7% (range, 94-100%) at 2%/2 mm.

CONCLUSIONS

Core ZAP-X features were found to be functional. On the basis of our results, point-dose and planar measurements were in agreement with TPS calculations using multiple phantoms and setup geometries, validating the ZAP-X TPS beam model for clinical use.

European Resuscitation Council and European Society of Intensive Care Medicine guidelines 2021: post-resuscitation care

The European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) have collaborated to produce these post-resuscitation care guidelines for adults, which are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. The topics covered include the post-cardiac arrest syndrome, diagnosis of cause of cardiac arrest, control of oxygenation and ventilation, coronary reperfusion, haemodynamic monitoring and management, control of seizures, temperature control, general intensive care management, prognostication, long-term outcome, rehabilitation and organ donation.

European Resuscitation Council and European Society of Intensive Care Medicine Guidelines 2021: Post-resuscitation care

The European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) have collaborated to produce these post-resuscitation care guidelines for adults, which are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. The topics covered include the post-cardiac arrest syndrome, diagnosis of cause of cardiac arrest, control of oxygenation and ventilation, coronary reperfusion, haemodynamic monitoring and management, control of seizures, temperature control, general intensive care management, prognostication, long-term outcome, rehabilitation, and organ donation.

Prognostic Values of the Gray-to-White Matter Ratio on Brain Computed Tomography Images for Neurological Outcomes after Cardiac Arrest: A Meta-Analysis

Materials and Methods

The PubMed, ScienceDirect, Web of Science, and China National Knowledge Infrastructure databases were searched for all relevant articles published before March 31, 2020, without any language restrictions. The pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated with a random-effects model using Stata 14.0 software.

Result

A total of 24 eligible studies with 2812 CA patients were recruited in the meta-analysis. The pooled result showed that decreased GWR was correlated with poor neurological outcomes after CA (OR = 11.28, 95% CI: 6.29–20.21, and P < 0.001) with moderate heterogeneity (I² = 71.5%, P < 0.001). The pooled sensitivity and specificity were 0.58 (95% CI: 0.47–0.68) and 0.95 (95% CI: 0.87–0.98), respectively. The area under the curve (AUC) of GWR was 0.84 (95% CI: 0.80–0.87). Compared with GWR (cerebrum) and GWR (average), GWR using the basal ganglion level of brain CT had the highest AUC of 0.87 (0.84–0.90). Subgroup analysis indicated that heterogeneity may be derived from the time of CT measurement, preset specificity, targeted temperature management, or proportion of cardiac etiology. Sensitivity analysis indicated that the result was stable, and Deeks' plot showed no possible publication bias (P = 0 .64).

Conclusion

Current research suggests that GWR, especially using the basal ganglion level of brain CT, is a useful parameter for determining neurological outcomes after CA.

Brain injury after cardiac arrest: from prognostication of comatose patients to rehabilitation

More patients are surviving cardiac arrest than ever before; however, the burden now lies with estimating neurological prognoses in a large number of patients who were initially comatose, in whom the ultimate outcome is unclear. Neurologists, neurointensivists, and clinical neurophysiologists must accurately balance the concern that overly conservative prognostication could leave patients in a severely disabled state, with the possibility that inaccurately pessimistic prognostication could lead to the withdrawal of life-sustaining treatment in patients who might otherwise have a good functional outcome. Prognostic tools have improved greatly, including electrophysiological tests, neuroimaging, and chemical biomarkers. Conclusions about the prognosis should be delayed at least 72 h after arrest to allow for the clearance of sedative drugs. Cognitive impairments, emotional problems, and fatigue are common among patients who have survived cardiac arrest, and often go unrecognised despite being related to caregiver burden and a decreased participation in society. Through simple screening, these problems can be identified, and patients can be provided with adequate information and rehabilitation.

Prediction of poor neurological outcome in comatose survivors of cardiac arrest: a systematic review

Purpose

To assess the ability of clinical examination, blood biomarkers, electrophysiology, or neuroimaging assessed within 7 days from return of spontaneous circulation (ROSC) to predict poor neurological outcome, defined as death, vegetative state, or severe disability (CPC 3–5) at hospital discharge/1 month or later, in comatose adult survivors from cardiac arrest (CA).

Methods

PubMed, EMBASE, Web of Science, and the Cochrane Database of Systematic Reviews (January 2013–April 2020) were searched. Sensitivity and false-positive rate (FPR) for each predictor were calculated. Due to heterogeneities in recording times, predictor thresholds, and definition of some predictors, meta-analysis was not performed.

Results

Ninety-four studies (30,200 patients) were included. Bilaterally absent pupillary or corneal reflexes after day 4 from ROSC, high blood values of neuron-specific enolase from 24 h after ROSC, absent N20 waves of short-latency somatosensory-evoked potentials (SSEPs) or unequivocal seizures on electroencephalogram (EEG) from the day of ROSC, EEG background suppression or burst-suppression from 24 h after ROSC, diffuse cerebral oedema on brain CT from 2 h after ROSC, or reduced diffusion on brain MRI at 2–5 days after ROSC had 0% FPR for poor outcome in most studies. Risk of bias assessed using the QUIPS tool was high for all predictors.

Conclusion

In comatose resuscitated patients, clinical, biochemical, neurophysiological, and radiological tests have a potential to predict poor neurological outcome with no false-positive predictions within the first week after CA. Guidelines should consider the methodological concerns and limited sensitivity for individual modalities. (PROSPERO CRD42019141169)

Electronic supplementary material

The online version of this article (10.1007/s00134-020-06198-w) contains supplementary material, which is available to authorized users.

Assessment of Hounsfield unit in the differential diagnosis of odontogenic cysts

OBJECTIVES

The purpose of this study was to evaluate the usefulness of Hounsfield unit (HU) assessment with multislice-CT in the differentiation of radicular cysts (RCs), dentigerous cysts (DCs) and odontogenic keratocysts (OKCs).

METHODS

In total, 307 odontogenic cysts (RCs, DCs and OKCs) were included in this study. Cysts with lesion diameter <10 mm, cysts with artefacts affecting measurement of HU values, cysts involving infection and recurrent cysts were regarded as exclusion criteria. Images were acquired in three different types of CT scanners: Aquilion ONE, Discovery CT750 HD and SOMATOM Definition Flash. Differences in HU values among scanners and among types of odontogenic cysts were assessed using one-way analysis of variance; multiple comparisons were performed post hoc, using the Tukey-Kramer honestly significant difference test.

RESULTS

In total, 164 cysts were analysed in this study (64 RCs, 57 DCs and 43 OKCs). Regardless of the type of lesion, the Aquilion ONE scanner demonstrated a significant difference in HU value, compared with the Discovery CT750 HD scanner. Regardless of CT scanner model, HU values significantly differed between DCs and OKCs (p < 0.0001), as well as between OKCs and RCs (p < 0.0001).

CONCLUSIONS

HU values were found to vary among CT scanners and should always be associated with other lesion imaging features while interpreting and elaboration diagnostic hypothesis. Notably, the results suggested that OKCs might be able to be differentiated from DCs and RCs by using HU values.

Creation of an anthropomorphic CT head phantom for verification of image segmentation

Purpose

Many methods are available to segment structural magnetic resonance (MR) images of the brain into different tissue types. These have generally been developed for research purposes but there is some clinical use in the diagnosis of neurodegenerative diseases such as dementia. The potential exists for computed tomography (CT) segmentation to be used in place of MRI segmentation, but this will require a method to verify the accuracy of CT processing, particularly if algorithms developed for MR are used, as MR has notably greater tissue contrast.

Methods

To investigate these issues we have created a three‐dimensional (3D) printed brain with realistic Hounsfield unit (HU) values based on tissue maps segmented directly from an individual T1 MRI scan of a normal subject. Several T1 MRI scans of normal subjects from the ADNI database were segmented using SPM12 and used to create stereolithography files of different tissues for 3D printing. The attenuation properties of several material blends were investigated, and three suitable formulations were used to print an object expected to have realistic geometry and attenuation properties. A skull was simulated by coating the object with plaster of Paris impregnated bandages. Using two CT scanners, the realism of the phantom was assessed by the measurement of HU values, SPM12 segmentation and comparison with the source data used to create the phantom.

Results

Realistic relative HU values were measured although a subtraction of 60 was required to obtain equivalence with the expected values (gray matter 32.9–35.8 phantom, 29.9–34.2 literature). Segmentation of images acquired at different kVps/mAs showed excellent agreement with the source data (Dice Similarity Coefficient 0.79 for gray matter). The performance of two scanners with two segmentation methods was compared, with the scanners found to have similar performance and with one segmentation method clearly superior to the other.

Conclusion

The ability to use 3D printing to create a realistic (in terms of geometry and attenuation properties) head phantom has been demonstrated and used in an initial assessment of CT segmentation accuracy using freely available software developed for MRI.

Timing of brain computed tomography and accuracy of outcome prediction after cardiac arrest

AIM

Gray-white-matter ratio (GWR) calculated from head CT is a radiologic index of tissue changes associated with hypoxic-ischemic encephalopathy after cardiac arrest (CA). Evidence from previous studies indicates high specificity for poor outcome prediction at GWR thresholds of 1.10-1.20. We aimed to determine the relationship between accuracy of neurologic prognostication by GWR and timing of CT.

METHODS

We included 195 patients admitted to the ICU following CA. GWR was calculated from CT radiologic densities in 16 regions of interest. Outcome was determined upon intensive care unit discharge using the cerebral performance category (CPC). Accuracy of outcome prediction of GWR was compared for 3 epochs (<6, 6-24, and >24 h after CA).

RESULTS

125 (64%) patients had poor (CPC4-5) and 70 (36%) good outcome (CPC1-3). Irrespective of timing, specificity for poor outcome prediction was 100% at a GWR threshold of 1.10. Among 50 patients with both early and late CT, GWR decreased significantly over time (p = 0.002) in patients with poor outcome, sensitivity for poor outcome prediction was 12% (7-20%) with early CTs (<6 h) and 48% (38-58%) for late CTs (>24 h). Across all patients, sensitivity of early and late CT was 17% (9-28%) and 39% (28-51%), respectively.

CONCLUSION

A GWR below 1.10 predicts poor outcome (CPC4-5) in patients after CA with high specificity irrespective of time of acquisition of CT. Because GWR decreases over time in patients with severe HIE, sensitivity for prediction of poor outcome is higher for late CTs (>24 h after CA) as compared to early CTs (<6 h after CA).

Grey-white matter ratio measured using early unenhanced brain computed tomography shows no correlation with neurological outcomes in patients undergoing targeted temperature management after cardiac arrest

AIM

This study evaluated whether the grey-white matter ratio (GWR) assessed via early brain computed tomography (CT) within 2 h after the return of spontaneous circulation (ROSC) following cardiac arrest is associated with poor neurological outcomes after 6 months in post-cardiac arrest patients treated with targeted temperature management (TTM).

METHODS

This study used data from the Korean Hypothermia Network prospective registry obtained from November 2015 to October 2017 to assess patients with out-of-hospital cardiac arrest (OHCA) who underwent brain CT within 2 h following the ROSC. The primary endpoint was the neurological outcome 6 months post-cardiac arrest (cerebral performance category; CPC). The GWR was measured using early brain CT images. The subgroup analysis examined the difference in GWRs obtained from early and repeated brain CT.

RESULTS

Five-hundred-twelve patients were enrolled. Good (CPC 1-2) and poor (CPC 3-5) neurological outcomes were observed in 162 (31.6%) and 350 (68.4%) patients, respectively. The multivariate logistic regression analysis revealed that the GWR measured using early brain CT was a statistically nonsignificant predictor of poor neurologic outcomes (p = 0.727). In patients with poor outcomes, the mean GWR obtained from early and repeated CT images were 1.171 ± 0.058 and 1.091 ± 0.133, respectively (p < 0.001); there was no statistically significant difference between the GWRs in patients with good outcomes.

CONCLUSION

The GWR assessed via early brain CT alone is not an independent factor predictive of poor neurologic outcomes but could be useful when used with repeated CT data.