Infantile Rosai-Dorfman Disease With Isolated Brain Lesions Disseminated to the Parenchyma and Intraventricular Ependyma, Alteration of Leukocytes as a Promotion Factor in Immune Defense, and New Proposals: A Case Report and Literature Review.

The patient is a one-year-old girl referred to the hospital for an enlarged head after a 1.5-month history of two falls, followed by polydipsia, polyuria, and slow movement and growth. Three subsequent magnetic resonance imaging (MRI) examinations of the brain revealed nodular lesions disseminated in the brain parenchyma and intraventricular ependyma, resulting in obstructive hydrocephalus. Thoracic and abdominopelvic sonography showed no additional lesions. The preliminary diagnosis was a primary or metastatic neoplasm or infection. A biopsy of a lesion in the right frontal lobe was taken. The histological examination revealed features of Rosai-Dorfman disease (RDD), consisting of limited perivascular lymphoplasma cell infiltration with intervening sheets of proliferated histiocytes, with some of the histiocytes showing endocytosis of a single intact lymphocyte (emperipolesis).

Neuroradiology Applications of Dual and Multi-energy Computed Tomography.

Computed tomography (CT) imaging has become an essential diagnostic tool for most emergent clinical conditions, owing to its speed, accuracy, cost, and few contraindications, compared with MR imaging cross-sectional imaging. Spectral CT, which includes dual, multienergy, and photon-counting CT, is superior to conventional single-energy CT (SECT) in many respects. Spectral information enables differentiation between materials with similar Hounsfield Unit attenuations on SECT; examples include but are not limited to "virtual noncontrast," "virtual noncalcium," and most notably for neuro applications, "hemorrhage versus iodine." This article expands on the many possible benefits of spectral CT in neuroimaging.

Incorporating algorithmic uncertainty into a clinical machine deep learning algorithm for urgent head CTs.

Machine learning (ML) algorithms to detect critical findings on head CTs may expedite patient management. Most ML algorithms for diagnostic imaging analysis utilize dichotomous classifications to determine whether a specific abnormality is present. However, imaging findings may be indeterminate, and algorithmic inferences may have substantial uncertainty. We incorporated awareness of uncertainty into an ML algorithm that detects intracranial hemorrhage or other urgent intracranial abnormalities and evaluated prospectively identified, 1000 consecutive noncontrast head CTs assigned to Emergency Department Neuroradiology for interpretation. The algorithm classified the scans into high (IC+) and low (IC-) probabilities for intracranial hemorrhage or other urgent abnormalities. All other cases were designated as No Prediction (NP) by the algorithm. The positive predictive value for IC+ cases (N = 103) was 0.91 (CI: 0.84-0.96), and the negative predictive value for IC- cases (N = 729) was 0.94 (0.91-0.96). Admission, neurosurgical intervention, and 30-day mortality rates for IC+ was 75% (63-84), 35% (24-47), and 10% (4-20), compared to 43% (40-47), 4% (3-6), and 3% (2-5) for IC-. There were 168 NP cases, of which 32% had intracranial hemorrhage or other urgent abnormalities, 31% had artifacts and postoperative changes, and 29% had no abnormalities. An ML algorithm incorporating uncertainty classified most head CTs into clinically relevant groups with high predictive values and may help accelerate the management of patients with intracranial hemorrhage or other urgent intracranial abnormalities.

Lesion Age Imaging in Acute Stroke: Water Uptake in CT Versus DWI-FLAIR Mismatch.

PURPOSE: In acute ischemic stroke with unknown time of onset, magnetic resonance (MR)-based diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) estimates lesion age to guide intravenous thrombolysis. Computed tomography (CT)-based quantitative net water uptake (NWU) may be a potential alternative. The purpose of this study was to directly compare CT-based NWU to magnetic resonance imaging (MRI) at identifying patients with lesion age < 4.5 hours from symptom onset. METHODS: Fifty patients with acute anterior circulation stroke were analyzed with both imaging modalities at admission between 0.5 and 8.0 hours after known symptom onset. DWI-FLAIR lesion mismatch was rated and NWU was measured in admission CT. An established NWU threshold (11.5%) was used to classify patients within and beyond 4.5 hours. Multiparametric MRI signal was compared with NWU using logistic regression analyses. The empirical distribution of NWU was analyzed in a consecutive cohort of patients with wake-up stroke. RESULTS: The median time between CT and MRI was 35 minutes (interquartile range [IQR] = 24-50). The accuracy of DWI-FLAIR mismatch was 68.8% (95% confidence interval [CI] = 53.7-81.3%) with a sensitivity of 58% and specificity of 82%. The accuracy of NWU threshold was 86.0% (95% CI = 73.3-94.2%) with a sensitivity of 91% and specificity of 78%. The area under the curve (AUC) of multiparametric MRI signal to classify lesion age <4.5 hours was 0.86 (95% CI = 0.64-0.97), and the AUC of quantitative NWU was 0.91 (95% CI = 0.78-0.98). Among 87 patients with wake-up stroke, 46 patients (53%) showed low NWU (< 11.5%). CONCLUSION: The predictive power of CT-based lesion water imaging to identify patients within the time window of thrombolysis was comparable to multiparametric DWI-FLAIR MRI. A significant proportion of patients with wake-up stroke exhibit low NWU and may therefore be potentially suitable for thrombolysis. ANN NEUROL 2020;88:1144-1152.

Nontraumatic Head and Neck Emergencies.

Head and neck imaging is an intimidating subject for many radiologists because of the complex anatomy and potentially serious consequences of delayed or improper diagnosis of the diverse abnormalities involving this region. The purpose of this article is to help radiologists to understand the intricate anatomy of the head and neck and to review the imaging appearances of a variety of nontraumatic head and neck conditions that bring patients to the emergency department, including acute infectious and inflammatory diseases and acute complications of head and neck neoplasms. These conditions are presented in five sections on the basis of their primary location of involvement: the oral cavity and pharynx, neck, sinonasal tract, orbits, and ears. Important anatomic landmarks are reviewed briefly in each related section.Online supplemental material is available for this article.©RSNA, 2019.

Stroke Imaging.

Stroke is the clinical syndrome of acute onset of neurologic deficit caused by ischemia or hemorrhage. Neuroimaging has a crucial role in differentiating ischemic from hemorrhagic stroke. Advanced neuroimaging has become essential in the management of patients with acute ischemic stroke mainly because of improved awareness of the imaging findings and their role in patient selection for novel treatment options as highlighted in recent clinical trials, including "late window" (8-24 hours post ictus!) intra-arterial thrombectomy. This article focuses on the role of neuroimaging in the management of patients with acute ischemic stroke.

An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasets.

Owing to improvements in image recognition via deep learning, machine-learning algorithms could eventually be applied to automated medical diagnoses that can guide clinical decision-making. However, these algorithms remain a 'black box' in terms of how they generate the predictions from the input data. Also, high-performance deep learning requires large, high-quality training datasets. Here, we report the development of an understandable deep-learning system that detects acute intracranial haemorrhage (ICH) and classifies five ICH subtypes from unenhanced head computed-tomography scans. By using a dataset of only 904 cases for algorithm training, the system achieved a performance similar to that of expert radiologists in two independent test datasets containing 200 cases (sensitivity of 98% and specificity of 95%) and 196 cases (sensitivity of 92% and specificity of 95%). The system includes an attention map and a prediction basis retrieved from training data to enhance explainability, and an iterative process that mimics the workflow of radiologists. Our approach to algorithm development can facilitate the development of deep-learning systems for a variety of clinical applications and accelerate their adoption into clinical practice.

The Adult Patient with Acute Neurologic Deficit: An Update on Imaging Trends.

Stroke is the clinical syndrome of abrupt onset of acute neurologic deficit owing to decreased oxygen delivery to the brain, resulting in ischemia or infarction. Approximately 87% of strokes are ischemic and 13% are hemorrhagic. Improved awareness of the neuroimaging findings highlighted in recent stroke clinical trials, as well as of their role in patient selection for novel treatment options-including "late window" (8-24 hours post-ictus!) intraarterial thrombectomy-has become increasingly important. This article focuses on the role of neuroimaging in the assessment and management of patients with acute ischemic stroke.

Dual-Energy Computed Tomography Angiography of the Head and Neck and Related Applications.

Dual-energy computed tomography (DECT) has become an increasingly widespread and useful component of the neuroimaging armamentarium, offering automated bone removal, metallic artifact reduction, and improved characterization of iodinated contrast enhancement. The application of these techniques to CT neuroangiography enables a number of benefits including more efficient 3D post-processing, contrast dose reduction opportunities, successful differentiation of hemorrhage from contrast staining following thromboembolic recanalization therapy, improved detection of active contrast extravasation in the setting of intracranial hemorrhage, and more precise characterization of atheromatous steno-occlusive disease.

Limited reliability of computed tomographic perfusion acute infarct volume measurements compared with diffusion-weighted imaging in anterior circulation stroke.

BACKGROUND AND PURPOSE: Diffusion-weighted imaging (DWI) can reliably identify critically ischemic tissue shortly after stroke onset. We tested whether thresholded computed tomographic cerebral blood flow (CT-CBF) and CT-cerebral blood volume (CT-CBV) maps are sufficiently accurate to substitute for DWI for estimating the critically ischemic tissue volume. METHODS: Ischemic volumes of 55 patients with acute anterior circulation stroke were assessed on DWI by visual segmentation and on CT-CBF and CT-CBV with segmentation using 15% and 30% thresholds, respectively. The contrast:noise ratios of ischemic regions on the DWI and CT perfusion (CTP) images were measured. Correlation and Bland-Altman analyses were used to assess the reliability of CTP. RESULTS: Mean contrast:noise ratios for DWI, CT-CBF, and CT-CBV were 4.3, 0.9, and 0.4, respectively. CTP and DWI lesion volumes were highly correlated (R(2)=0.87 for CT-CBF; R(2)=0.83 for CT-CBV; P<0.001). Bland-Altman analyses revealed little systemic bias (-2.6 mL) but high measurement variability (95% confidence interval, ±56.7 mL) between mean CT-CBF and DWI lesion volumes, and systemic bias (-26 mL) and high measurement variability (95% confidence interval, ±64.0 mL) between mean CT-CBV and DWI lesion volumes. A simulated treatment study demonstrated that using CTP-CBF instead of DWI for detecting a statistically significant effect would require at least twice as many patients. CONCLUSIONS: The poor contrast:noise ratios of CT-CBV and CT-CBF compared with those of DWI result in large measurement error, making it problematic to substitute CTP for DWI in selecting individual acute stroke patients for treatment. CTP could be used for treatment studies of patient groups, but the number of patients needed to identify a significant effect is much higher than the number needed if DWI is used.

Admission insular infarction >25% is the strongest predictor of large mismatch loss in proximal middle cerebral artery stroke.

BACKGROUND AND PURPOSE: Previous univariate analyses have suggested that proximal middle cerebral artery infarcts with insular involvement have greater severity and are more likely to progress into surrounding penumbral tissue at risk. We hypothesized that a practical, simple scoring method to assess percent insular ribbon infarction (PIRI score) would improve prediction of penumbral loss over other common imaging biomarkers. METHODS: Of consecutive acute stroke patients from 2003 to 2008, 45 with proximal middle cerebral artery-only occlusion met inclusion criteria, including available penumbral imaging. Infarct (diffusion-weighted imaging), tissue at risk (magnetic resonance mean transit time), and final infarct volume (magnetic resonance/computed tomography) were manually segmented. Diffusion-weighted imaging images were rated according to the 5-point PIRI score (0, normal; 1, <25%; 2, 25%-49%; 3, 50%-74%; 4, ≥75% insula involvement). Percent mismatch loss was calculated as an outcome measure of infarct progression. Receiver operating characteristic curve and multivariate analyses were performed. RESULTS: Mean admission diffusion-weighted imaging infarct volume was 30.9 (±38.8) mL and median (interquartile range) PIRI score was 3 (0.75-4). PIRI score was significantly correlated with percent mismatch loss (P<0.0001). When percent mismatch loss was dichotomized based on its median value (30.0%), receiver operating characteristic curve area under curve was 0.89 (P=0.0001) with a 25% insula infarction optimal threshold. After adjusting for time to imaging and treatment, binary logistic regression, including dichotomized PIRI (25% threshold), age, National Institutes of Health Stroke Scale score, diffusion-weighted imaging infarct volume, and computed tomography angiography collateral score as covariates, revealed that only dichotomized insula score (P=0.03) and age (P=0.02) were independent predictors of large (68.2%) versus small (8.1%) mismatch loss. There was excellent interobserver agreement for dichotomized PIRI scoring (κ=0.91). CONCLUSIONS: Admission insular infarction >25% is the strongest predictor of large mismatch loss in this cohort of proximal middle cerebral artery occlusive stroke. This outcome marker may help to identify treatment-eligible patients who are in greatest need of rapid reperfusion therapy.

Role of cardiac and extracranial vascular CT in the evaluation/management of cerebral ischemia and stroke.

Collectively, cardiac and large artery sources are responsible for the largest proportion of acute ischemic stroke. Technological advancements in computed tomography (CT) continue to improve evaluation of these patients. The literature was reviewed for the potential role and impact of these innovations in evaluation and management of these patients. In conclusion, incorporation of early cardiac and extracranial vascular CT angiography (CTA) in evaluation of patients with acute ischemic stroke may potentially improve patient management and outcome, while decreasing cost.

Radiology-pathology conference: primary adrenal lymphoma.

We present a case of a 62-year-old man with a history of type II diabetes mellitus who presented to our emergency department with back pain and right upper quadrant abdominal pain associated with vomiting and weight loss. A computed tomographic scan of the abdomen and pelvis demonstrated a large adrenal mass, and subsequent biopsy showed primary adrenal lymphoma.

CT perfusion mean transit time maps optimally distinguish benign oligemia from true "at-risk" ischemic penumbra, but thresholds vary by postprocessing technique.

BACKGROUND AND PURPOSE: Various CTP parameters have been used to identify ischemic penumbra. The purpose of this study was to determine the optimal CTP parameter and threshold to distinguish true "at-risk" penumbra from benign oligemia in acute stroke patients without reperfusion. MATERIALS AND METHODS: Consecutive stroke patients were screened and 23 met the following criteria: 1) admission scanning within 9 hours of onset, 2) CTA confirmation of large vessel occlusion, 3) no late clinical or radiographic evidence of reperfusion, 4) no thrombolytic therapy, 5) DWI imaging within 3 hours of CTP, and 6) either CT or MR follow-up imaging. CTP was postprocessed with commercial software packages, using standard and delay-corrected deconvolution algorithms. Relative cerebral blood flow, volume, and mean transit time (rCBF, rCBV and rMTT) values were obtained by normalization to the uninvolved hemisphere. The admission DWI and final infarct were transposed onto the CTP maps and receiver operating characteristic curve analysis was performed to determine optimal thresholds for each perfusion parameter in defining penumbra destined to infarct. RESULTS: Relative and absolute MTT identified penumbra destined to infarct more accurately than CBF or CBV*CBF (P < .01). Absolute and relative MTT thresholds for defining penumbra were 12s and 249% for the standard and 13.5s and 150% for the delay-corrected algorithms, respectively. CONCLUSIONS: Appropriately thresholded absolute and relative MTT-CTP maps optimally distinguish "at-risk" penumbra from benign oligemia in acute stroke patients with large-vessel occlusion and no reperfusion. The precise threshold values may vary, however, depending on the postprocessing technique used for CTP map construction.

Cranial CT with adaptive statistical iterative reconstruction: improved image quality with concomitant radiation dose reduction.

BACKGROUND AND PURPOSE: To safeguard patient health, there is great interest in CT radiation-dose reduction. The purpose of this study was to evaluate the impact of an iterative-reconstruction algorithm, ASIR, on image-quality measures in reduced-dose head CT scans for adult patients. MATERIALS AND METHODS: Using a 64-section scanner, we analyzed 100 reduced-dose adult head CT scans at 6 predefined levels of ASIR blended with FBP reconstruction. These scans were compared with 50 CT scans previously obtained at a higher routine dose without ASIR reconstruction. SNR and CNR were computed from Hounsfield unit measurements of normal GM and WM of brain parenchyma. A blinded qualitative analysis was performed in 10 lower-dose CT datasets compared with higher-dose ones without ASIR. Phantom data analysis was also performed. RESULTS: Lower-dose scans without ASIR had significantly lower mean GM and WM SNR (P = .003) and similar GM-WM CNR values compared with higher routine-dose scans. However, at ASIR levels of 20%-40%, there was no statistically significant difference in SNR, and at ASIR levels of ≥60%, the SNR values of the reduced-dose scans were significantly higher (P < .01). CNR values were also significantly higher at ASIR levels of ≥40% (P < .01). Blinded qualitative review demonstrated significant improvements in perceived image noise, artifacts, and GM-WM differentiation at ASIR levels ≥60% (P < .01). CONCLUSIONS: These results demonstrate that the use of ASIR in adult head CT scans reduces image noise and increases low-contrast resolution, while allowing lower radiation doses without affecting spatial resolution.

CT cerebral blood flow maps optimally correlate with admission diffusion-weighted imaging in acute stroke but thresholds vary by postprocessing platform.

BACKGROUND AND PURPOSE: Admission infarct core lesion size is an important determinant of management and outcome in acute (<9 hours) stroke. Our purposes were to: (1) determine the optimal CT perfusion parameter to define infarct core using various postprocessing platforms; and (2) establish the degree of variability in threshold values between these different platforms. METHODS: We evaluated 48 consecutive cases with vessel occlusion and admission CT perfusion and diffusion-weighted imaging within 3 hours of each other. CT perfusion was acquired with a "second-generation" 66-second biphasic cine protocol and postprocessed using "standard" (from 2 vendors, "A-std" and "B-std") and "delay-corrected" (from 1 vendor, "A-dc") commercial software. Receiver operating characteristic curve analysis was performed comparing each CT perfusion parameter-both absolute and normalized to the contralateral uninvolved hemisphere-between infarcted and noninfarcted regions as defined by coregistered diffusion-weighted imaging. RESULTS: Cerebral blood flow had the highest accuracy (receiver operating characteristic area under the curve) for all 3 platforms (P<0.01). The maximal areas under the curve for each parameter were: absolute cerebral blood flow 0.88, cerebral blood volume 0.81, and mean transit time 0.82 and relative Cerebral blood flow 0.88, cerebral blood volume 0.83, and mean transit time 0.82. Optimal receiver operating characteristic operating point thresholds varied significantly between different platforms (Friedman test, P<0.01). CONCLUSIONS: Admission absolute and normalized "second-generation" cine acquired CT cerebral blood flow lesion volumes correlate more closely with diffusion-weighted imaging-defined infarct core than do those of CT cerebral blood volume or mean transit time. Although limited availability of diffusion-weighted imaging for some patients creates impetus to develop alternative methods of estimating core, the marked variability in quantification among different postprocessing software limits generalizability of parameter map thresholds between platforms.

Combining acute diffusion-weighted imaging and mean transmit time lesion volumes with National Institutes of Health Stroke Scale Score improves the prediction of acute stroke outcome.

BACKGROUND AND PURPOSE: The purpose of this study was to determine whether acute diffusion-weighted imaging (DWI) and mean transit time (MTT) lesion volumes and presenting National Institutes of Health Stroke Scale (NIHSS) can identify patients with acute ischemic stroke who will have a high probability of good and poor outcomes. METHODS: Fifty-four patients with acute ischemic stroke who had MRI within 9 hours of symptom onset and 3-month follow-up with modified Rankin scale were evaluated. Acute DWI and MTT lesion volumes and baseline NIHSS scores were calculated. Clinical outcomes were considered good if the modified Rankin Scale was 0 to 2. RESULTS: The 33 of 54 (61%) patients with good outcomes had significantly smaller DWI lesion volumes (P=0.0001), smaller MTT lesion volumes (P<0.0001), and lower NIHSS scores (P<0.0001) compared with those with poor outcomes. Receiver operating characteristic curves for DWI, MTT, and NIHSS relative to poor outcome had areas under the curve of 0.889, 0.854, and 0.930, respectively, which were not significantly different. DWI and MTT lesion volumes predicted outcome better than mismatch volume or percentage mismatch. All patients with a DWI volume >72 mL (13 of 54) and an NIHSS score >20 (6 of 54) had poor outcomes. All patients with an MTT volume of <47 mL (16 of 54) and an NIHSS score <8 (17 of 54) had good outcomes. Combining clinical and imaging thresholds improved prognostic yield (70%) over clinical (43%) or imaging (54%) thresholds alone (P=0.01). CONCLUSIONS: Combining quantitative DWI and MTT with NIHSS predicts good and poor outcomes with high probability and is superior to NIHSS alone.

Arterial input function placement for accurate CT perfusion map construction in acute stroke.

OBJECTIVE: The objective of our study was to evaluate the effect of varying arterial input function (AIF) placement on the qualitative and quantitative CT perfusion parameters. MATERIALS AND METHODS: Retrospective analysis of CT perfusion data was performed on 14 acute stroke patients with a proximal middle cerebral artery (MCA) clot. Cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) maps were constructed using a systematic method by varying only the AIF placement in four positions relative to the MCA clot including proximal and distal to the clot in the ipsilateral and contralateral hemispheres. Two postprocessing software programs were used to evaluate the effect of AIF placement on perfusion parameters using a delay-insensitive deconvolution method compared with a standard deconvolution method. RESULTS: One hundred sixty-eight CT perfusion maps were constructed for each software package. Both software programs generated a mean CBF at the infarct core of < 12 mL/100 g/min and a mean CBV of < 2 mL/100 g for AIF placement proximal to the clot in the ipsilateral hemisphere and proximal and distal to the clot in the contralateral hemisphere. For AIF placement distal to the clot in the ipsilateral hemisphere, the mean CBF significantly increased to 17.3 mL/100 g/min with delay-insensitive software and to 19.4 mL/100 g/min with standard software (p < 0.05). The mean MTT was significantly decreased for this AIF position. Furthermore, this AIF position yielded qualitatively different parametric maps, being most pronounced with MTT and CBF. Overall, CBV was least affected by AIF location. CONCLUSION: For postprocessing of accurate quantitative CT perfusion maps, laterality of the AIF location is less important than avoiding AIF placement distal to the clot as detected on CT angiography. This pitfall is less severe with deconvolution-based software programs using a delay-insensitive technique than with those using a standard deconvolution method.