Accuracy of Non-Enhanced CT in Detecting Early Ischemic Edema Using Frequency Selective Non-Linear Blending

Improved Visualization and Quantification of Net Water Uptake in Recent Small Subcortical Infarcts in the Thalamus Using Computed Tomography

Diagnosing recent small subcortical infarcts (RSSIs) via early computed tomography (CT) remains challenging. This study aimed to assess CT attenuation values (Hounsfield Units (HU)) and net water uptake (NWU) in RSSI and explore a postprocessing algorithm's potential to enhance thalamic RSSI detection. We examined non-contrast CT (NCCT) data from patients with confirmed thalamic RSSI on diffusion-weighted magnetic resonance imaging (DW-MRI) between January 2010 and October 2017. Co-registered DW-MRI and NCCT images enabled HU and NWU quantification in the infarct area compared to unaffected contralateral tissue. Results were categorized based on symptom onset to NCCT timing. Postprocessing using window optimization and frequency-selective non-linear blending (FSNLB) was applied, with interpretations by three blinded Neuroradiologists. The study included 34 patients (median age 70 years [IQR 63-76], 14 women). RSSI exhibited significantly reduced mean CT attenuation compared to unaffected thalamus (29.6 HU (±3.1) vs. 33.3 HU (±2.6); p < 0.01). Mean NWU in the infarct area increased from 6.4% (±7.2) at 0-6 h to 16.6% (±8.7) at 24-36 h post-symptom onset. Postprocessed NCCT using these HU values improved sensitivity for RSSI detection from 32% in unprocessed CT to 41% in FSNLB-optimized CT, with specificities ranging from 86% to 95%. In conclusion, CT attenuation values and NWU are discernible in thalamic RSSI up to 36 h post-symptom onset. Postprocessing techniques, particularly window optimization and FSNLB, moderately enhance RSSI detection.

Imaging of Bowel Ischemia: An Update, From the AJR Special Series on Emergency Radiology

Acute mesenteric ischemia is a life-threatening condition that results from abrupt reduction in or cessation of blood flow to the bowel. Characterized by nonspecific abdominal symptoms, mesenteric ischemia is infrequently encountered and commonly misdiagnosed, with potentially catastrophic consequences. Prompt clinical diagnosis and early implementation of therapeutic interventions are critical to improving patient outcomes. Because cross-sectional imaging plays a key role in the diagnosis of mesenteric ischemia, radiologists must be familiar with the varied imaging manifestations of intestinal ischemia. Thus, the objectives of this article are to review the various types and common causes of mesenteric ischemia and to describe its spectrum of multimodality imaging findings, with special attention to novel imaging techniques and emerging diagnoses.

Model-Based Iterative Reconstruction (MBIR) for ASPECT Scoring in Acute Stroke Patients Selection: Comparison to rCBV and Follow-Up Imaging

BACKGROUND

To compare a model-based iterative reconstruction (MBIR) versus a hybrid iterative reconstruction (HIR) for initial and final Alberta Stroke Program Early Ct Score (ASPECT) scoring in acute ischemic stroke (AIS). We hypothesized that MBIR designed for brain computed tomography (CT) could perform better than HIR for ASPECT scoring.

METHODS

Among patients who had undergone CT perfusion for AIS between April 2018 and October 2019 with a follow-up imaging within 7 days, we designed a cohort of representative ASPECTS. Two readers assessed regional-cerebral-blood-volume-ASPECT (rCBV-ASPECTS) on the initial exam and final-ASPECTS on the follow-up non-contrast-CT (NCCT) in consensus. Four readers performed independently MBIR and HIR ASPECT scoring on baseline NCCT.

RESULTS

In total, 294 hemispheres from 147 participants (average age of 69.59 ± 15.63 SD) were analyzed. Overall raters' agreement between rCBV-map and MBIR and HIR ranged from moderate to moderate (κ = 0.54 to κ = 0.57) with HIR and moderate to substantial (κ = 0.52 to κ = 0.74) with MBIR. Overall raters' agreement between follow-up imaging and HIR/MBIR ranged from moderate to moderate (κ = 0.55 to κ = 0.59) with HIR and moderate to almost perfect (κ = 0.48 to κ = 0.82) with MBIR.

CONCLUSIONS

ASPECT scoring with MBIR more closely matched with initial and final infarct extent than classical HIR NCCT reconstruction.

Interindividual Comparison of Frequency-Selective Nonlinear Blending to Conventional CT for Detection of Focal Liver Lesions Using MRI as the Reference Standard

Background: Diagnosing liver lesions is challenging. CT is used for primary diagnosis; however, its contrast resolution is limited. Investigating methods for better detection of liver lesions is important. Objective: To evaluate the effect of frequency-selective nonlinear blending (NLB) on the detectability of liver lesions on CT. Methods: Retrospective search yielded 109 patients with malignant and benign liver lesions (n = 356; 191 principally diagnosed, 165 incidental findings) underwent contrast-enhanced CT (CECT) in portal venous phase and liver MRI between January 2012 and December 2017. Nonlinear blending (NLB) was applied to CECTs, and three readers rated image quality (5-point Likert scale) in blinded, independent, and randomized fashion. Focal lesions (n = 356) were evaluated for lesion identification and categorization to assess sensitivity. For 191 lesions (primary diagnosis) two readers evaluated CECT and NLB CT to compare size and subjective measurement accuracy. A fourth reader conducted ROI measurements for calculation of contrast-to-noise ratio (CNR), and a fifth reader reviewed MRI as standard of reference. Statistics included interobserver agreement, quantitative comparisons of CNR, lesion size, and subjective image analyses of image quality and sensitivity of detecting liver lesions. Results: Three readers rated image quality of NLB CT higher than for CECT (NLB CT, 4 [10% and 90% percentile: 4, 5]; CECT, 2 [1, 3]; p < .001). CECT showed good interreader agreement (interclass coefficient [ICC], 0.81 [95% CI, 0.76¬-0.85]); NLB CT also (ICC, 0.75 [95% CI, 0.69-0.79]). Mean CNR of liver lesions was increased using NLB (CECT, 4.18 [range, 1.67-9.06]; NLB CT, 12.49 [range, 6.18-23.39]; p < .001). Bland-Altman analysis of lesion size showed reduced underestimation from 2.5 mm (SD, 9.2 [95% CI, 1.2-3.9]) in CECT to 0.1 mm (SD, 3.9 [95% CI, -0.68 to 0.46) for NLB CT (concordance correlation coefficient, 0.99). Sensitivity for detecting liver lesions was increased to 86% for NLB CT (CECT, 76%). Conclusion: Frequency-selective NLB of CECT allows increased image quality and CNR, more precise size measurement, and higher sensitivity for detecting liver lesions. Clinical Impact: NLB CT improves liver lesion detection and increases the accuracy of lesion size measurement, which is important when considering local ablation or liver transplant.

Detecting brain lesions in suspected acute ischemic stroke with CT-based synthetic MRI using generative adversarial networks

Background

Difficulties in detecting brain lesions in acute ischemic stroke (AIS) have convinced researchers to use computed tomography (CT) to scan for and magnetic resonance imaging (MRI) to search for these lesions. This work aimed to develop a generative adversarial network (GAN) model for CT-to-MR image synthesis and evaluate reader performance with synthetic MRI (syn-MRI) in detecting brain lesions in suspected patients.

Methods

Patients with primarily suspected AIS were randomly assigned to the training (n=140) or testing (n=53) set. Emergency CT and follow-up MR images in the training set were used to develop a GAN model to generate syn-MR images from the CT data in the testing set. The standard reference was the manual segmentations of follow-up MR images. Image similarity was evaluated between syn-MRI and the ground truth using a 4-grade visual rating scale, the peak signal-to-noise ratio (PSNR), and the structural similarity index measure (SSIM). Reader performance with syn-MRI and CT was evaluated and compared on a per-patient (patient detection) and per-lesion (lesion detection) basis. Paired t-tests or Wilcoxon signed-rank tests were used to compare reader performance in lesion detection between the syn-MRI and CT data.

Results

Grade 2–4 brain lesions were observed on syn-MRI in 92.5% (49/53) of the patients, while the remaining syn-MRI data showed no lesions compared to the ground truth. The GAN model exhibited a weak PSNR of 24.30 dB but a favorable SSIM of 0.857. Compared with CT, syn-MRI led to an increase in the overall sensitivity from 38% (57/150) to 82% (123/150) in patient detection and from 4% (68/1,620) to 16% (262/1,620) in lesion detection (R=0.32, corrected P<0.001), but the specificity in patient detection decreased from 67% (6/9) to 33% (3/9). An additional 75% (70/93) of patients and 15% (77/517) of lesions missed on CT were detected on syn-MRI.

Conclusions

The GAN model holds potential for generating synthetic MR images from noncontrast CT data and thus could help sensitively detect individuals among patients with suspected AIS. However, the image similarity performance of the model needs to be improved, and further expert discrimination is strongly recommended.

Accuracy of thin-slice model-based iterative reconstruction designed for brain CT to diagnose acute ischemic stroke in the middle cerebral artery territory: a multicenter study

PURPOSE

Model-based iterative reconstruction (MBIR) yields higher spatial resolution and a lower image noise than conventional reconstruction methods. We hypothesized that thin-slice MBIR designed for brain CT could improve the detectability of acute ischemic stroke in the middle cerebral artery (MCA) territory.

METHODS

Included were 41 patients with acute ischemic stroke in the MCA territory; they were seen at 4 medical centers. The controls were 39 subjects without acute stroke. Images were reconstructed with hybrid IR and with MBIR designed for brain CT at slice thickness of 2 mm. We measured the image noise in the ventricle and compared the contrast-to-noise ratio (CNR) in the ischemic lesion. We analyzed the ability of reconstructed images to detect ischemic lesions using receiver operating characteristics (ROC) analysis; 8 observers read the routine clinical hybrid IR with 5 mm-thick images, while referring to 2 mm-thick hybrid IR images or MBIR images.

RESULTS

The image noise was significantly lower on MBIR- than hybrid IR images (1.2 vs. 3.4, p < 0.001). The CNR was significantly higher with MBIR than hybrid IR (6.3 vs. 1.6, p < 0.001). The mean area under the ROC curve was also significantly higher on hybrid IR plus MBIR than hybrid IR (0.55 vs. 0.48, p < 0.036). Sensitivity, specificity, and accuracy were 41.2%, 88.8%, and 65.7%, respectively, for hybrid IR; they were 58.8%, 86.1%, and 72.9%, respectively, for hybrid IR plus MBIR.

CONCLUSION

The additional thin-slice MBIR designed for brain CT may improve the detection of acute MCA stroke.

Minute changes of cerebral parenchymal non-contrast computed tomography attenuation reflect cerebral volume alterations of blood

AIMS

Non-infarcted acute cerebral ischaemic areas appear hypo-attenuated on non-contrast narrow-window computed tomography images. We aimed to determine the mechanism underlying minute computed tomography hypo-attenuation and visualise these attenuation changes on non-contrast computed tomography images.

METHODS

The cerebral parenchyma was defined by pixels with attenuation of 20-50 Hounsfield units. We calculated the mean cerebral parenchymal attenuation in non-contrast computed tomography images. We analysed the correlation of complete blood counts with corresponding mean cerebral parenchymal attenuation values using linear regression analysis. Moreover, we developed an image processing method that involved pixel colorisation based on the noise-reduced attenuation value for minute cerebral parenchymal attenuation visualisation.

RESULTS

Haemoglobin, haematocrit and red blood cell counts positively correlated with mean cerebral parenchymal attenuation values. The cerebral haematocrit is correlated with the blood haematocrit; therefore, cerebral parenchymal attenuation correlated linearly with cerebral haemoglobin concentration. Haemoglobin contents in a pixel partially determine the X-ray absorption dose and attenuation value. Pixel haemoglobin contents are determined by the cerebral volume of blood in a pixel. Image processed computed tomography images reflected cerebral volume of blood and showed the same alterations with regional cerebral blood volume maps of perfusion computed tomography.

CONCLUSIONS

Cerebral parenchymal attenuation correlated with cerebral haemoglobin concentration and cerebral volume of blood. Infarcted cerebral parenchyma shows about 5 Hounsfield units gray matter attenuation decrease. Attenuation decrease by less than 5 Hounsfield units means decreased cerebral volume of blood, indicating a reversible functional change. One cannot recognise minute hypo-attenuation (<5 Hounsfield units) in routine computed tomography images. However, it can be visualised through an image processing method on non-contrast computed tomography images. It may detect pre-infarction cerebral volume of blood and regional cerebral blood volume alterations.

Mesenteric ischemia: what the radiologist needs to know

Acute mesenteric ischemia (AMI) is a life-threatening condition that often presents with abdominal pain. Early diagnosis with contrast-enhanced computed tomography and revascularization can reduce the overall mortality in AMI. This article reviews practical etiological classification, pathophysiology of imaging manifestations and common pitfalls in intestinal ischemia.

Variability of optic nerve sheath diameter in acute ischemic stroke

Background:

Stroke is the third leading cause of death and the first cause of disability in the world. It holds an important place in hospital admissions and health expenses in the industrialized world.

Objective:

The aim of the study was to evaluate the relationship between optic nerve sheath diameter and the findings of brain computerized tomography scans and brain diffusion-weighted imaging and investigate the variability of optic nerve sheath diameter measured by ultrasonography in acute ischemic stroke.

Methods:

Patients who had acute ischemic stroke were included in Group A. Healthy adults were included in Group B as the control group. In addition, according to computerized tomography scans and diffusion-weighted imaging findings, Group A was divided into three subgroups. Patients with normal computerized tomography and diffusion-weighted imaging were included in Group 1, patients with normal computerized tomography and ischemic area on diffusion-weighted imaging were included in Group 2, and patients with ischemic area on computerized tomography and diffusion-weighted imaging were included in Group 3.

Results:

A total of 100 patients were included in Group A and 100 healthy adults included in Group B. The optic nerve sheath diameter values of Groups A and B were 5.4 ± 0.6 and 4.2 ± 0.4 mm (p < 0.001), respectively. The optic nerve sheath diameter cutoff value for detection of acute ischemic stroke was determined as 4.7 mm. The sensitivity and specificity at this cutoff value were determined as 89% and 90%, respectively. According to computerized tomography scans and diffusion-weighted imaging findings, there were 18 patients in Group 1, 56 patients in Group 2, and 26 patients in Group 3. Time from onset of symptoms to presentation to emergency department was shortest in Group 1 (3.0 ± 1.8 h). The widest optic nerve sheath diameter was calculated in Group 3 (optic nerve sheath diameter: 5.7 ± 0.6 mm).

Conclusion:

This study demonstrates that the optic nerve sheath diameter increases in acute ischemic stroke and it increases earlier than computerized tomography and diffusion-weighted imaging alteration occur. Therefore, optic nerve sheath diameter can be applied to assist the diagnosis of acute ischemic stroke with other imaging techniques with equivocal/negative results and determination of appropriate treatment, especially in cases with normal computerized tomography scan and diffusion-weighted imaging.

Using Correlative Properties of Neighboring Pixels to Enhance Contrast-to-Noise Ratio of Abnormal Hippocampus in Patients With Intractable Epilepsy and Mesial Temporal Sclerosis

RATIONALE AND OBJECTIVES

To test whether an image-processing algorithm can aid in visualization of mesial temporal sclerosis on magnetic resonance imaging by selectively increasing contrast-to-noise ratio (CNR) between abnormal hippocampus and normal brain.

MATERIALS AND METHODS

In this Institutional Review Board-approved and Health Insurance Portability and Accountability Act-compliant study, baseline coronal fluid-attenuated inversion recovery images of 18 adults (10 females, eight males; mean age 41.2 years) with proven mesial temporal sclerosis were processed using a custom algorithm to produce corresponding enhanced images. Average (Hmean) and maximum (Hmax) CNR for abnormal hippocampus were calculated relative to normal ipsilateral white matter. CNR values for normal gray matter (GM) were similarly calculated using ipsilateral cingulate gyrus as the internal control. To evaluate effect of image processing on visual conspicuity of hippocampal signal alteration, a neuroradiologist masked to the side of hippocampal abnormality rated signal intensity (SI) of hippocampi on baseline and enhanced images using a five-point scale (definitely abnormal to definitely normal). Differences in Hmean, Hmax, GM, and SI ratings for abnormal hippocampi on baseline and enhanced images were assessed for statistical significance.

RESULTS

Both Hmean and Hmax were significantly higher in enhanced images as compared to baseline images (p < 0.0001 for both). There was no significant difference in the GM between baseline and enhanced images (p = 0.9375). SI ratings showed a more confident identification of abnormality on enhanced images (p = 0.0001).

CONCLUSION

Image-processing resulted in increased CNR of abnormal hippocampus without affecting the CNR of normal gray matter. This selective increase in conspicuity of abnormal hippocampus was associated with more confident identification of hippocampal signal alteration.

Frequency-selective non-linear blending for the computed tomography diagnosis of acute gangrenous cholecystitis: Pilot retrospective evaluation

Purpose

To compare the diagnostic performance of frequency-selective non-linear blending and conventional linear blending contrast-enhanced CT for the diagnosis of acute (AC) and gangrenous (GC) cholecystitis.

Materials and methods

Following local ethics committee approval for retrospective data analysis, a database search derived 39 patients (26 men, mean age 67.8 ± 14.6 years) with clinical signs of acute cholecystitis, contrast enhanced CT (CECT) evaluation, cholecystectomy, and pathological examination of the resected specimen. The interval between CECT and surgery was 4.7 ± 4.1 days. Pathological gross examination was used to categorize the cases into AC and GC. Subsequently, two radiologists categorized the CECT studies in a blinded and independent fashion into AC and GC, during two different reading sessions using linear blending and frequency-selective non-linear blending CECT.

Results

Histologic analysis diagnosed 31/39 (79.4%) cases of GC and 8/39 (20.6%) cases of AC. Image interpretation of linear blending CECT resulted in classification of 7/39 (17.9%) patients as GC and 32/39 (82.1%) as AC, whereas image interpretation of frequency-selective non-linear blending CECT resulted in classification of 29/39 (74.3%) patients as GC and 10/39 (25.7%) as AC. Sensitivity/specificity/PPV/NPV for detection of GC were 22.6%/100%/100%/25% with linear blending CECT and 80.6%/50%/86.2%/40% with frequency-selective non-linear blending CECT, respectively. Based on the histopathologic diagnosis frequency-selective non-linear blending had a significant improvement (p > 0.0001) in the diagnostic accuracy of gangrenous cholecystitis compared with linear blending.

Conclusion

Frequency-selective non-linear blending post-processing increases the diagnostic accuracy of gangrenous cholecystitis owing to improved visualization of absence of focal enhancement and mural ulcerations.

Using Correlative Properties of Neighboring Pixels to Improve Gray-White Differentiation in Pediatric Head CT Images

BACKGROUND AND PURPOSE

A lower radiation dose can have a detrimental effect on the quality of head CT images. The aim of this study performed in a pediatric population was to test whether an image-processing algorithm (Correlative Image Enhancement) based on the correlation among intensities of neighboring pixels can improve gray-white differentiation in head CTs.

MATERIALS AND METHODS

Sixty baseline head CT images with normal findings obtained from scans of 30 children were processed using Correlative Image Enhancement to produce corresponding enhanced images. Gray-white differentiation in baseline and enhanced images was assessed quantitatively by calculating the contrast-to-noise ratio and conspicuity in equivalent ROIs in gray and white matter. Two masked readers rated the images for visibility of gray-white differentiation on a 5-point Likert scale. Differences in both quantitative and qualitative measures of gray-white differentiation between baseline and enhanced images were tested for statistical significance. P values < .05 were considered significant.

RESULTS

Image processing resulted in improvement in the contrast-to-noise ratio (from 1.86 ± 0.94 to 2.26 ± 1.00, P = .02) as well as conspicuity (from 37.28 ± 11.56 to 46.4 ± 11.5, P < .001). This was accompanied by improved subjective visibility of gray-white differentiation as reported by both readers (P < .01).

CONCLUSIONS

Image processing using Correlative Image Enhancement had a beneficial effect on quantitative measures of gray-white differentiation. This translated into improved perception of gray-white differentiation by readers. Further studies are needed to assess the effect of such image processing on the detection of disease processes using head CTs.

Improved CT-detection of acute bowel ischemia using frequency selective non-linear image blending

Background

Computed tomography (CT) as a fast and reliable diagnostic technique is the imaging modality of choice for acute bowel ischemia. However, diagnostic is often difficult mainly due to low attenuation differences between ischemic and perfused segments.

Purpose

To compare the diagnostic efficacy of a new post-processing tool based on frequency selective non-linear blending with that of conventional linear contrast-enhanced CT (CECT) image blending for the detection of bowel ischemia.

Material and Methods

Twenty-seven consecutive patients (19 women; mean age = 73.7 years, age range = 50–94 years) with acute bowel ischemia were scanned using multidetector CT (120 kV; 100–200 mAs). Pre-contrast and portal venous scans (65–70 s delay) were acquired. All patients underwent surgery for acute bowel ischemia and intraoperative diagnosis as well as histologic evaluation of explanted bowel segments was considered “gold standard.” First, two radiologists read the conventional CECT images in which linear blending was adapted for optimal contrast, and second (three weeks later) the frequency selective non-linear blending (F-NLB) image. Attenuation values were compared, both in the involved and non-involved bowel segments creating ratios between unenhanced and CECT.

Results

The mean attenuation difference between ischemic and non-ischemic wall in the portal venous scan was 69.54 HU (reader 2 = 69.01 HU) higher for F-NLB compared with conventional CECT. Also, the attenuation ratio between contrast-enhanced and pre-contrast CT data for the non-ischemic walls showed significantly higher values for the F-NLB image (CECT: reader 1 = 2.11 (reader 2 = 3.36), F-NLB: reader 1 = 4.46 (reader 2 = 4.98)]. Sensitivity in detecting ischemic areas increased significantly for both readers using F-NLB (CECT: reader 1/2 = 53%/65% versus F-NLB: reader 1/2 = 62%/75%).

Conclusion

Frequency selective non-linear blending improves detection of bowel ischemia compared with conventional CECT by increasing attenuation differences between ischemic and perfused segments.

Imaging of cerebral ischemic edema and neuronal death

PURPOSE

In acute cerebral ischemia, the assessment of irreversible injury is crucial for treatment decisions and the patient's prognosis. There is still uncertainty how imaging can safely differentiate reversible from irreversible ischemic brain tissue in the acute phase of stroke.

METHODS

We have searched PubMed and Google Scholar for experimental and clinical papers describing the pathology and pathophysiology of cerebral ischemia under controlled conditions.

RESULTS

Within the first 6 h of stroke onset, ischemic cell injury is subtle and hard to recognize under the microscope. Functional impairment is obvious, but can be induced by ischemic blood flow allowing recovery with flow restoration. The critical cerebral blood flow (CBF) threshold for irreversible injury is ~15 ml/100 g × min. Below this threshold, ischemic brain tissue takes up water in case of any residual capillary flow (ionic edema). Because tissue water content is linearly related to X-ray attenuation, computed tomography (CT) can detect and measure ionic edema and, thus, determine ischemic brain infarction. In contrast, diffusion-weighted magnetic resonance imaging (DWI) detects cytotoxic edema that develops at higher thresholds of ischemic CBF and is thus highly sensitive for milder levels of brain ischemia, but not specific for irreversible brain tissue injury.

CONCLUSION

CT and MRI are complimentary in the detection of ischemic stroke pathology and are valuable for treatment decisions.