Novel Imaging Approaches for Glioma Classification in the Era of the World Health Organization 2021 Update: A Scoping Review.

The 2021 WHO classification of CNS tumors is a challenge for neuroradiologists due to the central role of the molecular profile of tumors. The potential of novel data analysis tools in neuroimaging must be harnessed to maintain its role in predicting tumor subgroups. We performed a scoping review to determine current evidence and research gaps. A comprehensive literature search was conducted regarding glioma subgroups according to the 2021 WHO classification and the use of MRI, radiomics, machine learning, and deep learning algorithms. Sixty-two original articles were included and analyzed by extracting data on the study design and results. Only 8% of the studies included pediatric patients. Low-grade gliomas and diffuse midline gliomas were represented in one-third of the research papers. Public datasets were utilized in 22% of the studies. Conventional imaging sequences prevailed; data on functional MRI (DWI, PWI, CEST, etc.) are underrepresented. Multiparametric MRI yielded the best prediction results. IDH mutation and 1p/19q codeletion status prediction remain in focus with limited data on other molecular subgroups. Reported AUC values range from 0.6 to 0.98. Studies designed to assess generalizability are scarce. Performance is worse for smaller subgroups (e.g., 1p/19q codeleted or IDH1/2 mutated gliomas). More high-quality study designs with diversity in the analyzed population and techniques are needed.

Deep learning-accelerated image reconstruction in back pain-MRI imaging: reduction of acquisition time and improvement of image quality.

INTRODUCTION: Low back pain is a global health issue causing disability and missed work days. Commonly used MRI scans including T1-weighted and T2-weighted images provide detailed information of the spine and surrounding tissues. Artificial intelligence showed promise in improving image quality and simultaneously reducing scan time. This study evaluates the performance of deep learning (DL)-based T2 turbo spin-echo (TSE, T2DLR) and T1 TSE (T1DLR) in lumbar spine imaging regarding acquisition time, image quality, artifact resistance, and diagnostic confidence. MATERIAL AND METHODS: This retrospective monocentric study included 60 patients with lower back pain who underwent lumbar spinal MRI between February and April 2023. MRI parameters and DL reconstruction (DLR) techniques were utilized to acquire images. Two neuroradiologists independently evaluated image datasets based on various parameters using a 4-point Likert scale. RESULTS: Accelerated imaging showed significantly less image noise and artifacts, as well as better image sharpness, compared to standard imaging. Overall image quality and diagnostic confidence were higher in accelerated imaging. Relevant disk herniations and spinal fractures were detected in both DLR and conventional images. Both readers favored accelerated imaging in the majority of examinations. The lumbar spine examination time was cut by 61% in accelerated imaging compared to standard imaging. CONCLUSION: In conclusion, the utilization of deep learning-based image reconstruction techniques in lumbar spinal imaging resulted in significant time savings of up to 61% compared to standard imaging, while also improving image quality and diagnostic confidence. These findings highlight the potential of these techniques to enhance efficiency and accuracy in clinical practice for patients with lower back pain.

Improved diagnostic confidence and tumor type prediction in adult-type diffuse glioma by multimodal imaging including DCE perfusion and diffusion kurtosis mapping - A standardized multicenter study.

BACKGROUND AND PURPOSE: To evaluate the feasibility of a multimodal approach involving dynamic contrast-enhanced (DCE) perfusion imaging and diffusion kurtosis imaging (DKI) in the preoperative imaging of brain tumors in a multicenter setting, and to evaluate the effect on diagnostic confidence and accuracy for tumor grade and type prediction. MATERIALS AND METHODS: One hundred and thirty-three patients with brain tumors were imaged in six hospitals with a standardized multimodal protocol. Standard imaging and six parameter maps derived from DCE and DKI sequences were reviewed off-site by two independent readers. Image quality and diagnostic confidence were evaluated in qualitative analyses. Quantitative analyses were performed to assess diagnostic accuracy and the performance of DKI and DCE parameters for tumor grade differentiation and molecular tumor type determination. RESULTS: Standardized acquisition of DCE and DKI maps was feasible with excellent image quality. Diagnostic confidence was significantly improved from 85 % to 96 % (p = 0.0005) by additional review of the DCE and DKI maps. The combination of mean kurtosis and CBV was particularly advantageous for differentiating low-grade and high-grade glioma, oligodendroglial vs. astrocytic, and IDH1/2 wild type vs. mutated tumors. CONCLUSION: A multimodal imaging approach with DCE and DKI improves diagnostic confidence and yields higher diagnostic accuracy for predicting tumor grade and type in adult-type glioma.

Deep learning-accelerated image reconstruction in MRI of the orbit to shorten acquisition time and enhance image quality.

BACKGROUND AND PURPOSE: This study explores the use of deep learning (DL) techniques in MRI of the orbit to enhance imaging. Standard protocols, although detailed, have lengthy acquisition times. We investigate DL-based methods for T2-weighted and T1-weighted, fat-saturated, contrast-enhanced turbo spin echo (TSE) sequences, aiming to improve image quality, reduce acquisition time, minimize artifacts, and enhance diagnostic confidence in orbital imaging. METHODS: In a 3-Tesla MRI study of 50 patients evaluating orbital diseases from March to July 2023, conventional (TSES ) and DL TSE sequences (TSEDL ) were used. Two neuroradiologists independently assessed the image datasets for image quality, diagnostic confidence, noise levels, artifacts, and image sharpness using a randomized and blinded 4-point Likert scale. RESULTS: TSEDL significantly reduced image noise and artifacts, enhanced image sharpness, and decreased scan time, outperforming TSES (p < .05). TSEDL showed superior overall image quality and diagnostic confidence, with relevant findings effectively detected in both DL-based and conventional images. In 94% of cases, readers preferred accelerated imaging. CONCLUSION: The study proved that using DL for MRI image reconstruction in orbital scans significantly cut acquisition time by 69%. This approach also enhanced image quality, reduced image noise, sharpened images, and boosted diagnostic confidence.

Deep Learning Accelerated Image Reconstruction of Fluid-Attenuated Inversion Recovery Sequence in Brain Imaging: Reduction of Acquisition Time and Improvement of Image Quality.

RATIONALE AND OBJECTIVES: Fluid-attenuated inversion recovery (FLAIR) imaging is playing an increasingly significant role in the detection of brain metastases with a concomitant increase in the number of magnetic resonance imaging (MRI) examinations. Therefore, the purpose of this study was to investigate the impact on image quality and diagnostic confidence of an innovative deep learning-based accelerated FLAIR (FLAIRDLR) sequence of the brain compared to conventional (standard) FLAIR (FLAIRS) imaging. MATERIALS AND METHODS: Seventy consecutive patients with staging cerebral MRIs were retrospectively enrolled in this single-center study. The FLAIRDLR was conducted using the same MRI acquisition parameters as the FLAIRS sequence, except for a higher acceleration factor for parallel imaging (from 2 to 4), which resulted in a shorter acquisition time of 1:39 minute instead of 2:40 minutes (-38%). Two specialized neuroradiologists evaluated the imaging datasets using a Likert scale that ranged from 1 to 4, with 4 indicating the best score for the following parameters: sharpness, lesion demarcation, artifacts, overall image quality, and diagnostic confidence. Additionally, the image preference of the readers and the interreader agreement were assessed. RESULTS: The average age of the patients was 63 ± 11years. FLAIRDLR exhibited significantly less image noise than FLAIRS, with P-values of< .001 and< .05, respectively. The sharpness of the images and the ability to detect lesions were rated higher in FLAIRDLR, with a median score of 4 compared to a median score of 3 in FLAIRS (P-values of<.001 for both readers). In terms of overall image quality, FLAIRDLR was rated superior to FLAIRS, with a median score of 4 vs 3 (P-values of<.001 for both readers). Both readers preferred FLAIRDLR in 68/70 cases. CONCLUSION: The feasibility of deep learning FLAIR brain imaging was shown with additional 38% reduction in examination time compared to standard FLAIR imaging. Furthermore, this technique has shown improvement in image quality, noise reduction, and lesion demarcation.

Patterns of acute ischemic stroke and intracranial hemorrhage in patients with COVID-19 : Results of a retrospective multicenter neuroimaging-based study from three central European countries.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is an infection which can affect the central nervous system. In this study, we sought to investigate associations between neuroimaging findings with clinical, demographic, blood and cerebrospinal fluid (CSF) parameters, pre-existing conditions and the severity of acute COVID-19. MATERIALS AND METHODS: Retrospective multicenter data retrieval from 10 university medical centers in Germany, Switzerland and Austria between February 2020 and September 2021. We included patients with COVID-19, acute neurological symptoms and cranial imaging. We collected demographics, neurological symptoms, COVID-19 severity, results of cranial imaging, blood and CSF parameters during the hospital stay. RESULTS: 442 patients could be included. COVID-19 severity was mild in 124 (28.1%) patients (moderate n = 134/30.3%, severe n = 43/9.7%, critical n = 141/31.9%). 220 patients (49.8%) presented with respiratory symptoms, 167 (37.8%) presented with neurological symptoms first. Acute ischemic stroke (AIS) was detected in 70 (15.8%), intracranial hemorrhage (IH) in 48 (10.9%) patients. Typical risk factors were associated with AIS; extracorporeal membrane oxygenation therapy and invasive ventilation with IH. No association was found between the severity of COVID-19 or blood/CSF parameters and the occurrence of AIS or IH. DISCUSSION: AIS was the most common finding on cranial imaging. IH was more prevalent than expected but a less common finding than AIS. Patients with IH had a distinct clinical profile compared to patients with AIS. There was no association between AIS or IH and the severity of COVID-19. A considerable proportion of patients presented with neurological symptoms first. Laboratory parameters have limited value as a screening tool.

Correction: Characteristics of people with epilepsy and Neurocysticercosis in three eastern African countries-A pooled analysis.

[This corrects the article DOI: 10.1371/journal.pntd.0010870.].

Delirium in hospitalized COVID-19 patients: Predictors and implications for patient outcome.

INTRODUCTION: Delirium is recognized as a severe complication of coronavirus-disease-2019 (COVID-19). COVID-19-associated delirium has been linked to worse patient outcomes and is considered to be of multifactorial origin. Here we sought to evaluate the incidence and risk factors of delirium in hospitalized COVID-19 patients, along with its impact on clinical outcome. METHODS: Consecutive adult COVID-19 patients admitted to a tertiary academic referral hospital between March 1st and December 31st, 2020 were included. Potential risk factors for delirium were evaluated, including: age, gender, disease severity (as per the highest WHO grading reached during admission), laboratory parameters for infection and renal function (as per their most extreme values), and presence of comorbidities. To assess the relative strength of risk factors for predicting the occurrence of delirium, we performed a random-forest survival analysis. RESULTS: 347 patients with positive COVID-19 PCR test and median age 68.2 [IQR 55.5, 80.5] years were included. Of those, 79 patients (22.8%) developed delirium, 81 (23.3%) were transferred to ICU, 58 (16.7%) died. 163 (73.8%) patients were discharged home, 13 (5.9%) to another hospital, 32 (14.5%) to nursing homes, 13 (5.9%) to rehabilitation with an overall median admission-to-discharge time of 53 [IQR 14, 195] days. The strongest predictors for the occurrence of delirium were blood urea nitrogen (minimal depth value (MD): 3.33), age (MD: 3.75), disease severity (as captured by WHO grading; MD: 3.93), leukocyte count (MD: 4.22), the presence of a neurodegenerative history (MD: 4.43), ferritin (MD: 4.46) and creatinine (MD: 4.59) levels. CONCLUSION: The risk of delirium in COVID-19 can be stratified based on COVID-19 disease severity and-similar to delirium associated with other respiratory infections-the factors advanced age, neurodegenerative disease history, and presence of elevated infection and renal-retention parameters. Screening for these risk factors may facilitate early identification of patients at high-risk for COVID-19-associated delirium.

Characteristics of people with epilepsy and Neurocysticercosis in three eastern African countries-A pooled analysis.

BACKGROUND: Neurocysticercosis (NCC), a zoonotic disease caused by the pork tapeworm T. solium, represents one of the most common causes of secondary epilepsy but remains often undiagnosed due to lack of awareness and diagnostic facilities. METHODOLOGY: We pooled data from four cross-sectional studies on epilepsy and NCC in eastern Africa. Study sites were in Uganda, Malawi and in Tanzania (Dar es Salaam and Haydom). The study in Uganda and Malawi were community-based, the two studies in Tanzania were hospital-based. The same questionnaire was used for assessment of clinical characteristics of patients with epilepsy. Computed tomography (CT) scans and serological testing were performed in order to diagnose NCC. RESULTS: Overall, 1,179 people with epilepsy were included in our analysis. Of those, 941 PWE underwent CT scanning and were pooled for NCC analysis. Seventy patients were diagnosed with NCC, but NCC prevalence differed considerably between sites ranging from 2.0% (95%CI 0.4% to 3.6%) in Dar es Salaam to 17.5% (95%CI 12.4% to 22.6%) in Haydom. NCC prevalence did not show any association with sex but increased with age and was higher in rural than urban settings. In addition, being a farmer, non-Muslim, eating pork and living with pigs close by was associated with a higher NCC prevalence. PWE with NCC experienced their first epileptic seizure around 3 years later in life compared to PWE without NCC and their epileptic seizures seemed to be better controlled (p<0.001). There was no difference between focal onset seizures and focal signs on neurological examination in both groups (p = 0.49 and p = 0.92, respectively). The rT24H-EITB had a sensitivity for the detection of NCC of 70% (95% confidence interval [CI] 51 to 84%), the LLGP of 76% (95%CI 58 to 89%) and the antigen ELISA of 36% (95% CI 20 to 55%). CONCLUSIONS: NCC is prevalent among PWE in eastern Africa, although it may not be as common as previously stated. Demographic characteristics of PWE with NCC differed from those without NCC, but semiological characteristics and results on neurological examination did not differ compared to PWE without NCC. Interestingly, seizures seemed to be less frequent in PWE with NCC. Being aware of those differences and similarities may help triaging PWE for neuroimaging in order to establish a diagnosis of NCC.

Community-level prevalence of epilepsy and of neurocysticercosis among people with epilepsy in the Balaka district of Malawi: A cross-sectional study.

BACKGROUND: Epilepsy and neurocysticercosis (NCC) prevalence estimates in sub-Saharan Africa are still scarce but show important variation due to the population studied and different screening and diagnosis strategies used. The aims of this study were to estimate the prevalence of epileptic seizures and epilepsy in the sampled population, and the proportion of NCC among people with epilepsy (PWE) in a large cross-sectional study in a rural district of southern Malawi. METHODS: We conducted a community-based door-to-door screening study for epileptic seizures in Balaka, Malawi between October and December 2012. Past epileptic seizures were reported through a 15-item questionnaire answered by at least one person per household generating five major criteria. People who screened positive were further examined by a neurologist to establish diagnosis. Patients diagnosed with epilepsy were examined and offered Taenia solium cyst antigen and antibody serological tests, and a CT scan for the diagnosis of NCC. RESULTS: In total, screening information on 69,595 individuals was obtained for lifetime occurrence of epileptic seizures. 3,100 (4.5%) participants screened positive, of whom 1,913 (62%) could be followed-up and underwent further assessment. Lifetime prevalence was 3.0% (95% Bayesian credible interval [CI] 2.8 to 3.1%) and 1.2% (95%BCI 0.9 to 1.6%) for epileptic seizures and epilepsy, respectively. NCC prevalence among PWE was estimated to be 4.4% (95%BCI 0.8 to 8.5%). A diagnosis of epilepsy was ultimately reached for 455 participants. CONCLUSION: The results of this large community-based study contribute to the evaluation and understanding of the burden of epilepsy in the population and of NCC among PWE in sub-Saharan Africa.

Characteristics of people with epilepsy in three Eastern African countries - a pooled analysis.

BACKGROUND: Epilepsy is one of the most common neurological disorders worldwide. Yet, its treatment gap is large in some areas and especially in sub-Saharan Africa data on clinical, radiological and semiological characteristics, as well as on treatment of persons with epilepsy (PWE) are still scarce. METHODS: We pooled data from four cross-sectional studies on epilepsy in eastern Africa. Two studies from Malawi and Uganda were community-based; two studies in Tanzania (urban Dar es Salaam and rural Haydom) were hospital-based. Clinical characteristics of PWE were assessed by the same questionnaire. Additionally, data on treatment were collected and computed tomography (CT) scans were performed. RESULTS: Overall, 1179 PWE were included in our analysis (581 (49.3%) female, median age 22 years (IQR 15-32 years)). Up to 25% of the patients had focal onset seizures. Those showed a higher rate of remarkable CT scan findings, with especially post-ischaemic and neurocysticercosis-associated lesions, compared to PWE with generalized onset seizures (35.1% vs. 20%). The majority of the patients experienced tonic-clonic seizures (70-85%). Only 67-78% of PWE received anti-seizure medication (ASM) treatment in the community-based studies, mostly monotherapy with phenobarbital, phenytoin or carbamazepine. Yet, underdosage was frequent and a large proportion of PWE received alternative non-ASM treatment consisting of herbal treatment (up to 83%) and/or scarification (up to 20%). CONCLUSIONS: Epilepsy is common in sub-Saharan Africa, often caused by neurocysticercosis or ischaemic strokes. PWE suffer from high seizure rates and subsequent injuries, as well as from socio-economic consequences due to insufficient ASM treatment. This pooled analysis illustrates the need for structural programmes for adequate identification, education, assessment and treatment of PWE in sub-Saharan Africa.

GLINT: GlucoCEST in neoplastic tumors at 3 T-clinical results of GlucoCEST in gliomas.

OBJECTIVE: Clinical relevance of dynamic glucose enhanced (DGE) chemical exchange saturation transfer (CEST) imaging has mostly been demonstrated at ultra-high field (UHF) due to low effect size. Results of a cohort study at clinical field strength are shown herein. MATERIALS AND METHODS: Motion and field inhomogeneity corrected T1ρ-based DGE (DGE⍴) images were acquired before, during and after a D-glucose injection with 6.3 s temporal resolution to detect accumulation in the brain. Six glioma patients with clear blood-brain barrier (BBB) leakage, two glioma patients with suspected BBB leakage, and three glioma patients without BBB leakage were scanned at 3 T. RESULTS: In high-grade gliomas with BBB leakage, D-glucose uptake could be detected in the gadolinium (Gd) enhancing region as well as in the tumor necrosis with a maximum increase of ∆DGE⍴ around 0.25%, whereas unaffected white matter did not show any significant DGE⍴ increase. Glioma patients without Gd enhancement showed no detectable DGE⍴ effect within the tumor. CONCLUSION: First application of DGE⍴ in a patient cohort shows an association between BBB leakage and DGE signal irrespective of the tumor grade. This indicates that glucoCEST corresponds more to the disruptions of BBB with Gd uptake than to the molecular tumor profile or tumor grading.

Dynamic Susceptibility Perfusion Imaging for Differentiating Progressive Disease from Pseudoprogression in Diffuse Glioma Molecular Subtypes.

RATIONALE AND OBJECTIVES: Advanced adjuvant therapy of diffuse gliomas can result in equivocal findings in follow-up imaging. We aimed to assess the additional value of dynamic susceptibility perfusion imaging in the differentiation of progressive disease (PD) from pseudoprogression (PsP) in different molecular glioma subtypes. MATERIALS AND METHODS: 89 patients with treated diffuse glioma with different molecular subtypes (IDH wild type (Astro-IDHwt), IDH mutant astrocytomas (Astro-IDHmut) and oligodendrogliomas), and tumor-suspect lesions on post-treatment follow-up imaging were classified into two outcome groups (PD or PsP) retrospectively by histopathology or clinical follow-up. The relative cerebral blood volume (rCBV) was assessed in the tumor-suspect FLAIR and contrast-enhancing (CE) lesions. We analyzed how a multilevel classification using a molecular subtype, the presence of a CE lesion, and two rCBV histogram parameters performed for PD prediction compared with a decision tree model (DTM) using additional rCBV parameters. RESULTS: The PD rate was 69% in the whole cohort, 86% in Astro-IDHwt, 52% in Astro-IDHmut, and 55% in oligodendrogliomas. In the presence of a CE lesion, the PD rate was higher with 82%, 94%, 59%, and 88%, respectively; if there was no CE lesion, however, the PD rate was only 44%, 60%, 40%, and 33%, respectively. The additional use of the rCBV parameters in the DTM yielded a prediction accuracy for PD of 99%, 100%, 93%, and 95%, respectively. CONCLUSION: Utilizing combined information about the molecular tumor type, the presence or absence of CE lesions and rCBV parameters increases PD prediction accuracy in diffuse glioma.

Taenia solium cysticercosis and taeniasis in urban settings: Epidemiological evidence from a health-center based study among people with epilepsy in Dar es Salaam, Tanzania.

In Africa, urbanization is happening faster than ever before which results in new implications for transmission of infectious diseases. For the zoonotic parasite Taenia solium, a major cause of acquired epilepsy in endemic countries, the prevalence in urban settings is unknown. The present study investigated epidemiological, neurological, and radiological characteristics of T. solium cysticercosis and taeniasis (TSCT) in people with epilepsy (PWE) living in Dar es Salaam, Tanzania, one of the fastest growing cities worldwide. A total of 302 PWE were recruited from six health centers in the Kinondoni district of Dar es Salaam. Serological testing for T. solium cysticercosis-antigen (Ag) and -antibodies (Abs) and for T. solium taeniasis-Abs was performed in all PWE. In addition, clinical and radiological examinations that included cranial computed tomography (CT) were performed. With questionnaires, demographic data from study populations were collected, and factors associated with TSCT were assessed. Follow-up examinations were conducted in PWE with TSCT. T. solium cysticercosis-Ag was detected in three (0.99%; 95% CI: 0-2.11%), -Abs in eight (2.65%; 95% CI: 0.84-4.46%), and taeniasis-Abs in five (1.66%; 95% CI: 0.22-3.09%) of 302 PWE. Six PWE (1.99%; 95% CI: 0.41-3.56%) were diagnosed with neurocysticercosis (NCC). This study demonstrates the presence of TSCT in Dar es Salaam, however, NCC was only associated with a few cases of epilepsy. The small fraction of PWE with cysticercosis- and taeniasis-Abs may suggest that active transmission of T. solium plays only a minor role in Dar es Salaam. A sufficiently powered risk analysis was hampered by the small number of PWE with TSCT; therefore, further studies are required to determine the exact routes of infection and risk behavior of affected individuals.

Contrast-enhanced spectral mammography in patients with MRI contraindications.

Background Contrast-enhanced spectral mammography (CESM) is a novel breast imaging technique providing comparable diagnostic accuracy to breast magnetic resonance imaging (MRI). Purpose To show that CESM in patients with MRI contraindications is feasible, accurate, and useful as a problem-solving tool, and to highlight its limitations. Material and Methods A total of 118 patients with MRI contraindications were examined by CESM. Histology was obtained in 94 lesions and used as gold standard for diagnostic accuracy calculations. Imaging data were reviewed retrospectively for feasibility, accuracy, and technical problems. The diagnostic yield of CESM as a problem-solving tool and for therapy response evaluation was reviewed separately. Results CESM was more accurate than mammography (MG) for lesion categorization (r = 0.731, P < 0.0001 vs. r = 0.279, P = 0.006) and for lesion size estimation (r = 0.738 vs. r = 0.689, P < 0.0001). Negative predictive value of CESM was significantly higher than of MG (85.71% vs. 30.77%, P < 0.0001). When used for problem-solving, CESM changed patient management in 2/8 (25%) cases. Superposition artifacts and timing problems affected diagnostic utility in 3/118 (2.5%) patients. Conclusion CESM is a feasible and accurate alternative for patients with MRI contraindications, but it is necessary to be aware of the method's technical limitations.

Magnetic resonance imaging of the inferior alveolar nerve with special regard to metal artifact reduction.

PURPOSE: Magnetic resonance imaging (MRI) is an excellent imaging modality for displaying peripheral nerves. Since the knowledge about MRI of the inferior alveolar nerve (IAN) is limited, this pilot study aims to identify the prospects and limitations of MRI of the IAN, with special consideration of metal artifacts. MATERIALS AND METHODS: Initially, in vitro MRI of a dental implant was performed to establish an optimized protocol for metal artifact reduction using WARP sequences (a software package provided by Siemens Healthcare, Erlangen, Germany) including view angle tilting (VAT) and slice-encoding metal artifact correction (SEMAC) techniques. MRI with this optimized protocol was performed in three volunteers and four patients presenting with postoperative IAN impairment. Measuring the evaluable area and the artifact size was performed to assess the benefit of the specific artifact reduction sequences. RESULTS: In vitro imaging of a dental implant demonstrated that WARP sequences with VAT and SEMAC techniques led to a volume reduction of the artifact of up to 69.1%. Observations in both volunteers and patients with neurosensory IAN impairment showed a distinct artifact reduction with the MRI protocol adapted to metallic materials. Additionally VAT and SEMAC techniques improved the imaging due to further artifact reduction. As a main drawback of the VAT technique, the image quality was compromised by a blurring effect. Still, on 3-T MRI the resolution was high enough to reveal even fine structures. Imaging of the IAN was successful in all cases despite metallic material in the region of interest, and structural IAN changes could be detected in correlation with clinical symptoms. CONCLUSION: In contrast to conventional radiography and computed tomography, MRI can directly depict the IAN and provide reliable information on its position and exact course within the mandible. MRI offers an objective assessment of IAN injuries, supporting the decision-making process regarding surgical exploration and microneural repair. With the advent of specialized MRI techniques such as VAT and SEMAC, reduction of metal artifacts is considerably improved.

Ex vivo characterization of pathologic fluids with quantitative phase-contrast computed tomography.

PURPOSE: X-ray phase-contrast imaging (PCI) provides additional information beyond absorption characteristics by detecting the phase shift of the X-ray beam passing through material. The grating-based system works with standard polychromatic X-ray sources, promising a possible clinical implementation. PCI has been shown to provide additional information in soft-tissue samples. The aim of this study was to determine if ex vivo quantitative phase-contrast computed tomography (PCCT) may differentiate between pathologic fluid collections. MATERIALS AND METHODS: PCCT was performed with the grating interferometry method. A protein serial dilution, human blood samples and 17 clinical samples of pathologic fluid retentions were imaged and correlated with clinical chemistry measurements. Conventional and phase-contrast tomography images were reconstructed. Phase-contrast Hounsfield Units (HUp) were used for quantitative analysis analogously to conventional HU. The imaging was analyzed using overall means, ROI values as well as whole-volume-histograms and vertical gradients. Contrast to noise ratios were calculated between different probes and between imaging methods. RESULTS: HUp showed a very good linear correlation with protein concentration in vitro. In clinical samples, HUp correlated rather well with cell count and triglyceride content. PCI was better than absorption imaging at differentiating protein concentrations in the protein samples as well as at differentiating blood plasma from cellular components. PCI also allowed for differentiation of watery samples (such as lymphoceles) from pus. CONCLUSION: Phase-contrast computed tomography is a promising tool for the differentiation of pathologic fluids that appear homogenous with conventional attenuation imaging.

Ultra Low Dose CT Pulmonary Angiography with Iterative Reconstruction.

OBJECTIVE: Evaluation of a new iterative reconstruction algorithm (IMR) for detection/rule-out of pulmonary embolism (PE) in ultra-low dose computed tomography pulmonary angiography (CTPA). METHODS: Lower dose CT data sets were simulated based on CTPA examinations of 16 patients with pulmonary embolism (PE) with dose levels (DL) of 50%, 25%, 12.5%, 6.3% or 3.1% of the original tube current setting. Original CT data sets and simulated low-dose data sets were reconstructed with three reconstruction algorithms: the standard reconstruction algorithm "filtered back projection" (FBP), the first generation iterative reconstruction algorithm iDose and the next generation iterative reconstruction algorithm "Iterative Model Reconstruction" (IMR). In total, 288 CTPA data sets (16 patients, 6 tube current levels, 3 different algorithms) were evaluated by two blinded radiologists regarding image quality, diagnostic confidence, detectability of PE and contrast-to-noise ratio (CNR). RESULTS: iDose and IMR showed better detectability of PE than FBP. With IMR, sensitivity for detection of PE was 100% down to a dose level of 12.5%. iDose and IMR showed superiority to FBP regarding all characteristics of subjective (diagnostic confidence in detection of PE, image quality, image noise, artefacts) and objective image quality. The minimum DL providing acceptable diagnostic performance was 12.5% (= 0.45 mSv) for IMR, 25% (= 0.89 mSv) for iDose and 100% (= 3.57 mSv) for FBP. CNR was significantly (p < 0.001) improved by IMR compared to FBP and iDose at all dose levels. CONCLUSION: By using IMR for detection of PE, dose reduction for CTPA of up to 75% is possible while maintaining full diagnostic confidence. This would result in a mean effective dose of approximately 0.9 mSv for CTPA.