Myelography Using Energy-Integrating Detector CT Versus Photon-Counting Detector CT for Detection of CSF-Venous Fistulas in Patients With Spontaneous Intracranial Hypotension.

BACKGROUND. CSF-venous fistulas (CVFs), which are an increasingly recognized cause of spontaneous intracranial hypotension (SIH), are often diminutive in size and exceedingly difficult to detect by conventional imaging. OBJECTIVE. This purpose of this study was to compare energy-integrating detector (EID) CT myelography and photon-counting detector (PCD) CT myelography in terms of image quality and diagnostic performance for detecting CVFs in patients with SIH. METHODS. This retrospective study included 38 patients (15 men and 23 women; mean age, 55 ± 10 [SD] years) with SIH who underwent both clinically indicated EID CT myelography (slice thickness, 0.625 mm) and PCD CT myelography (slice thickness, 0.2 mm; performed in ultrahigh-resolution mode) to assess for CSF leak. Three blinded radiologists reviewed examinations in random order, assessing image noise, discernibility of spinal nerve root sleeves, and overall image quality (each assessed using a scale of 0-100, with 100 denoting highest quality) and recording locations of the CVFs. Definite CVFs were defined as CVFs described in CT myelography reports using unequivocal language and having an attenuation value greater than 70 HU. RESULTS. For all readers, PCD CT myelography, in comparison with EID CT myelography, showed higher mean image noise (reader 1: 69.9 ± 18.5 [SD] vs 37.6 ± 15.2; reader 2: 59.5 ± 8.7 vs 49.3 ± 12.7; and reader 3: 57.6 ± 13.2 vs 42.1 ± 16.6), higher mean nerve root sleeve discernibility (reader 1: 81.6 ± 21.7 [SD] vs 30.4 ± 13.6; reader 2: 83.6 ± 10 vs 70.1 ± 18.9; and reader 3: 59.6 ± 13.5 vs 50.5 ± 14.4), and higher mean overall image quality (reader 1: 83.2 ± 20.0 [SD] vs 38.1 ± 13.5; reader 2: 80.1 ± 10.1 vs 72.4 ± 19.8; and reader 3: 57.8 ± 11.2 vs 51.9 ± 13.6) (all p < .05). Eleven patients had a definite CVF. Sensitivity and specificity of EID CT myelography and PCD CT myelography for the detection of definite CVF were 45% and 96% versus 64% and 85%, respectively, for reader 1; 36% and 100% versus 55% and 96%, respectively, for reader 2; and 57% and 100% versus 55% and 93%, respectively, for reader 3. The sensitivity was significantly higher for PCD CT myelography than for EID CT myelography for reader 1 and reader 2 (both p < .05) and was not significantly different between the two techniques for reader 3 (p = .45); for all three readers, specificity was not significantly different between the two modalities (all p > .05). CONCLUSION. In comparison with EID CT myelography, PCD CT myelography yielded significantly improved image quality with significantly higher sensitivity for CVFs (for two of three readers), without significant loss of specificity. CLINICAL IMPACT. The findings support a potential role for PCD CT myelography in facilitating earlier diagnosis and targeted treatment of SIH, avoiding high morbidity during potentially prolonged diagnostic workups.

Technology Characterization Through Diverse Evaluation Methodologies: Application to Thoracic Imaging in Photon-Counting Computed Tomography.

OBJECTIVE: Different methods can be used to condition imaging systems for clinical use. The purpose of this study was to assess how these methods complement one another in evaluating a system for clinical integration of an emerging technology, photon-counting computed tomography (PCCT), for thoracic imaging. METHODS: Four methods were used to assess a clinical PCCT system (NAEOTOM Alpha; Siemens Healthineers, Forchheim, Germany) across 3 reconstruction kernels (Br40f, Br48f, and Br56f). First, a phantom evaluation was performed using a computed tomography quality control phantom to characterize noise magnitude, spatial resolution, and detectability. Second, clinical images acquired using conventional and PCCT systems were used for a multi-institutional reader study where readers from 2 institutions were asked to rank their preference of images. Third, the clinical images were assessed in terms of in vivo image quality characterization of global noise index and detectability. Fourth, a virtual imaging trial was conducted using a validated simulation platform (DukeSim) that models PCCT and a virtual patient model (XCAT) with embedded lung lesions imaged under differing conditions of respiratory phase and positional displacement. Using known ground truth of the patient model, images were evaluated for quantitative biomarkers of lung intensity histograms and lesion morphology metrics. RESULTS: For the physical phantom study, the Br56f kernel was shown to have the highest resolution despite having the highest noise and lowest detectability. Readers across both institutions preferred the Br56f kernel (71% first rank) with a high interclass correlation (0.990). In vivo assessments found superior detectability for PCCT compared with conventional computed tomography but higher noise and reduced detectability with increased kernel sharpness. For the virtual imaging trial, Br40f was shown to have the best performance for histogram measures, whereas Br56f was shown to have the most precise and accurate morphology metrics. CONCLUSION: The 4 evaluation methods each have their strengths and limitations and bring complementary insight to the evaluation of PCCT. Although no method offers a complete answer, concordant findings between methods offer affirmatory confidence in a decision, whereas discordant ones offer insight for added perspective. Aggregating our findings, we concluded the Br56f kernel best for high-resolution tasks and Br40f for contrast-dependent tasks.

The Multifaceted S100B Protein: A Role in Obesity and Diabetes?

The S100B protein is abundant in the nervous system, mainly in astrocytes, and is also present in other districts. Among these, the adipose tissue is a site of concentration for the protein. In the light of consistent research showing some associations between S100B and adipose tissue in the context of obesity, metabolic disorders, and diabetes, this review tunes the possible role of S100B in the pathogenic processes of these disorders, which are known to involve the adipose tissue. The reported data suggest a role for adipose S100B in obesity/diabetes processes, thus putatively re-proposing the role played by astrocytic S100B in neuroinflammatory/neurodegenerative processes.

S100B Expression Plays a Crucial Role in Cytotoxicity, Reactive Oxygen Species Generation and Nitric Oxide Synthase Activation Induced by Amyloid ß-Protein in an Astrocytoma Cell Line.

S100B is an astrocytic cytokine that has been shown to be involved in several neurodegenerative diseases. We used an astrocytoma cell line (U373 MG) silenced for S100B, and stimulated it with amyloid beta-peptide (Aß) as a known paradigm factor for astrocyte activation, and showed that the ability of the cell (including the gene machinery) to express S100B is a prerequisite for inducing reactive astrocytic features, such as ROS generation, NOS activation and cytotoxicity. Our results showed that control astrocytoma cell line exhibited overexpression of S100B after Aß treatment, and subsequently cytotoxicity, increased ROS generation and NOS activation. In contrast, cells silenced with S100B were essentially protected, consistently reducing cell death, significantly decreasing oxygen radical generation and nitric oxide synthase activity. The conclusive aim of the present study was to show a causative linkage between the cell expression of S100B and induction of astrocyte activation processes, such as cytotoxicity, ROS and NOS activation.

The S100B Protein: A Multifaceted Pathogenic Factor More Than a Biomarker.

S100B is a calcium-binding protein mainly concentrated in astrocytes in the nervous system. Its levels in biological fluids are recognized as a reliable biomarker of active neural distress, and more recently, mounting evidence points to S100B as a Damage-Associated Molecular Pattern molecule, which, at high concentration, triggers tissue reactions to damage. S100B levels and/or distribution in the nervous tissue of patients and/or experimental models of different neural disorders, for which the protein is used as a biomarker, are directly related to the progress of the disease. In addition, in experimental models of diseases such as Alzheimer's and Parkinson's diseases, amyotrophic lateral sclerosis, multiple sclerosis, traumatic and vascular acute neural injury, epilepsy, and inflammatory bowel disease, alteration of S100B levels correlates with the occurrence of clinical and/or toxic parameters. In general, overexpression/administration of S100B worsens the clinical presentation, whereas deletion/inactivation of the protein contributes to the amelioration of the symptoms. Thus, the S100B protein may be proposed as a common pathogenic factor in different disorders, sharing different symptoms and etiologies but appearing to share some common pathogenic processes reasonably attributable to neuroinflammation.

S100B Affects Gut Microbiota Biodiversity.

This in vivo study in mice addresses the relationship between the biodiversity of the microbiota and the levels of S100B, a protein present in enteroglial cells, but also in foods such as milk. A positive significant correlation was observed between S100B levels and Shannon values, which was reduced after treatment with Pentamidine, an inhibitor of S100B function, indicating that the correlation was influenced by the modulation of S100B activity. Using the bootstrap average method based on the distribution of the S100B concentration, three groups were identified, exhibiting a significant difference between the microbial profiles. Operational taxonomic units, when analyzed by SIMPER analysis, showed that genera regarded to be eubiotic were mainly concentrated in the intermediate group, while genera potentially harboring pathobionts often appeared to be more concentrated in groups where the S100B amounts were very low or high. Finally, in a pilot experiment, S100B was administered orally, and the microbial profiles appeared to be modified accordingly. These data may open novel perspectives involving the possibility of S100B-mediated regulation in the intestinal microbiota.

Past and Future of the Molecular Characterization of the T Cell Repertoire: Some Highlights of Eli Sercarz's Contributions.

The contribution of Eli E. Sercarz to immunology and immunopathology has been remarkable and achieved many milestones in the understanding of the processes of the mechanisms fine-tuning immune responses. A part of his work was dedicated to the study of the deep complexity of the lymphocyte T cell repertoire and its importance during the physiologic development and disease, such as clonal heterogeneity of T cell responses. Starting from these studies, under his mentoring, we had the opportunity to implement the spectratyping method and apply it to human and experimental autoimmune diseases, obtaining intriguing results. The open question of this brief review is the possible role of this fine and complex technique, the immunoscope analysis, in the era of the big data and omics.

Comparison of 12 surrogates to characterize CT radiation risk across a clinical population.

OBJECTIVES: Quantifying radiation burden is essential for justification, optimization, and personalization of CT procedures and can be characterized by a variety of risk surrogates inducing different radiological risk reflections. This study compared how twelve such metrics can characterize risk across patient populations. METHODS: This study included 1394 CT examinations (abdominopelvic and chest). Organ doses were calculated using Monte Carlo methods. The following risk surrogates were considered: volume computed tomography dose index (CTDIvol), dose-length product (DLP), size-specific dose estimate (SSDE), DLP-based effective dose (EDk ), dose to a defining organ (ODD), effective dose and risk index based on organ doses (EDOD, RI), and risk index for a 20-year-old patient (RIrp). The last three metrics were also calculated for a reference ICRP-110 model (ODD,0, ED0, and RI0). Lastly, motivated by the ICRP, an adjusted-effective dose was calculated as [Formula: see text]. A linear regression was applied to assess each metric's dependency on RI. The results were characterized in terms of risk sensitivity index (RSI) and risk differentiability index (RDI). RESULTS: The analysis reported significant differences between the metrics with EDr showing the best concordance with RI in terms of RSI and RDI. Across all metrics and protocols, RSI ranged between 0.37 (SSDE) and 1.29 (RI0); RDI ranged between 0.39 (EDk) and 0.01 (EDr) cancers × 103patients × 100 mGy. CONCLUSION: Different risk surrogates lead to different population risk characterizations. EDr exhibited a close characterization of population risk, also showing the best differentiability. Care should be exercised in drawing risk predictions from unrepresentative risk metrics applied to a population. KEY POINTS: • Radiation risk characterization in CT populations is strongly affected by the surrogate used to describe it. • Different risk surrogates can lead to different characterization of population risk. • Healthcare professionals should exercise care in ascribing an implicit risk to factors that do not closely reflect risk.

Patient-Informed Organ Dose Estimation in Clinical CT: Implementation and Effective Dose Assessment in 1048 Clinical Patients.

OBJECTIVE. The purpose of this study is to comprehensively implement a patient-informed organ dose monitoring framework for clinical CT and compare the effective dose (ED) according to the patient-informed organ dose with ED according to the dose-length product (DLP) in 1048 patients. MATERIALS AND METHODS. Organ doses for a given examination are computed by matching the topogram to a computational phantom from a library of anthropomorphic phantoms and scaling the fixed tube current dose coefficients by the examination volume CT dose index (CTDIvol) and the tube-current modulation using a previously validated convolution-based technique. In this study, the library was expanded to 58 adult, 56 pediatric, five pregnant, and 12 International Commission on Radiological Protection (ICRP) reference models, and the technique was extended to include multiple protocols, a bias correction, and uncertainty estimates. The method was implemented in a clinical monitoring system to estimate organ dose and organ dose-based ED for 647 abdomen-pelvis and 401 chest examinations, which were compared with DLP-based ED using a t test. RESULTS. For the majority of the organs, the maximum errors in organ dose estimation were 18% and 8%, averaged across all protocols, without and with bias correction, respectively. For the patient examinations, DLP-based ED was significantly different from organ dose-based ED by as much as 190.9% and 234.7% for chest and abdomen-pelvis scans, respectively (mean, 9.0% and 24.3%). The differences were statistically significant (p < .001) and exhibited overestimation for larger-sized patients and underestimation for smaller-sized patients. CONCLUSION. A patient-informed organ dose estimation framework was comprehensively implemented applicable to clinical imaging of adult, pediatric, and pregnant patients. Compared with organ dose-based ED, DLP-based ED may overestimate effective dose for larger-sized patients and underestimate it for smaller-sized patients.

S100B Protein as a Therapeutic Target in Multiple Sclerosis: The S100B Inhibitor Arundic Acid Protects from Chronic Experimental Autoimmune Encephalomyelitis.

S100B is an astrocytic protein behaving at high concentration as a damage-associated molecular pattern molecule. A direct correlation between the increased amount of S100B and inflammatory processes has been demonstrated, and in particular, the inhibitor of S100B activity pentamidine has been shown to ameliorate clinical scores and neuropathologic-biomolecular parameters in the relapsing-remitting experimental autoimmune encephalomyelitis mouse model of multiple sclerosis. This study investigates the effect of arundic acid (AA), a known inhibitor of astrocytic S100B synthesis, in the chronic experimental autoimmune encephalomyelitis, which is another mouse model of multiple sclerosis usually studied. By the daily evaluation of clinical scores and neuropathologic-molecular analysis performed in the spinal cord, we observed that the AA-treated group showed lower severity compared to the vehicle-treated mice, particularly in the early phase of disease onset. We also observed a significant reduction of astrocytosis, demyelination, immune infiltrates, proinflammatory cytokines expression and enzymatic oxidative reactivity in the AA-treated group. Overall, our results reinforce the involvement of S100B in the development of animal models of multiple sclerosis and propose AA targeting the S100B protein as a focused potential drug to be considered for multiple sclerosis treatment.

Modeling Patient-Informed Liver Contrast Perfusion in Contrast-enhanced Computed Tomography.

OBJECTIVE: To determine the correlation between patient attributes and contrast enhancement in liver parenchyma and demonstrate the potential for patient-informed prediction and optimization of contrast enhancement in liver imaging. METHODS: The study included 418 chest/abdomen/pelvis computed tomography scans, with 75% to 25% training-testing split. Two regression models were built to predict liver parenchyma contrast enhancement over time: first model (model A) utilized patient attributes (height, weight, sex, age, bolus volume, injection rate, scan times, body mass index, lean body mass) and bolus-tracking data. A second model (model B) only used the patient attributes. Pearson coefficient was used to assess predictive accuracy. RESULTS: Weight- and height-related features were found to be statistically significant predictors (P < 0.05), weight being the strongest. Of the 2 models, model A (r = 0.75) showed greater accuracy than model B (r = 0.42). CONCLUSIONS: Patient attributes can be used to build prediction model for liver parenchyma contrast enhancement. The model can have utility in optimization and improved consistency in contrast-enhanced liver imaging.

A comparison of COVID-19 and imaging radiation risk in clinical patient populations.

The outbreak of coronavirus SARS-COV2 affected more than 180 countries necessitating fast and accurate diagnostic tools. Reverse transcriptase polymerase chain reaction (RT-PCR) has been identified as a gold standard test with Chest CT and Chest Radiography showing promising results as well. However, radiological solutions have not been used extensively for the diagnosis of COVID-19 disease, partly due to radiation risk. This study aimed to provide quantitative comparison of imaging radiation risk versus COVID risk. The analysis was performed in terms of mortality rate per age group. COVID-19 mortality was extracted from epidemiological data across 299, 004 patients published by ISS-Integrated surveillance of COVID-19 in Italy. For radiological risk, the study considered 659 Chest CT performed in adult patients. Organ doses were estimated using a Monte Carlo method and then used to calculate Risk Index that was converted into an upper bound for related mortality rate following NCI-SEER data. COVID-19 mortality showed a rapid rise for ages >30 years old (min: 0.30%; max: 30.20%), whereas only four deaths were reported in the analysed patient cohort for ages <20 years old. The rates decreased for radiation risk across age groups. The median mortality rate across all ages for Chest-CT and Chest-Radiography were 0.007% (min: 0.005%; max: 0.011%) and 0.0003% (min: 0.0002%; max: 0.0004%), respectively. COVID-19, Chest Radiography, and Chest CT mortality rates showed different magnitudes and trends across age groups. In higher ages, the risk of COVID-19 far outweighs that of radiological exams. Based on risk comparison alone, Chest Radiography and CT for COVID-19 care is justified for patients older than 20 and 30 years old, respectively. Notwithstanding other aspects of diagnosis, the present results capture a component of risk consideration associated with the use of imaging for COVID. Once integrated with other diagnostic factors, they may help inform better management of the pandemic.

Expanding the Concept of Diagnostic Reference Levels to Noise and Dose Reference Levels in CT.

OBJECTIVE. Diagnostic reference levels were developed as guidance for radiation dose in medical imaging and, by inference, diagnostic quality. The objective of this work was to expand the concept of diagnostic reference levels to explicitly include noise of CT examinations to simultaneously target both dose and quality through corresponding reference values. MATERIALS AND METHODS. The study consisted of 2851 adult CT examinations performed with scanners from two manufacturers and two clinical protocols: abdominopelvic CT with IV contrast administration and chest CT without IV contrast administration. An institutional informatics system was used to automatically extract protocol type, patient diameter, volume CT dose index, and noise magnitude from images. The data were divided into five reference patient size ranges. Noise reference level, noise reference range, dose reference level, and dose reference range were defined for each size range. RESULTS. The data exhibited strong dependence between dose and patient size, weak dependence between noise and patient size, and different trends for different manufacturers with differing strategies for tube current modulation. The results suggest size-based reference intervals and levels for noise and dose (e.g., noise reference level and noise reference range of 11.5-12.9 HU and 11.0-14.0 HU for chest CT and 10.1-12.1 HU and 9.4-13.7 HU for abdominopelvic CT examinations) that can be targeted to improve clinical performance consistency. CONCLUSION. New reference levels and ranges, which simultaneously consider image noise and radiation dose information across wide patient populations, were defined and determined for two clinical protocols. The methods of new quantitative constraints may provide unique and useful information about the goal of managing the variability of image quality and dose in clinical CT examinations.

Low reliability of anti-KIR4.183-120 peptide auto-antibodies in multiple sclerosis patients.

BACKGROUND: Multiple sclerosis (MS) is an autoimmune disease for which auto-antibodies fully validated as diagnostic and prognostic biomarkers are widely desired. Recently, an immunoreactivity against the inward rectifying potassium channel 4.1 (KIR4.1) has been reported in a large proportion of a group of MS patients, with amino acids 83-120 being the major epitope. Moreover, a strong correlation between anti-KIR4.183-120 and anti-full-length-protein auto-antibodies titer was reported. However, this finding received limited confirmation. OBJECTIVE: Validation of the diagnostic potential of anti-KIR4.183-120 antibodies in 78 MS patients, 64 healthy blood donors, and 42 individuals with other neurological diseases. METHODS: Analysis of anti-KIR4.183-120 antibodies by enzyme-linked immunosorbent assay (ELISA) using a mouse antiserum we produced as a new ELISA reliability control. Additionally, evaluation of reactivity against 293-T cells transiently transfected with full-length KIR4.1 by flow cytometry. RESULTS: We found antibodies to KIR4.183-120 only in 13 out of 78 (16.6%) MS patients; among these, only 2 were positive for anti-full-length KIR4.1 antibodies. CONCLUSION: Employing a new reliability control and a new cytofluorometric assay, we cannot support anti-KIR4.183-120 auto-antibodies as a reliable biomarker in MS.

T cell repertoire in DQ5-positive MuSK-positive myasthenia gravis patients.

Myasthenia gravis (MG) is a prototypical antibody-mediated disease characterized by muscle weakness and fatigability. Serum antibodies to the acetylcholine receptor and muscle-specific tyrosine kinase receptor (MuSK) are found in about 85% and 8% of patients respectively. We have previously shown that more than 70% of MG patients with MuSK antibodies share the HLA DQ5 allele. The aim of the present study was to analyze the T cell receptor (TCR) repertoire specific for recombinant human MuSK protein. We used the CDR3 TRBV-TRBJ spectratyping (immunoscope) to analyze the T cell response to MuSK from 13 DQ5+ MuSK-MG patients and from 7 controls (six DQ5+ MuSK negative subjects and one DQ5- DQ3+ MuSK positive patient). DQ5+ MuSK-MG patients but not controls used a restricted set of TCR VJ rearrangements in response to MuSK stimulation. One semiprivate (TRBV29-TRBJ2.5) rearrangement was found in 5/13 patients, while 4 other semiprivate (one in TRBV28-TRBJ2.1 and in TRBV3-TRBJ1.2, and two in TRBV28-TRBJ1.2) rearrangements were differently shared by 4/13 patients each and were absent in controls. When we sequenced the TRBV29-TRBJ2.5 rearrangement, we obtained 26 different sequences of the expected 130 bp length from 117 samples of the 5 positive patients: two common motifs GXGQET/TEHQET were shared in 4 patients as semiprivate motifs. Thus, the MuSK-specific T-cell response appears to be restricted in DQ5+ MuSK-MG patients, with a semiprivate repertoire including a common motif of TRBV29. This oligoclonal restriction of T cells will allow the identification of immunodominant epitopes in the antigen, providing therefore new tools for diagnosis and targeted therapy.