Minimalistic mycoplasmas harbor different functional toxin-antitoxin systems.

Mycoplasmas are minute bacteria controlled by very small genomes ranging from 0.6 to 1.4 Mbp. They encompass several important medical and veterinary pathogens that are often associated with a wide range of chronic diseases. The long persistence of mycoplasma cells in their hosts can exacerbate the spread of antimicrobial resistance observed for many species. However, the nature of the virulence factors driving this phenomenon in mycoplasmas is still unclear. Toxin-antitoxin systems (TA systems) are genetic elements widespread in many bacteria that were historically associated with bacterial persistence. Their presence on mycoplasma genomes has never been carefully assessed, especially for pathogenic species. Here we investigated three candidate TA systems in M. mycoides subsp. capri encoding a (i) novel AAA-ATPase/subtilisin-like serine protease module, (ii) a putative AbiEii/AbiEi pair and (iii) a putative Fic/RelB pair. We sequence analyzed fourteen genomes of M. mycoides subsp. capri and confirmed the presence of at least one TA module in each of them. Interestingly, horizontal gene transfer signatures were also found in several genomic loci containing TA systems for several mycoplasma species. Transcriptomic and proteomic data confirmed differential expression profiles of these TA systems during mycoplasma growth in vitro. While the use of heterologous expression systems based on E. coli and B. subtilis showed clear limitations, the functionality and neutralization capacities of all three candidate TA systems were successfully confirmed using M. capricolum subsp. capricolum as a host. Additionally, M. capricolum subsp. capricolum was used to confirm the presence of functional TA system homologs in mycoplasmas of the Hominis and Pneumoniae phylogenetic groups. Finally, we showed that several of these M. mycoides subsp. capri toxins tested in this study, and particularly the subtilisin-like serine protease, could be used to establish a kill switch in mycoplasmas for industrial applications.

Identification of Photorhabdus symbionts by MALDI-TOF MS.

Species of the bacterial genus Photorhabus live in a symbiotic relationship with Heterorhabditis entomopathogenic nematodes. Besides their use as biological control agents against agricultural pests, some Photorhabdus species are also a source of natural products and are of medical interest due to their ability to cause tissue infections and subcutaneous lesions in humans. Given the diversity of Photorhabdus species, rapid and reliable methods to resolve this genus to the species level are needed. In this study, we evaluated the potential of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for the identification of Photorhabdus species. To this end, we established a collection of 54 isolates consisting of type strains and multiple field strains that belong to each of the validly described species and subspecies of this genus. Reference spectra for the strains were generated and used to complement a currently available database. The extended reference database was then used for identification based on the direct transfer sample preparation method and the protein fingerprint of single colonies. High-level discrimination of distantly related species was observed. However, lower discrimination was observed with some of the most closely related species and subspecies. Our results therefore suggest that MALDI-TOF MS can be used to correctly identify Photorhabdus strains at the genus and species level, but has limited resolution power for closely related species and subspecies. Our study demonstrates the suitability and limitations of MALDI-TOF-based identification methods for assessment of the taxonomic position and identification of Photorhabdus isolates.

7T MR of intracranial pathology: Preliminary observations and comparisons to 3T and 1.5T.

PURPOSE: There have been an increasing number of studies involving ultra-high-field 7T of intracranial pathology, however, comprehensive clinical studies of neuropathology at 7T still remain limited. 7T has the advantage of a higher signal-to-noise ratio and a higher contrast-to-noise ratio, compared to current low field clinical MR scanners. We hypothesized 7T applied clinically, may improve detection and characterization of intracranial pathology. MATERIALS AND METHODS: We performed an IRB-approved 7T prospective study of patients with neurological disease who previously had lower field 3T and 1.5T. All patients underwent 7T scans, using comparable clinical imaging protocols, with the aim of qualitatively comparing neurological lesions at 7T with 3T or 1.5T. To qualitatively assess lesion conspicuity at 7T compared with low field, 80-paired images were viewed by 10 experienced neuroradiologists and scored on a 5-point scale. Inter-rater agreement was characterized using a raw percent agreement and mean weighted kappa. RESULTS: One-hundred and four patients with known neurological disease have been scanned to date. Fifty-five patients with epilepsy, 18 patients with mild traumatic brain injury, 11 patients with known or suspected multiple sclerosis, 9 patients with amyotrophic lateral sclerosis, 4 patients with intracranial neoplasm, 2 patients with orbital melanoma, 2 patients with cortical infarcts, 2 patients with cavernous malformations, and 1 patient with cerebral amyloid angiopathy. From qualitative observations, we found better resolution and improved detection of lesions at 7T compared to 3T. There was a 55% raw inter-rater agreement that lesions were more conspicuous on 7T than 3T/1.5T, compared with a 6% agreement that lesions were more conspicuous on 3T/1.5T than 7T. CONCLUSION: Our findings show that the primary clinical advantages of 7T magnets, which include higher signal-to-noise ratio, higher contrast-to-noise ratio, smaller voxels and stronger susceptibility contrast, may increase lesion conspicuity, detection and characterization compared to low field 1.5T and 3T. However, low field which detects a plethora of intracranial pathology remains the mainstay for diagnostic imaging until limitations at 7T are addressed and further evidence of utility provided.

Determination of Antidepressants in Hair via UHPLC-MS/MS as a Complementary Informative Tool for Clinical and Forensic Toxicological Assessments.

BACKGROUND: Hair analysis is a complementary approach for the detection of antidepressants (ADs) in clinical and forensic schemes because it yields a picture of long-term exposure over a time window depending on the length of the hair. METHODS: A fast and sensitive ultra-high performance liquid chromatography tandem mass spectrometry method using a BEH C18 column with a mobile phase consisting of ammonium acetate/acetonitrile was developed and validated according to international guidelines for the simultaneous analysis of 24 ADs in hair. Methanol/acetonitrile/ammonium formate buffer 1 mmol/L (25:25:50, vol/vol/vol) was used to extract the drugs from the hair matrix before a solid-phase extraction using cation exchange cartridges was applied. Hair samples (n = 18) obtained from a US workplace drug testing center were analyzed to demonstrate the method applicability. RESULTS: The limit of quantification values ranged from 0.006 to 0.05 ng/mg hair, and the calibration curves ranged from the LOQ up to 10 ng/mg hair. The bias and imprecision were <15% for all the compounds except maprotiline (17%). This was evaluated with 2 "in-house" QCs and 1 authentic hair sample from an amitriptyline user. No significant matrix effects for most of the compounds were observed, and the extraction efficiency of the sample cleanup procedure ranged from 40% to 80% (relative standard deviation <15%) [except for demethylcitalopram, didemethylcitalopram, and trazodone (relative standard deviation <33%)]. The method was then successfully applied to the analysis of hair samples from workplace drug testing. The samples were analyzed in 1-cm segments to determine the medication history of the patient. When a sample was reported positive, information concerning the prescription was obtained anonymously for several samples. Concentrations of (minimum-maximum value in ng/mg) citalopram (0.01-132: extrapolated), trazodone (0.01-5.3), sertraline (0.05-0.1), paroxetine (0.02-1.0), bupropion (0.05-0.6), fluoxetine (0.5-8), and amitriptyline (0.2-4.8), including metabolites, are reported. CONCLUSIONS: This study may be of interest to clinical and forensic laboratories for interpretation because it demonstrates the AD concentration windows in hair and the link to the prescribed drugs.

Analysis of cocaine and metabolites in hair: validation and application of measurement of hydroxycocaine metabolites as evidence of cocaine ingestion.

An LC/MS/MS method to identify and quantitate in hair the minor metabolites of cocaine-meta-, para-, and ortho-hydroxy cocaine-was developed and validated. Analysis was performed on a triple quadrupole ABSciex API 3000 MS equipped with an atmospheric pressure ionization source via an IonSpray (ESI). For LC, a series 200 micro binary pump with a Perkin Elmer Model 200 autosampler was used. The limit of detection (LOD) and limit of quantification (LOQ) were 0.02 ng/10 mg hair, with linearity from 0.02 to 10 ng/10 mg hair. Concentrations of the para isomer in extensively washed hair samples were in the range of 1-2 % of the cocaine in the sample, while the concentrations of the ortho form were considerably less. The method was used to analyze large numbers of samples from two populations: workplace and criminal justice. In vitro experiments to determine if deodorants or peroxide-containing cosmetic treatments could result in the presence of these metabolites in hair showed that this does not occur with extensively washed hair. Presence of hydroxycocaines, when detected after aggressive washing of the hair samples, provides a valuable additional indicator of ingestion of cocaine rather than mere environmental exposure.

Somatic mosaicism of a novel IKBKG mutation in a male patient with incontinentia pigmenti.

Incontinentia pigmenti (IP) is an X-linked, dominant genodermatosis usually fatal in utero in males. In rare circumstances, survival is possible due to abnormal karyotype or somatic mosaicism. In this report, the mechanism and significance of loss of detectable mutation in peripheral blood leukocytes of a somatic mosaic male is discussed and an alternative approach to achieving molecular diagnosis presented. A male patient is reported, who initially presented at 2 days of age with a rash and seizure. Clinical assessment and histology of a skin biopsy were consistent with a diagnosis of IP. He was subsequently found to have bilateral retinal detachments. Screening for the common deletion in IKBKG was negative. A novel nonsense variant, c.937C>T (p.Gln313*) in IKBKG was identified at an approximate level of 15% in a blood sample taken at 10 days of age, but was undetectable in a sample taken at 3 years most likely due to selective apoptosis of mutant cells. Samples taken from the patient when he was 5-6 years of age identified the mutation at a low level in hair root and urine but not in blood or buccal cells. The detection of the mutation in cells derived from all germ layers indicates a de novo event at an early stage of embryogenesis. This is the first report of a nonsense mutation in a male IP patient.

Detection of Benzodiazepines and z-Drugs in Hair Using an UHPLC-MS/MS Validated Method: Application to Workplace Drug Testing.

BACKGROUND: A sensitive and reproducible Ultra High Performance Liquid Chromatography-Tandem Mass Spectrometry method has been developed for the simultaneous quantification of the 29 commonly prescribed benzodiazepines and z-drugs in hair. The method was validated according to international guidelines. METHODS: After decontamination (with dichloromethane and water), compounds were extracted from 20 mg of pulverized hair samples using methanol at 45°C and sonication for 2 hours. The drugs were recovered by liquid-liquid extraction using 1-chlorobutane, evaporated to dryness, and reconstituted with 100 µL of methanol before injection in the UPLC-MS/MS. RESULTS: The applied gradient ensured the elution of all the compounds within 7 minutes using 0.1% formic acid in water and methanol as mobile phase. The lower limit of quantification values ranged from 0.5 to 5 pg/mg of hair. Calibration curves were linear for almost all the compounds and ranged from the limit of quantification to 620 pg/mg hair. The bias and relative standard deviation of the intraday and interday imprecision were lower than 15% in 3 fortified "in-house" quality control samples, 1 external quality control sample, and 1 authentic hair sample (from a diazepam user). No significant matrix effects were observed for most of the compounds, and the extraction efficiency of the sample cleanup procedure ranged from 19% to 82% with a relative standard deviation <15% [except for clobazam (16%), loprazolam (20%), brotizolam (18%), and 7-aminoclonazepam (20%)]. The method was then successfully applied to the analysis of 40 hair samples from the workplace drug testing, containing alprazolam, estazolam, clonazepam, diazepam, zolpidem, and desalkylflurazepam (and metabolites). CONCLUSIONS: The method was completely validated and can be of interest to clinical and forensic laboratories.

Performance of GPT-4 on the American College of Radiology In-training Examination: Evaluating Accuracy, Model Drift, and Fine-tuning.

RATIONALE AND OBJECTIVES: In our study, we evaluate GPT-4's performance on the American College of Radiology (ACR) 2022 Diagnostic Radiology In-Training Examination (DXIT). We perform multiple experiments across time points to assess for model drift, as well as after fine-tuning to assess for differences in accuracy. MATERIALS AND METHODS: Questions were sequentially input into GPT-4 with a standardized prompt. Each answer was recorded and overall accuracy was calculated, as was logic-adjusted accuracy, and accuracy on image-based questions. This experiment was repeated several months later to assess for model drift, then again after the performance of fine-tuning to assess for changes in GPT's performance. RESULTS: GPT-4 achieved 58.5% overall accuracy, lower than the PGY-3 average (61.9%) but higher than the PGY-2 average (52.8%). Adjusted accuracy was 52.8%. GPT-4 showed significantly higher (p = 0.012) confidence for correct answers (87.1%) compared to incorrect (84.0%). Performance on image-based questions was significantly poorer (p < 0.001) at 45.4% compared to text-only questions (80.0%), with adjusted accuracy for image-based questions of 36.4%. When the questions were repeated, GPT-4 chose a different answer 25.5% of the time and there was no change in accuracy. Fine-tuning did not improve accuracy. CONCLUSION: GPT-4 performed between PGY-2 and PGY-3 levels on the 2022 DXIT, significantly poorer on image-based questions, and with large variability in answer choices across time points. Exploratory experiments in fine-tuning did not improve performance. This study underscores the potential and risks of using minimally-prompted general AI models in interpreting radiologic images as a diagnostic tool. Implementers of general AI radiology systems should exercise caution given the possibility of spurious yet confident responses.

Predictors of salvage therapy for parasagittal meningiomas treated with primary surgery, radiosurgery, or surgery plus adjuvant radiotherapy.

OBJECTIVE: Parasagittal meningiomas (PM) are treated with primary microsurgery, radiosurgery (SRS), or surgery with adjuvant radiation. We investigated predictors of tumor progression requiring salvage surgery or radiation treatment. We sought to determine whether primary treatment modality, or radiologic, histologic, and clinical variables were associated with tumor progression requiring salvage treatment. METHODS: Retrospective study of 109 consecutive patients with PMs treated with primary surgery, radiation (RT), or surgery plus adjuvant RT (2000-2017) and minimum 5 years follow-up. Patient, radiologic, histologic, and treatment data were analyzed using standard statistical methods. RESULTS: Median follow up was 8.5 years. Primary treatment for PM was surgery in 76 patients, radiation in 16 patients, and surgery plus adjuvant radiation in 17 patients. Forty percent of parasagittal meningiomas in our cohort required some form of salvage treatment. On univariate analysis, brain invasion (OR: 6.93, p < 0.01), WHO grade 2/3 (OR: 4.54, p < 0.01), peritumoral edema (OR: 2.81, p = 0.01), sagittal sinus invasion (OR: 6.36, p < 0.01), sagittal sinus occlusion (OR: 4.86, p < 0.01), and non-spherical shape (OR: 3.89, p < 0.01) were significantly associated with receiving salvage treatment. On multivariate analysis, superior sagittal sinus invasion (OR: 8.22, p = 0.01) and WHO grade 2&3 (OR: 7.58, p < 0.01) were independently associated with receiving salvage treatment. There was no difference in time to salvage therapy (p = 0.11) or time to progression (p = 0.43) between patients receiving primary surgery alone, RT alone, or surgery plus adjuvant RT. Patients who had initial surgery were more likely to have peritumoral edema on preoperative imaging (p = 0.01). Median tumor volume was 19.0 cm3 in patients receiving primary surgery, 5.3 cm3 for RT, and 24.4 cm3 for surgery plus adjuvant RT (p < 0.01). CONCLUSION: Superior sagittal sinus invasion and WHO grade 2/3 are independently associated with PM progression requiring salvage therapy regardless of extent of resection or primary treatment modality. Parasagittal meningiomas have a high rate of recurrence with 80.0% of patients with WHO grade 2/3 tumors with sinus invasion requiring salvage treatment whereas only 13.6% of the WHO grade 1 tumors without sinus invasion required salvage treatment. This information is useful when counseling patients about disease management and setting expectations.

Amphetamines in Workplace Testing Hair Samples over the Years 2011-2020.

Amphetamines (AMPs) in hair were investigated with thousands of workplace testing head and body hair samples collected and analyzed over 10 years and tabulated by year. All samples were washed by a published extensive method prior to confirmation by liquid chromatography-mass spectrometry-mass spectrometry. Presented are concentrations of parent methamphetamine (METH), 3,4-methylenedioxymethamphetamine (MDMA) and methylenedioxyamphetamine as metabolite and AMP as metabolite and without the presence of parent drug. Some differences in METH concentrations from year to year were significant, and some ratios of metabolite to parent drug for both METH and MDMA also varied significantly. While rates of METH use may not have changed significantly, some aspects of the drugs ingested as demonstrated by hair analysis varied over the 10-year period.

Identifying contamination versus ingestion in hair testing, with cocaine as example.

When developing a procedure to identify external contamination of hair as opposed to drug that is in hair from ingestion, there are components of the process that must be considered in the final method. A method that does not achieve the objective may be missing one or more of these elements: choice of solvent, a drug-binding agent, ratio of solvent to hair, temperature, time, intactness of the hair, and establishing, for the chosen method, a criterion based on the drug contents of the wash and hair that indicates the hair may be contaminated.

Cannabinoids Tetrahydrocannabinol, Cannabinol, Cannabidiol, Tetrahydrocannabivarin and 11-nor-9-carboxy-∆9-THC in Hair.

The cannabinoids tetrahydrocannabinol (THC), tetrahydrocannabivarin (THCV), cannabidiol (CBD), cannabinol (CBN) and (-)-11-nor-9-carboxy-∆9-tetrahydrocannabinol (THC-COOH) were determined in 4,773 hair samples. Confirmation of THC-COOH was by GC-MS-MS (gas chromatography--mass spectrometry-mass spectrometry). Confirmation of THC, THCV, CBN and CBD was by LC-MS-MS (liquid chromatoraphy--mass spectrometry-mass spectrometry) on an AB Sciex QTRAP 6500+ LC-MS-MS. The purpose of this work was not to utilize any analyte other than THC-COOH as indicative of ingestion, but to assess the absence or presence, and relative concentrations, of the other cannabinoid analytes in hair of marijuana users vs. primarily CBD users. In this regard, 10% of samples contained significantly higher concentrations of CBD relative to THC than the other 90%. A concentration of CBD that is five times greater than that of THC was proposed as good evidence of primarily CBD ingestion. THC concentrations in the samples ranged from below the limit of detection (5 pg/mg) to 47,808 pg/mg hair, varying widely in the relationship between parent THC and the metabolite THC-COOH. CBN was present in most samples, but concentrations relative to THC decreased with increasing THC concentrations. Only 26% of the samples contained THCV detectable by the method. When present, THCV concentrations averaged 1.77% of THC. A limitation of this study is the lack of subject histories to determine the types and amounts of products used and the mode of ingestion. Also, not all THC from external contamination may be removed. Nonetheless, the data provide a useful guide as to what cannabinoids may be found in hair, at what concentrations and under conditions of marijuana use vs. likely primarily CBD use.

Artificial intelligence in the radiomic analysis of glioblastomas: A review, taxonomy, and perspective.

Radiological imaging techniques, including magnetic resonance imaging (MRI) and positron emission tomography (PET), are the standard-of-care non-invasive diagnostic approaches widely applied in neuro-oncology. Unfortunately, accurate interpretation of radiological imaging data is constantly challenged by the indistinguishable radiological image features shared by different pathological changes associated with tumor progression and/or various therapeutic interventions. In recent years, machine learning (ML)-based artificial intelligence (AI) technology has been widely applied in medical image processing and bioinformatics due to its advantages in implicit image feature extraction and integrative data analysis. Despite its recent rapid development, ML technology still faces many hurdles for its broader applications in neuro-oncological radiomic analysis, such as lack of large accessible standardized real patient radiomic brain tumor data of all kinds and reliable predictions on tumor response upon various treatments. Therefore, understanding ML-based AI technologies is critically important to help us address the skyrocketing demands of neuro-oncology clinical deployments. Here, we provide an overview on the latest advancements in ML techniques for brain tumor radiomic analysis, emphasizing proprietary and public dataset preparation and state-of-the-art ML models for brain tumor diagnosis, classifications (e.g., primary and secondary tumors), discriminations between treatment effects (pseudoprogression, radiation necrosis) and true progression, survival prediction, inflammation, and identification of brain tumor biomarkers. We also compare the key features of ML models in the realm of neuroradiology with ML models employed in other medical imaging fields and discuss open research challenges and directions for future work in this nascent precision medicine area.

Imaging of GBM in the Age of Molecular Markers and MRI Guided Adaptive Radiation Therapy.

Glioblastoma (GBM) continues to be one of the most lethal malignancies and is almost always fatal. In this review article, the role of radiation therapy, systemic therapy, as well as the molecular basis of classifying GBM is described. Technological advances in the treatment of GBM are outlined as well as the diagnostic imaging characteristics of this tumor. In addition, factors that affect prognosis such as differentiating progression from treatment effect is discussed. The role of MRI guided radiation therapy and how this technology may provide a mechanism to improve the care of patients with this disease are described.

Clinical Management of Supratentorial Non-Skull Base Meningiomas.

Supratentorial non-skull base meningiomas are the most common primary central nervous system tumor subtype. An understanding of their pathophysiology, imaging characteristics, and clinical management options will prove of substantial value to the multi-disciplinary team which may be involved in their care. Extensive review of the broad literature on the topic is conducted. Narrowing the scope to meningiomas located in the supratentorial non-skull base anatomic location highlights nuances specific to this tumor subtype. Advances in our understanding of the natural history of the disease and how findings from both molecular pathology and neuroimaging have impacted our understanding are discussed. Clinical management and the rationale underlying specific approaches including observation, surgery, radiation, and investigational systemic therapies is covered in detail. Future directions for probable advances in the near and intermediate term are reviewed.

Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to Characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma.

The concept of tumor field effect implies that cancer is a systemic disease with its impact way beyond the visible tumor confines. For instance, in Glioblastoma (GBM), an aggressive brain tumor, the increase in intracranial pressure due to tumor burden often leads to brain herniation and poor outcomes. Our work is based on the rationale that highly aggressive tumors tend to grow uncontrollably, leading to pronounced biomechanical tissue deformations in the normal parenchyma, which when combined with local morphological differences in the tumor confines on MRI scans, will comprehensively capture tumor field effect. Specifically, we present an integrated MRI-based descriptor, radiomic-Deformation and Textural Heterogeneity (r-DepTH). This descriptor comprises measurements of the subtle perturbations in tissue deformations throughout the surrounding normal parenchyma due to mass effect. This involves non-rigidly aligning the patients' MRI scans to a healthy atlas via diffeomorphic registration. The resulting inverse mapping is used to obtain the deformation field magnitudes in the normal parenchyma. These measurements are then combined with a 3D texture descriptor, Co-occurrence of Local Anisotropic Gradient Orientations (COLLAGE), which captures the morphological heterogeneity and infiltration within the tumor confines, on MRI scans. In this work, we extensively evaluated r-DepTH for survival risk-stratification on a total of 207 GBM cases from 3 different cohorts (Cohort 1 ( n1 = 53 ), Cohort 2 ( n2 = 75 ), and Cohort 3 ( n3 = 79 )), where each of these three cohorts was used as a training set for our model separately, and the other two cohorts were used for testing, independently, for each training experiment. When employing Cohort 1 for training, r-DepTH yielded Concordance indices (C-indices) of 0.7 and 0.65, hazard ratios (HR) and Confidence Intervals (CI) of 10 (6 - 19) and 5 (3 - 8) on Cohorts 2 and 3, respectively. Similarly, training on Cohort 2 yielded C-indices of 0.6 and 0.7, HR and CI of 1 (0.7 - 2) and 3 (2 - 5) on Cohorts 1 and 3, respectively. Finally, training on Cohort 3 yielded C-indices of 0.75 and 0.63, HR and CI of 24 (10 - 57) and 12 (6 - 21) on Cohorts 1 and 2, respectively. Our results show that r-DepTH descriptor may serve as a comprehensive and a robust MRI-based prognostic marker of disease aggressiveness and survival in solid tumors.

Transfer learning for predicting conversion from mild cognitive impairment to dementia of Alzheimer's type based on a three-dimensional convolutional neural network.

Dementia of Alzheimer's type (DAT) is associated with devastating and irreversible cognitive decline. Predicting which patients with mild cognitive impairment (MCI) will progress to DAT is an ongoing challenge in the field. We developed a deep learning model to predict conversion from MCI to DAT. Structural magnetic resonance imaging scans were used as input to a 3-dimensional convolutional neural network. The 3-dimensional convolutional neural network was trained using transfer learning; in the source task, normal control and DAT scans were used to pretrain the model. This pretrained model was then retrained on the target task of classifying which MCI patients converted to DAT. Our model resulted in 82.4% classification accuracy at the target task, outperforming current models in the field. Next, we visualized brain regions that significantly contribute to the prediction of MCI conversion using an occlusion map approach. Contributory regions included the pons, amygdala, and hippocampus. Finally, we showed that the model's prediction value is significantly correlated with rates of change in clinical assessment scores, indicating that the model is able to predict an individual patient's future cognitive decline. This information, in conjunction with the identified anatomical features, will aid in building a personalized therapeutic strategy for individuals with MCI.

Sexually dimorphic radiogenomic models identify distinct imaging and biological pathways that are prognostic of overall survival in glioblastoma.

BACKGROUND: Recent epidemiological studies have suggested that sexual dimorphism influences treatment response and prognostic outcome in glioblastoma (GBM). To this end, we sought to (i) identify distinct sex-specific radiomic phenotypes-from tumor subcompartments (peritumoral edema, enhancing tumor, and necrotic core) using pretreatment MRI scans-that are prognostic of overall survival (OS) in GBMs, and (ii) investigate radiogenomic associations of the MRI-based phenotypes with corresponding transcriptomic data, to identify the signaling pathways that drive sex-specific tumor biology and treatment response in GBM. METHODS: In a retrospective setting, 313 GBM patients (male = 196, female = 117) were curated from multiple institutions for radiomic analysis, where 130 were used for training and independently validated on a cohort of 183 patients. For the radiogenomic analysis, 147 GBM patients (male = 94, female = 53) were used, with 125 patients in training and 22 cases for independent validation. RESULTS: Cox regression models of radiomic features from gadolinium T1-weighted MRI allowed for developing more precise prognostic models, when trained separately on male and female cohorts. Our radiogenomic analysis revealed higher expression of Laws energy features that capture spots and ripple-like patterns (representative of increased heterogeneity) from the enhancing tumor region, as well as aggressive biological processes of cell adhesion and angiogenesis to be more enriched in the "high-risk" group of poor OS in the male population. In contrast, higher expressions of Laws energy features (which detect levels and edges) from the necrotic core with significant involvement of immune related signaling pathways was observed in the "low-risk" group of the female population. CONCLUSIONS: Sexually dimorphic radiogenomic models could help risk-stratify GBM patients for personalized treatment decisions.

Radiological and Clinical Value of 7T MRI for Evaluating 3T-Visible Lesions in Pharmacoresistant Focal Epilepsies.

Objective: The recent FDA approval of the first 7T MRI scanner for clinical diagnostic use in October 2017 will likely increase the utilization of 7T for epilepsy presurgical evaluation. This study aims at accessing the radiological and clinical value of 7T in patients with pharmacoresistant focal epilepsy and 3T-visible lesions. Methods: Patients with pharmacoresistant focal epilepsy were included if they had a lesion on pre-operative standard-of-care 3T MRI and also a 7T research MRI. An epilepsy protocol was used for the acquisition of the 7T MRI. Prospective visual analysis of 7T MRI was performed by an experienced board-certified neuroradiologist and communicated to the patient management team. The clinical significance of the additional 7T findings was assessed by intracranial EEG (ICEEG) ictal onset, surgical resection, post-operative seizure outcome and histopathology. A subset of lesions were demarked with arrows for subsequent, retrospective comparison between 3T and 7T by 7 neuroradiologists using a set of quantitative scales: lesion presence, conspicuity, boundary, gray-white tissue contrast, artifacts, and the most helpful sequence for diagnosis. Conger's kappa for multiple raters was performed for chance-adjusted agreement statistics. Results: A total of 47 patients were included, with the main pathology types of focal cortical dysplasia (FCD), hippocampal sclerosis, periventricular nodular heterotopia (PVNH), tumor and polymicrogyria (PMG). 7T detected additional smaller lesions in 19% (9/47) of patients, who had extensive abnormalities such as PMG and PVNH; however, these additional findings were not necessarily epileptogenic. 3T-7T comparison by the neuroradiologist team showed that lesion conspicuity and lesion boundary were significantly better at 7T (p < 0.001), particularly for FCD, PVNH and PMG. Chance-adjusted agreement was within the fair range for lesion presence, conspicuity and boundary. Gray-white contrast was significantly improved at 7T (p < 0.001). Significantly more artifacts were encountered at 7T (p < 0.001). Significance: For patients with 3T-visible lesions, 7T MRI may better elucidate the extent of multifocal abnormalities such as PVNH and PMG, providing potential targets to improve ICEEG implantation. Patients with FCD, PVNH and PMG would likely benefit the most from 7T due to improved lesion conspicuity and boundary. Pathologies in the antero-inferior temporal regions likely benefit less due to artifacts.

Patients are happy to be informed of their final non-melanoma skin cancer results by post.

During the past year, because of increasing pressure to see more patients, we have started to write to our patients informing them in a letter of their final skin cancer histology results following surgery for non-melanoma skin cancers: basal cell carcinoma and squamous cell carcinoma only. A questionnaire-based study was carried out to assess whether patients were happy to receive information concerning their non-melanoma skin cancer diagnosis in a carefully worded letter. One-hundred fifty patients were involved with a diagnosis of "completely excised non-melanoma skin cancer (NMSC)" that had previously received their final diagnosis by post. Seventy-seven (51.3%) patients responded to the questionnaire. Eighty-seven percent felt that they had been given the cancer diagnosis in an appropriate manner; 90 percent reported that they had understood the explanation about their skin cancer. In addition, 81 percent stated that they had been sufficiently involved in the discussion about their skin cancer and its treatment. Patients gave an average rating of 7.76 (1 = poor and 10 = excellent) for the overall experience of care that they had received. By writing to the patient with their final histology results, we have reduced the number of follow-up appointments without reducing the quality of patient care.