Objectives:To investigate whether serum neurofilament light (NfL) concentration is increased in familial Alzheimer disease (FAD), both pre and post symptom onset, and whether it is associated with markers of disease stage and severity.Methods:We recruited 48 individuals from families with PSEN1 or APP mutations to a cross-sectional study: 18 had symptomatic Alzheimer disease (AD) and 30 were asymptomatic but at 50% risk of carrying a mutation. Serum NfL was measured using an ultrasensitive immunoassay on the single molecule array (Simoa) platform. Cognitive testing and MRI were performed; 33 participants had serial MRI, allowing calculation of atrophy rates. Genetic testing established mutation status. A generalized least squares regression model was used to compare serum NfL among symptomatic mutation carriers, presymptomatic carriers, and noncarriers, adjusting for age and sex. Spearman coefficients assessed associations between serum NfL and (1) estimated years to/from symptom onset (EYO), (2) cognitive measures, and (3) MRI measures of atrophy.Results:Nineteen of the asymptomatic participants were mutation carriers (mean EYO −9.6); 11 were noncarriers. Compared with noncarriers, serum NfL concentration was higher in both symptomatic (p < 0.0001) and presymptomatic mutation carriers (p = 0.007). Across all mutation carriers, serum NfL correlated with EYO (ρ = 0.81, p < 0.0001) and multiple cognitive and imaging measures, including Mini-Mental State Examination (ρ = −0.62, p = 0.0001), Clinical Dementia Rating Scale sum of boxes (ρ = 0.79, p < 0.0001), baseline brain volume (ρ = −0.62, p = 0.0002), and whole-brain atrophy rate (ρ = 0.53, p = 0.01).Conclusions:Serum NfL concentration is increased in FAD prior to symptom onset and correlates with measures of disease stage and severity. Serum NfL may thus be a feasible biomarker of early AD-related neurodegeneration.

Objective: To provide a comprehensive description of motor speech function in behavioral variant frontotemporal dementia (bvFTD).Methods: Forty-eight individuals (24 bvFTD and 24 age-and sex-matched healthy controls) provided speech samples. These varied in complexity and thus cognitive demand. Their language was assessed using the Progressive Aphasia Language Scale and verbal fluency tasks. Speech was analyzed perceptually to describe the nature of deficits and acoustically to quantify differences between patients with bvFTD and healthy controls. Cortical thickness and subcortical volume derived from MRI scans were correlated with speech outcomes in patients with bvFTD.Results: Speech of affected individuals was significantly different from that of healthy controls. The speech signature of patients with bvFTD is characterized by a reduced rate (75%) and accuracy (65%) on alternating syllable production tasks, and prosodic deficits including reduced speech rate (45%), prolonged intervals (54%), and use of short phrases (41%). Groups differed on acoustic measures derived from the reading, unprepared monologue, and diadochokinetic tasks but not the days of the week or sustained vowel tasks. Variability of silence length was associated with cortical thickness of the inferior frontal gyrus and insula and speech rate with the precentral gyrus. Conclusions:One in 8 patients presented with moderate speech timing deficits with a further twothirds rated as mild or subclinical. Subtle but measurable deficits in prosody are common in bvFTD and should be considered during disease management. Language function correlated with speech timing measures derived from the unprepared monologue only. Neurology ® 2017;89:837-844 GLOSSARY ALS 5 amyotrophic lateral sclerosis; AMR 5 alternating motion rate; bvFTD 5 behavioral variant of frontotemporal dementia; CBD 5 corticobasal degeneration; CI 5 confidence interval; DDK 5 diadochokinesis; FTD 5 frontotemporal dementia; lvPPA 5 logopenic variant primary progressive aphasia; nvPPA 5 nonfluent variant primary progressive aphasia; PALS 5 Progressive Aphasia Language Scale; PPA 5 primary progressive aphasia; PSP 5 progressive supranuclear palsy; ROI 5 region of interest; SMR 5 sequential motion rate; svPPA 5 semantic variant primary progressive aphasia.

Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer’s disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.

There are numerous challenges to identifying, developing and implementing quantitative techniques for use in clinical radiology, suggesting the need for a common translational pathway. We developed the quantitative neuroradiology initiative (QNI), as a model framework for the technical and clinical validation necessary to embed automated segmentation and other image quantification software into the clinical neuroradiology workflow. We hypothesize that quantification will support reporters with clinically relevant measures contextualized with normative data, increase the precision of longitudinal comparisons, and generate more consistent reporting across levels of radiologists’ experience. The QNI framework comprises the following steps: (1) establishing an area of clinical need and identifying the appropriate proven imaging biomarker(s) for the disease in question; (2) developing a method for automated analysis of these biomarkers, by designing an algorithm and compiling reference data; (3) communicating the results via an intuitive and accessible quantitative report; (4) technically and clinically validating the proposed tool pre-use; (5) integrating the developed analysis pipeline into the clinical reporting workflow; and (6) performing in-use evaluation. We will use current radiology practice in dementia as an example, where radiologists have established visual rating scales to describe the degree and pattern of atrophy they detect. These can be helpful, but are somewhat subjective and coarse classifiers, suffering from floor and ceiling limitations. Meanwhile, several imaging biomarkers relevant to dementia diagnosis and management have been proposed in the literature; some clinically approved radiology software tools exist but in general, these have not undergone rigorous clinical validation in high volume or in tertiary dementia centres. The QNI framework aims to address this need. Quantitative image analysis is developing apace within the research domain. Translating quantitative techniques into the clinical setting presents significant challenges, which must be addressed to meet the increasing demand for accurate, timely and impactful clinical imaging services.

Developments in neuroradiological MRI analysis offer promise in enhancing objectivity and consistency in dementia diagnosis through the use of quantitative volumetric reporting tools (QReports). Translation into clinical settings should follow a structured framework of development, including technical and clinical validation steps. However, published technical and clinical validation of the available commercial/proprietary tools is not always easy to find and pathways for successful integration into the clinical workflow are varied. The quantitative neuroradiology initiative (QNI) framework highlights six necessary steps for the development, validation and integration of quantitative tools in the clinic. In this paper, we reviewed the published evidence regarding regulatory-approved QReports for use in the memory clinic and to what extent this evidence fulfils the steps of the QNI framework. We summarize unbiased technical details of available products in order to increase the transparency of evidence and present the range of reporting tools on the market. Our intention is to assist neuroradiologists in making informed decisions regarding the adoption of these methods in the clinic. For the 17 products identified, 11 companies have published some form of technical validation on their methods, but only 4 have published clinical validation of their QReports in a dementia population. Upon systematically reviewing the published evidence for regulatory-approved QReports in dementia, we concluded that there is a significant evidence gap in the literature regarding clinical validation, workflow integration and in-use evaluation of these tools in dementia MRI diagnosis.

Background In neuroblastoma, genetic alterations in ATRX, define a distinct poor outcome patient subgroup. Despite the need for new therapies, there is a lack of available models and a dearth of pre-clinical research. Methods To evaluate the impact of ATRX loss of function (LoF) in neuroblastoma, we utilized CRISPR-Cas9 gene editing to generate neuroblastoma cell lines isogenic for ATRX . We used these and other models to identify therapeutically exploitable synthetic lethal vulnerabilities associated with ATRX LoF. Findings In isogenic cell lines, we found that ATRX inactivation results in increased DNA damage, homologous recombination repair (HRR) defects and impaired replication fork processivity. In keeping with this, high-throughput compound screening showed selective sensitivity in ATRX mutant cells to multiple PARP inhibitors and the ATM inhibitor KU60019. ATRX mutant cells also showed selective sensitivity to the DNA damaging agents, sapacitabine and irinotecan. HRR deficiency was also seen in the ATRX deleted CHLA-90 cell line, and significant sensitivity demonstrated to olaparib/irinotecan combination therapy in all ATRX LoF models. In-vivo sensitivity to olaparib/irinotecan was seen in ATRX mutant but not wild-type xenografts. Finally, sustained responses to olaparib/irinotecan therapy were seen in an ATRX deleted neuroblastoma patient derived xenograft. Interpretation ATRX LoF results in specific DNA damage repair defects that can be therapeutically exploited. In ATRX LoF models, preclinical sensitivity is demonstrated to olaparib and irinotecan, a combination that can be rapidly translated into the clinic. Funding This work was supported by Christopher's Smile, Neuroblastoma UK, Cancer Research UK, and the Royal Marsden Hospital NIHR BRC.

Objective Hippocampal sclerosis (HS) is the most common cause of drug‐resistant temporal lobe epilepsy, and its accurate detection is important to guide epilepsy surgery. Radiological features of HS include hippocampal volume loss and increased T2 signal, which can both be quantified to help improve detection. In this work, we extend these quantitative methods to generate cross‐sectional area and T2 profiles along the hippocampal long axis to improve the localization of hippocampal abnormalities. Methods T1‐weighted and T2 relaxometry data from 69 HS patients (32 left, 32 right, 5 bilateral) and 111 healthy controls were acquired on a 3‐T magnetic resonance imaging (MRI) scanner. Automated hippocampal segmentation and T2 relaxometry were performed and used to calculate whole‐hippocampal volumes and to estimate quantitative T2 (qT2) values. By generating a group template from the controls, and aligning this so that the hippocampal long axes were along the anterior‐posterior axis, we were able to calculate hippocampal cross‐sectional area and qT2 by a slicewise method to localize any volume loss or T2 hyperintensity. Individual patient profiles were compared with normative data generated from the healthy controls. Results Profiling of hippocampal volumetric and qT2 data could be performed automatically and reproducibly. HS patients commonly showed widespread decreases in volume and increases in T2 along the length of the affected hippocampus, and focal changes may also be identified. Patterns of atrophy and T2 increase in the left hippocampus were similar between left, right, and bilateral HS. These profiles have potential to distinguish between sclerosis affecting volume and qT2 in the whole or parts of the hippocampus, and may aid the radiological diagnosis in uncertain cases or cases with subtle or focal abnormalities where standard whole‐hippocampal measurements yield normal values. Significance Hippocampal profiling of volumetry and qT2 values can help spatially localize hippocampal MRI abnormalities and work toward improved sensitivity of subtle focal lesions.

Objectives We examined whether providing a quantitative report (QReport) of regional brain volumes improves radiologists’ accuracy and confidence in detecting volume loss, and in differentiating Alzheimer’s disease (AD) and frontotemporal dementia (FTD), compared with visual assessment alone. Methods Our forced-choice multi-rater clinical accuracy study used MRI from 16 AD patients, 14 FTD patients, and 15 healthy controls; age range 52–81. Our QReport was presented to raters with regional grey matter volumes plotted as percentiles against data from a normative population (n = 461). Nine raters with varying radiological experience (3 each: consultants, registrars, ‘non-clinical image analysts’) assessed each case twice (with and without the QReport). Raters were blinded to clinical and demographic information; they classified scans as ‘normal’ or ‘abnormal’ and if ‘abnormal’ as ‘AD’ or ‘FTD’. Results The QReport improved sensitivity for detecting volume loss and AD across all raters combined (p = 0.015* and p = 0.002*, respectively). Only the consultant group’s accuracy increased significantly when using the QReport (p = 0.02*). Overall, raters’ agreement (Cohen’s κ) with the ‘gold standard’ was not significantly affected by the QReport; only the consultant group improved significantly (κs 0.41➔0.55, p = 0.04*). Cronbach’s alpha for interrater agreement improved from 0.886 to 0.925, corresponding to an improvement from ‘good’ to ‘excellent’. Conclusion Our QReport referencing single-subject results to normative data alongside visual assessment improved sensitivity, accuracy, and interrater agreement for detecting volume loss. The QReport was most effective in the consultants, suggesting that experience is needed to fully benefit from the additional information provided by quantitative analyses. Key Points • The use of quantitative report alongside routine visual MRI assessment improves sensitivity and accuracy for detecting volume loss and AD vs visual assessment alone. • Consultant neuroradiologists’ assessment accuracy and agreement (kappa scores) significantly improved with the use of quantitative atrophy reports. • First multi-rater radiological clinical evaluation of visual quantitative MRI atrophy report for use as a diagnostic aid in dementia.