Tumour Size and Overall Survival in a Cohort of Patients with Unifocal Glioblastoma: A Uni- and Multivariable Prognostic Modelling and Resampling Study.

Published models inconsistently associate glioblastoma size with overall survival (OS). This study aimed to investigate the prognostic effect of tumour size in a large cohort of patients diagnosed with GBM and interrogate how sample size and non-linear transformations may impact on the likelihood of finding a prognostic effect. In total, 279 patients with a IDH-wildtype unifocal WHO grade 4 GBM between 2014 and 2020 from a retrospective cohort were included. Uni-/multivariable association between core volume, whole volume (CV and WV), and diameter with OS was assessed with (1) Cox proportional hazard models +/- log transformation and (2) resampling with 1,000,000 repetitions and varying sample size to identify the percentage of models, which showed a significant effect of tumour size. Models adjusted for operation type and a diameter model adjusted for all clinical variables remained significant (p = 0.03). Multivariable resampling increased the significant effects (p < 0.05) of all size variables as sample size increased. Log transformation also had a large effect on the chances of a prognostic effect of WV. For models adjusted for operation type, 19.5% of WV vs. 26.3% log-WV (n = 50) and 69.9% WV and 89.9% log-WV (n = 279) were significant. In this large well-curated cohort, multivariable modelling and resampling suggest tumour volume is prognostic at larger sample sizes and with log transformation for WV.

Brain Re-Irradiation Or Chemotherapy: a phase II randomised trial of re-irradiation and chemotherapy in patients with recurrent glioblastoma (BRIOChe) - protocol for a multi-centre open-label randomised trial.

INTRODUCTION: Glioblastoma (GBM) is the most common adult primary malignant brain tumour. The condition is incurable and, despite aggressive treatment at first presentation, almost all tumours recur after a median of 7 months. The aim of treatment at recurrence is to prolong survival and maintain health-related quality of life (HRQoL). Chemotherapy is typically employed for recurrent GBM, often using nitrosourea-based regimens. However, efficacy is limited, with reported median survivals between 5 and 9 months from recurrence. Although less commonly used in the UK, there is growing evidence that re-irradiation may produce survival outcomes at least similar to nitrosourea-based chemotherapy. However, there remains uncertainty as to the optimum approach and there is a paucity of available data, especially with regards to HRQoL. Brain Re-Irradiation Or Chemotherapy (BRIOChe) aims to assess re-irradiation, as an acceptable treatment option for recurrent IDH-wild-type GBM. METHODS AND ANALYSIS: BRIOChe is a phase II, multi-centre, open-label, randomised trial in patients with recurrent GBM. The trial uses Sargent's three-outcome design and will recruit approximately 55 participants from 10 to 15 UK radiotherapy sites, allocated (2:1) to receive re-irradiation (35 Gy in 10 daily fractions) or nitrosourea-based chemotherapy (up to six, 6-weekly cycles). The primary endpoint is overall survival rate for re-irradiation patients at 9 months. There will be no formal statistical comparison between treatment arms for the decision-making primary analysis. The chemotherapy arm will be used for calibration purposes, to collect concurrent data to aid interpretation of results. Secondary outcomes include HRQoL, dexamethasone requirement, anti-epileptic drug requirement, radiological response, treatment compliance, acute and late toxicities, progression-free survival. ETHICS AND DISSEMINATION: BRIOChe obtained ethical approval from Office for Research Ethics Committees Northern Ireland (reference no. 20/NI/0070). Final trial results will be published in peer-reviewed journals and adhere to the ICMJE guidelines. TRIAL REGISTRATION NUMBER: ISRCTN60524.

Glioblastoma and Radiotherapy: a multi-center AI study for Survival Predictions from MRI (GRASP study).

BACKGROUND: The aim was to predict survival of glioblastoma at eight months after radiotherapy (a period allowing for completing a typical course of adjuvant temozolomide), by applying deep learning to the first brain MRI after radiotherapy completion. METHODS: Retrospective and prospective data were collected from 206 consecutive glioblastoma, IDH-wildtype patients diagnosed between March 2014-February 2022 across 11 UK centers. Models were trained on 158 retrospective patients from three centers. Holdout test sets were retrospective (n=19; internal validation), and prospective (n=29; external validation from eight distinct centers).Neural network branches for T2-weighted and contrast-enhanced T1-weighted inputs were concatenated to predict survival. A non-imaging branch (demographics/MGMT/treatment data) was also combined with the imaging model. We investigated the influence of individual MR sequences; non-imaging features; and weighted dense blocks pretrained for abnormality detection. RESULTS: The imaging model outperformed the non-imaging model in all test sets (area under the receiver-operating characteristic curve, AUC p=0.038) and performed similarly to a combined imaging/non-imaging model (p>0.05). Imaging, non-imaging, and combined models applied to amalgamated test sets gave AUCs of 0.93, 0.79, and 0.91. Initializing the imaging model with pretrained weights from 10,000s of brain MRIs improved performance considerably (amalgamated test sets without pretraining 0.64; p=0.003). CONCLUSIONS: A deep learning model using MRI images after radiotherapy, reliably and accurately determined survival of glioblastoma. The model serves as a prognostic biomarker identifying patients who will not survive beyond a typical course of adjuvant temozolomide, thereby stratifying patients into those who might require early second-line or clinical trial treatment.

Consistency of Radiological Grading of Cervical Foraminal Stenosis.

BACKGROUND: The degree of cervical foraminal stenosis on MRI scans may be measured and categorised using the Kim or modified Kim methods. These grading scales have not previously been validated in a cohort of patients awaiting surgery. OBJECTIVES: To establish the normal foraminal and root diameters as well as the consistency of inter and intra-rater grading using the Kim and modified Kim grading systems in pre-operative surgical patients. METHODS: Asymptomatic cervical nerve roots and foramina demonstrated on the pre-operative MRI scans of adult surgical patients with cervical radiculopathy were measured and categorised by six raters using the Kim and modified Kim grading methods. Repeat "second pass" measurements were made by the same assessors on the same images a minimum of one month later. RESULTS: Foraminal diameters (mm) in asymptomatic foramina were C2/C3 (mean±SD): 4.18±1.44, C3/C4 2.96±1.23, C4/C5 3.02±1.19, C5/C6 3.15±1.33, C6/C7 3.53±1.36, C7/T1 3.93±1.34. Nerve root diameters were C3 3.11±0.87, C4 2.95±0.77, C5 2.56±0.73, C6 2.26±0.76, C7 2.56±0.82, C8 3.83±0.86. Inter-rater consistency was kappa [95% CI]: Kim 0.01 [0.00, 0.03], modified Kim 0.08 [0.05, 0.10]. Intra-rater consistency was kappa [95% CI]: Kim 0.81 [0.77, 0.86], modified Kim 0.69 [0.62, 0.76]. CONCLUSION: There was poor inter-rater consistency but good intra-rater consistency when assessing the severity of foraminal stenosis on axial T2 MRI scans. Foraminal diameter was narrowest at C3/C4 and C4/C5, whereas the smallest root diameter was C5/C6. Volumetric or oblique MR may improve consistency.

Treatment and Response Factors in Muscle Activation during Spinal Manipulation.

The forces applied during a spinal manipulation produce a neuromuscular response in the paraspinal muscles. A systematic evaluation of the factors involved in producing this muscle activity provides a clinical insight. The purpose of this study is to quantify the effect of treatment factors (manipulation sequence and manipulation site) and response factors (muscle layer, muscle location, and muscle side) on the neuromuscular response to spinal manipulation. The surface and indwelling electromyographies of 8 muscle sites were recorded during lumbar side-lying manipulations in 20 asymptomatic participants. The effects of the factors on the number of muscle responses and the muscle activity onset delays were compared using mixed-model linear regressions, effect sizes, and equivalence testing. The treatment factors did not reveal statistical differences between the manipulation sequences (first or second) or manipulation sites (L3 or SI) in the number of muscle responses (p = 0.11, p = 0.28, respectively), or in muscle activity onset delays (p = 0.35 p = 0.35, respectively). There were significantly shorter muscle activity onset delays in the multifidi compared to the superficial muscles (p = 0.02). A small effect size of side (d = 0.44) was observed with significantly greater number of responses (p = 0.02) and shorter muscle activity onset delays (p < 0.001) in the muscles on the left side compared to the right. The location, layer, and side of the neuromuscular responses revealed trends of decreasing muscle response rates and increasing muscle activity onset delays as the distance from the manipulation site increased. These results build on the body of work suggesting that the specificity of manipulation site may not play a role in the neuromuscular response to spinal manipulation-at least within the lumbar spine. In addition, these results demonstrate that multiple manipulations performed in similar areas (L3 and S1) do not change the response significantly, as well as contribute to the clinical understanding that the muscle response rate is higher and with a shorter delay, the closer it is to the manipulation.

Imaging Spectrum of the Developing Glioblastoma: A Cross-Sectional Observation Study.

Glioblastoma (GBM) has the typical radiological appearance (TRA) of a centrally necrotic, peripherally enhancing tumor with surrounding edema. The objective of this study was to determine whether the developing GBM displays a spectrum of imaging changes detectable on routine clinical imaging prior to TRA GBM. Patients with pre-operative imaging diagnosed with GBM (1 January 2014-31 March 2022) were identified from a neuroscience center. The imaging was reviewed by an experienced neuroradiologist. Imaging patterns preceding TRA GBM were analyzed. A total of 76 out of 555 (14%) patients had imaging preceding TRA GBM, 57 had solitary lesions, and 19 had multiple lesions (total = 84 lesions). Here, 83% of the lesions had cortical or cortical/subcortical locations. The earliest imaging features for 84 lesions were T2 hyperintensity/CT low density (n = 18), CT hyperdensity (n = 51), and T2 iso-intensity (n = 15). Lesions initially showing T2 hyperintensity/CT low density later showed T2 iso-intensity. When CT and MRI were available, all CT hyperdense lesions showed T2 iso-intensity, reduced diffusivity, and the following enhancement patterns: nodular 35%, solid 29%, none 26%, and patchy peripheral 10%. The mean time to develop TRA GBM from T2 hyperintensity was 140 days and from CT hyperdensity was 69 days. This research suggests that the developing GBM shows a spectrum of imaging features, progressing through T2 hyperintensity to CT hyperdensity, T2 iso-intensity, reduced diffusivity, and variable enhancement to TRA GBM. Red flags for non-TRA GBM lesions are cortical/subcortical CT hyperdense/T2 iso-intense/low ADC. Future research correlating this imaging spectrum with pathophysiology may provide insight into GBM growth patterns.

Do animal models of brain tumors replicate human peritumoral edema? a systematic literature search.

INTRODUCTION: Brain tumors cause morbidity and mortality in part through peritumoral brain edema. The current main treatment for peritumoral brain edema are corticosteroids. Due to the increased recognition of their side-effect profile, there is growing interest in finding alternatives to steroids but there is little formal study of animal models of peritumoral brain edema. This study aims to summarize the available literature. METHODS: A systematic search was undertaken of 5 literature databases (Medline, Embase, CINAHL, PubMed and the Cochrane Library). The generic strategy was to search for various terms associated with "brain tumors", "brain edema" and "animal models". RESULTS: We identified 603 reports, of which 112 were identified as relevant for full text analysis that studied 114 peritumoral brain edema animal models. We found significant heterogeneity in the species and strain of tumor-bearing animals, tumor implantation method and edema assessment. Most models did not produce appreciable brain edema and did not test for observable manifestations thereof. CONCLUSION: No animal model currently exists that enable the investigation of novel candidates for the treatment of peritumoral brain edema. With current interest in alternative treatments for peritumoral brain edema, there is an unmet need for clinically relevant animal models.

Literature Review of Automated Grading Systems Utilizing MRI for Neuroforaminal Stenosis.

BACKGROUND: Cervical neural foraminal stenosis is a common and debilitating condition affecting people between the ages 40-60. Although it is established that MRI is the best method of scanning the neural foramen, the question remains whether there is a role for three-dimensional MRIs and whether it is possible to develop a computer-aided automated grading system to establish the degree of clinically relevant cervical foraminal stenosis. OBJECTIVE: The study's objective is to conduct a literature review of existing or recently developed automated grading systems for the cervical neural foramen, including volumetric MRI evaluations of the foramen. METHODS: A systematic search of Cochrane Library, Cochrane Clinical Trials, Ovid MEDLINE, EMBASE, CINAHL, ACM Digital Library and Institute of Electrical and Electronics Engineers (IEEE), and Web of Science was performed for reports examining automated systems and volumetric scanning foraminal stenosis published before 31.07.2021. RESULTS: 3971 articles were identified of which 8 were included in the study. The automated grading systems of the neural foramen focus largely on the lumbar spine with elements that may be applicable to the cervical spine. Although there are established studies on the automated grading of the lumbar spine, it is uncertain whether any of these are reproducible in the cervical spine. Visual grading systems for the cervical spine demonstrate good inter-reader reliability between radiologists and clinicians. CONCLUSION: The Park visual grading method shows strong inter-reader reliability across radiologists and clinicians despite the limited data on the correlation with neurological symptoms or surgical outcome. There is scope for further development of an automated grading system for cervical foraminal stenosis to improve the speed and consistency of image interpretation.

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.

Liquid biopsies for early diagnosis of brain tumours: in silico mathematical biomarker modelling.

Brain tumours are the biggest cancer killer in those under 40 and reduce life expectancy more than any other cancer. Blood-based liquid biopsies may aid early diagnosis, prediction and prognosis for brain tumours. It remains unclear whether known blood-based biomarkers, such as glial fibrillary acidic protein (GFAP), have the required sensitivity and selectivity. We have developed a novel in silico model which can be used to assess and compare blood-based liquid biopsies. We focused on GFAP, a putative biomarker for astrocytic tumours and glioblastoma multi-formes (GBMs). In silico modelling was paired with experimental measurement of cell GFAP concentrations and used to predict the tumour volumes and identify key parameters which limit detection. The average GBM volumes of 449 patients at Leeds Teaching Hospitals NHS Trust were also measured and used as a benchmark. Our model predicts that the currently proposed GFAP threshold of 0.12 ng ml-1 may not be suitable for early detection of GBMs, but that lower thresholds may be used. We found that the levels of GFAP in the blood are related to tumour characteristics, such as vasculature damage and rate of necrosis, which are biological markers of tumour aggressiveness. We also demonstrate how these models could be used to provide clinical insight.

Exploratory Analysis of Serial 18F-fluciclovine PET-CT and Multiparametric MRI during Chemoradiation for Glioblastoma.

Anti-1-amino-3-18fluorine-fluorocyclobutane-1-carboxylic acid (18F-fluciclovine) positron emission tomography (PET) shows preferential glioma uptake but there is little data on how uptake correlates with post-contrast T1-weighted (Gd-T1) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) activity during adjuvant treatment. This pilot study aimed to compare 18F-fluciclovine PET, DCE-MRI and Gd-T1 in patients undergoing chemoradiotherapy for glioblastoma (GBM), and in a parallel pre-clinical GBM model, to investigate correlation between 18F-fluciclovine uptake, MRI findings, and tumour biology. 18F-fluciclovine-PET-computed tomography (PET-CT) and MRI including DCE-MRI were acquired before, during and after adjuvant chemoradiotherapy (60 Gy in 30 fractions with temozolomide) in GBM patients. MRI volumes were manually contoured; PET volumes were defined using semi-automatic thresholding. The similarity of the PET and DCE-MRI volumes outside the Gd-T1 volume boundary was measured using the Dice similarity coefficient (DSC). CT-2A tumour-bearing mice underwent MRI and 18F-fluciclovine PET-CT. Post-mortem mice brains underwent immunohistochemistry staining for ASCT2 (amino acid transporter), nestin (stemness) and Ki-67 (proliferation) to assess for biologically active tumour. 6 patients were recruited (GBM 1-6) and grouped according to overall survival (OS)-short survival (GBM-SS, median OS 249 days) and long survival (GBM-LS, median 903 days). For GBM-SS, PET tumour volumes were greater than DCE-MRI, in turn greater than Gd-T1. For GBM-LS, Gd-T1 and DCE-MRI were greater than PET. Tumour-specific 18F-fluciclovine uptake on pre-clinical PET-CT corresponded to immunostaining for Ki-67, nestin and ASCT2. Results suggest volumes of 18F-fluciclovine-PET activity beyond that depicted by DCE-MRI and Gd-T1 are associated with poorer prognosis in patients undergoing chemoradiotherapy for GBM. The pre-clinical model confirmed 18F-fluciclovine uptake reflected biologically active tumour.

Harmonisation of scanner-dependent contrast variations in magnetic resonance imaging for radiation oncology, using style-blind auto-encoders.

Background and purpose: Magnetic Resonance Imaging (MRI) exhibits scanner dependent contrast, which limits generalisability of radiomics and machine-learning for radiation oncology. Current deep-learning harmonisation requires paired data, retraining for new scanners and often suffers from geometry-shift which alters anatomical information. The aim of this study was to investigate style-blind auto-encoders for MRI harmonisation to accommodate unpaired training data, avoid geometry-shift and harmonise data from previously unseen scanners. Materials and methods: A style-blind auto-encoder, using adversarial classification on the latent-space, was designed for MRI harmonisation. The public CC359 T1-w MRI brain dataset includes six scanners (three manufacturers, two field strengths), of which five were used for training. MRI from all six (including one unseen) scanner were harmonised to common contrast. Harmonisation extent was quantified via Kolmogorov-Smirnov testing of residual scanner dependence of 3D radiomic features, and compared to WhiteStripe normalisation. Anatomical content preservation was measured through change in structural similarity index on contrast-cycling (δSSIM). Results: The percentage of radiomics features showing statistically significant scanner-dependence was reduced from 41% (WhiteStripe) to 16% for white matter and from 39% to 27% for grey matter. δSSIM < 0.0025 on harmonisation and de-harmonisation indicated excellent anatomical content preservation. Conclusions: Our method harmonised MRI contrast effectively, preserved critical anatomical details at high fidelity, trained on unpaired data and allowed zero-shot harmonisation. Robust and clinically translatable harmonisation of MRI will enable generalisable radiomic and deep-learning models for a range of applications, including radiation oncology treatment stratification, planning and response monitoring.

Intensity standardization of MRI prior to radiomic feature extraction for artificial intelligence research in glioma-a systematic review.

OBJECTIVES: Radiomics is a promising avenue in non-invasive characterisation of diffuse glioma. Clinical translation is hampered by lack of reproducibility across centres and difficulty in standardising image intensity in MRI datasets. The study aim was to perform a systematic review of different methods of MRI intensity standardisation prior to radiomic feature extraction. METHODS: MEDLINE, EMBASE, and SCOPUS were searched for articles meeting the following eligibility criteria: MRI radiomic studies where one method of intensity normalisation was compared with another or no normalisation, and original research concerning patients diagnosed with diffuse gliomas. Using PRISMA criteria, data were extracted from short-listed studies including number of patients, MRI sequences, validation status, radiomics software, method of segmentation, and intensity standardisation. QUADAS-2 was used for quality appraisal. RESULTS: After duplicate removal, 741 results were returned from database and reference searches and, from these, 12 papers were eligible. Due to a lack of common pre-processing and different analyses, a narrative synthesis was sought. Three different intensity standardisation techniques have been studied: histogram matching (5/12), limiting or rescaling signal intensity (8/12), and deep learning (1/12)-only two papers compared different methods. From these studies, histogram matching produced the more reliable features compared to other methods of altering MRI signal intensity. CONCLUSION: Multiple methods of intensity standardisation have been described in the literature without clear consensus. Further research that directly compares different methods of intensity standardisation on glioma MRI datasets is required. KEY POINTS: • Intensity standardisation is a key pre-processing step in the development of robust radiomic signatures to evaluate diffuse glioma. • A minority of studies compared the impact of two or more methods. • Further research is required to directly compare multiple methods of MRI intensity standardisation on glioma datasets.

Systematic review of radiological cervical foraminal grading systems.

The study design of this paper is systematic review. The purpose of this review is to evaluate the existing radiological grading systems that are used to assess cervical foraminal stenosis. The importance of imaging the cervical spine using CT or MRI in evaluating cervical foraminal stenosis is widely accepted; however, there is no consensus for standardized methodology to assess the compression of the cervical nerve roots. A systematic search of Ovid Medline databases, Embase 1947 to present, Cinahl, Web of Science, Cochrane Library, ISRCTN and WHO international clinical trials was performed for reports of cervical foraminal stenosis published before 01 February 2020. In collaboration with the University of Leeds, a search strategy was developed. A total of 6952 articles were identified with 59 included. Most of the reports involved multiple imaging modalities with standard axial and sagittal imaging used most. The grading themes that came from this systematic review show that the most mature for cervical foraminal stenosis is described by (Kim et al. Korean J Radiol 16:1294, 2015) and (Park et al. Br J Radiol 86:20120515, 2013). Imaging of the cervical nerve root canals is mostly performed using MRI and is reported using subjective terminology. The Park, Kim and Modified Kim systems for classifying the degree of stenosis of the nerve root canal have been described. Clinical application of these scoring systems is limited by their reliance on nonstandard imaging (Park), limited validation against clinical symptoms and surgical outcome data. Oblique fine cut images derived from three dimensional MRI datasets may yield more consistency, better clinical correlation, enhanced surgical decision-making and outcomes.

Volumetric and dosimetric impact of post-surgical MRI-guided radiotherapy for glioblastoma: A pilot study.

Objectives: Glioblastoma (GBM) radiotherapy (RT) target delineation requires MRI, ideally concurrent with CT simulation (pre-RT MRI). Due to limited MRI availability, <72 h post-surgery MRI is commonly used instead. Whilst previous investigations assessed volumetric differences between post-surgical and pre-RT delineations, dosimetric impact remains unknown. We quantify volumetric and dosimetric impact of using post-surgical MRI for GBM target delineation. Methods: Gross tumour volumes (GTVs) for five GBM patients receiving chemo-RT with post-surgical and pre-RT MRIs were delineated by three independent observers. Planning target volumes (PTVs) and RT plans were generated for each GTV. Volumetric and dosimetric differences were assessed through: absolute volumes, volume-distance histograms and dose-volume histogram statistics. Results: Post-surgical MRI delineations had significantly (p < 0.05) larger GTV and PTV volumes (median 16.7 and 64.4 cm3, respectively). Post-surgical RT plans, applied to pre-RT delineations, had significantly decreased (p < 0.01) median PTV doses (ΔD99% = -8.1 Gy and ΔD95% = -2.0 Gy). Median organ-at-risk (OAR) dose increases (brainstem ΔD5% =+0.8, normal brain mean dose =+2.9 and normal brain ΔD10% = 5.3 Gy) were observed. Conclusion: Post-surgical MRI delineation significantly impacted RT planning, with larger normal-appearing tissue volumes irradiated and increased OAR doses, despite a reduced coverage of the pre-RT defined target. Advances in knowledge: We believe this is the first investigation assessing the dosimetric impact of using post-surgical MRI for GBM target delineation. It highlights the potential of significantly degraded RT plans, showing the clinical need for dedicated MRI for GBM RT.

Post-treatment FDG PET-CT in head and neck carcinoma: comparative analysis of 4 qualitative interpretative criteria in a large patient cohort.

There is no consensus regarding optimal interpretative criteria (IC) for Fluorine-18 fluorodeoxyglucose (FDG) Positron Emission Tomography - Computed Tomography (PET-CT) response assessment following (chemo)radiotherapy (CRT) for head and neck squamous cell carcinoma (HNSCC). The aim was to compare accuracy of IC (NI-RADS, Porceddu, Hopkins, Deauville) for predicting loco-regional control and progression free survival (PFS). All patients with histologically confirmed HNSCC treated at a specialist cancer centre with curative-intent non-surgical treatment who underwent baseline and response assessment FDG PET-CT between August 2008 and May 2017 were included. Metabolic response was assessed using 4 different IC harmonised into 4-point scales (complete response, indeterminate, partial response, progressive disease). IC performance metrics (sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy) were compared. Kaplan-Meier and Cox proportional hazards regression analyses were performed for survival analysis. 562 patients were included (397 oropharynx, 53 hypopharynx, 48 larynx, 64 other/unknown primary). 420 patients (75%) received CRT and 142 (25%) had radiotherapy alone. Median follow-up was 26 months (range 3-148). 156 patients (28%) progressed during follow-up. All IC were accurate for prediction of primary tumour (mean NPV 85.0% (84.6-85.3), PPV 85.0% (82.5-92.3), accuracy 84.9% (84.2-86.0)) and nodal outcome (mean NPV 85.6% (84.1-86.6), PPV 94.7% (93.8-95.1), accuracy 86.8% (85.6-88.0)). Number of indeterminate scores for NI-RADS, Porceddu, Deauville and Hopkins were 91, 25, 20, 13 and 55, 70, 18 and 3 for primary tumour and nodes respectively. PPV was significantly reduced for indeterminate uptake across all IC (mean PPV primary tumour 36%, nodes 48%). Survival analyses showed significant differences in PFS between response categories classified by each of the four IC (p <0.001). All four IC have similar diagnostic performance characteristics although Porceddu and Deauville scores offered the best trade off of minimising indeterminate outcomes whilst maintaining a high NPV.

Does manual therapy affect functional and biomechanical outcomes of a sit-to-stand task in a population with low back pain? A preliminary analysis.

Introduction: Manual therapy (MT) hypothetically affects discrepant neuromuscular control and movement observed in populations with low back pain (LBP). Previous studies have demonstrated the limited influence of MT on movement, predominately during range of motion (ROM) testing. It remains unclear if MT affects neuromuscular control in mobility-based activities of daily living (ADLs). The sit-to-stand (STS) task represents a commonly-performed ADL that is used in a variety of clinical settings to assess functional and biomechanical performance. Objective: To determine whether MT affects functional performance and biomechanical performance during a STS task in a population with LBP. Methods: Kinematic data were recorded from the pelvis and thorax of participants with LBP, using an optoelectronic motion capture system as they performed a STS task before and after MT from November 2011 to August 2014. MT for each participant consisted of two high-velocity low-amplitude spinal manipulations, as well as two grade IV mobilizations of the lumbar spine and pelvis targeted toward the third lumbar vertebra and sacroiliac joint in a side-lying position; the order of these treatments was randomized. Pelvis and thorax kinematic data were used to derive the time-varying lumbar angle in the sagittal plane for each STS trial. The difference between the maximum and minimum lumbar angles during the STS trial determined the sagittal ROM that was used as the biomechanical outcome. Time to complete each STS trial was used as a functional measure of performance. Pre-MT and post-MT values for the lumbar sagittal ROM and time to completion were statistically analysed using paired samples t-tests. Results: Data were obtained from 40 participants with 35 useful datasets (NRS = 3.3 ± 1.2; 32.4 ± 9.8 years; 16 females, 19 males). After MT, lumbar sagittal ROM increased by 2.7 ± 5.5 degrees (p = 0.007). Time to complete the STS test decreased by 0.4 ± 0.4 s (p < 0.001). Discussion: These findings provide preliminary evidence that MT might influence the biomechanical and functional performance of an STS task in populations with LBP. The MT intervention in this study involved a combination of spinal manipulations and mobilizations. Future work will expand upon these data as a basis for targeted investigations on the effects of either spinal manipulation and mobilization on neuromuscular control and movement in populations with LBP.

Is 1H-MR spectroscopy useful as a diagnostic aid in MSA-C?

BACKGROUND: Multiple system atrophy (MSA) is a sporadic adult-onset neurodegenerative disease with a cerebellar subtype where ataxic symptoms predominate (MSA-C) associated with autonomic dysfunction and a grave prognosis. The purpose of this analysis was to identify if cerebellar volumetry and MR spectroscopy obtained as part of routine clinical work up of patients with sporadic ataxia differentiates patients with multiple system atrophy- cerebellar type (MSA-C) from those with sporadic adult-onset ataxia of unknown etiology (SAOA) who's condition follows a more benign course. METHODS: Retrospective comparison was undertaken of 20 clinically probable or possible MSA-C patients, 20 age and sex matched patients with SAOA and 20 healthy control subjects. Single voxel 1H-MR spectroscopy of the cerebellar hemisphere and vermis and volumetric analysis of the cerebellum and brainstem were undertaken on baseline scans, comparing all groups. RESULTS: There was significant reduction in NAA/Cr levels in patients with MSA-C when compared to those with ISA (p = 0.005) and healthy controls (p < 0.001) in both the hemisphere and vermis. Brainstem volume was significantly reduced in MSA-C patients compared to SAOA patients (p < 0.001) and healthy controls (p < 0.001). There was no difference in cerebellar volume between MSA-C patients and SAOA patients. CONCLUSION: This paper demonstrates that at presentation, MSA-C patients have a significant reduction of NAA/Cr in the cerebellum and significant decrease in brainstem volume when compared to SAOA and healthy controls. This is the first study to sucessfully show clinical utility of MR spectroscopy of the cerebellum for differentiating MSA-C from patients with SAOA.