Anatomy-based correction of kidney PVE on [Formula: see text] SPECT images.

BACKGROUND: In peptide receptor radionuclide therapy (PRRT), accurate quantification of kidney activity on post-treatment SPECT images paves the way for patient-specific treatment. Due to the limited spatial resolution of SPECT images, the partial volume effect (PVE) is a significant source of quantitative bias. In this study, we aimed to evaluate the performance and robustness of anatomy-based partial volume correction (PVC) algorithms to recover the accurate activity concentration of realistic kidney geometries on [Formula: see text]Lu SPECT images recorded under clinical conditions. METHODS: Based on the CT scan data from patients, three sets of fillable kidneys with surface-to-volume (S:V) ratios ranging from 1.5 to 2.8 cm-1, were 3D printed and attached in a IEC phantom. Quantitative [Formula: see text]Lu SPECT/CT acquisitions were performed on a GE Discovery NM CT 870 DR camera for the three modified IEC phantoms and for 6 different Target-To-Background ratios (TBRs: 2, 4, 6, 8, 10, 12). Two region-based (GTM and Labbé) and five voxel-based (GTM + MTC, Labbé + MTC, GTM + RBV, Labbé + RBV and IY) methods were evaluated with this data set. Additionally, the robustness of PVC methods to Point Spread Function (PSF) discrepancies, registration mismatches and background heterogeneity was evaluated. RESULTS: Without PVC, the average kidney RCs across all TBRs ranged from 0.66 ± 0.05 (smallest kidney) to 0.80 ± 0.03 (largest kidney). For a TBR of 12, all anatomy-based method were able to recover the kidneys activity concentration with an error < 6%. All methods result in a comparable decline in RC restoration with decreasing TBR. The Labbé method was the most robust against PSF and registration mismatches but was also the most sensitive to background heterogeneity. Among the voxel-based methods, MTC images were less uniform than RBV and IY images at the outer edge of high uptake areas (kidneys and spheres). CONCLUSION: Anatomy-based PVE correction allows for accurate SPECT quantification of the [Formula: see text]Lu activity concentration with realistic kidney geometries. Combined with recent progress in deep-learning algorithms for automatic anatomic segmentation of whole-body CT, these methods could be of particular interest for a fully automated OAR dosimetry pipeline with PVE correction.

Does Spinocerebellar ataxia 27B mimic cerebellar multiple system atrophy?

BACKGROUND: Whether spinocerebellar ataxia 27B (SCA27B) may present as a cerebellar multiple system atrophy (MSA-C) mimic remains undetermined. OBJECTIVES: To assess the prevalence of FGF14 (GAA)≥250 expansions in patients with MSA-C, to compare SCA27B and MSA-C clinical presentation and natural history. METHODS: FGF14 expansion screening combined with longitudinal deep-phenotyping in a prospective cohort of 195 patients with sporadic late-onset cerebellar ataxia. RESULTS: After a mean disease duration of 6.4 years, 111 patients were not meeting criteria for MSA-C while 24 and 60 patients had a final diagnosis of possible and probable MSA-C, respectively. 16 patients carried an FGF14 (GAA)≥250 expansion in the group not meeting MSA-C criteria (14.4%), 3 patients in the possible MSA-C group (12.5%), but none among probable MSA-C cases. SCA27B patients were evolving more slowly than probable MSA-C patients. CONCLUSIONS: FGF14 (GAA)≥250 expansion may account for MSA look-alike cases and should be screened among slow progressors.

PiDeeL: metabolic pathway-informed deep learning model for survival analysis and pathological classification of gliomas.

MOTIVATION: Online assessment of tumor characteristics during surgery is important and has the potential to establish an intra-operative surgeon feedback mechanism. With the availability of such feedback, surgeons could decide to be more liberal or conservative regarding the resection of the tumor. While there are methods to perform metabolomics-based tumor pathology prediction, their model complexity predictive performance is limited by the small dataset sizes. Furthermore, the information conveyed by the feedback provided on the tumor tissue could be improved both in terms of content and accuracy. RESULTS: In this study, we propose a metabolic pathway-informed deep learning model (PiDeeL) to perform survival analysis and pathology assessment based on metabolite concentrations. We show that incorporating pathway information into the model architecture substantially reduces parameter complexity and achieves better survival analysis and pathological classification performance. With these design decisions, we show that PiDeeL improves tumor pathology prediction performance of the state-of-the-art in terms of the Area Under the ROC Curve by 3.38% and the Area Under the Precision-Recall Curve by 4.06%. Similarly, with respect to the time-dependent concordance index (c-index), PiDeeL achieves better survival analysis performance (improvement of 4.3%) when compared to the state-of-the-art. Moreover, we show that importance analyses performed on input metabolite features as well as pathway-specific neurons of PiDeeL provide insights into tumor metabolism. We foresee that the use of this model in the surgery room will help surgeons adjust the surgery plan on the fly and will result in better prognosis estimates tailored to surgical procedures. AVAILABILITY AND IMPLEMENTATION: The code is released at https://github.com/ciceklab/PiDeeL. The data used in this study are released at https://zenodo.org/record/7228791.

Natural History and Phenotypic Spectrum of GAA-FGF14 Sporadic Late-Onset Cerebellar Ataxia (SCA27B).

BACKGROUND: Heterozygous GAA expansions in the FGF14 gene have been related to autosomal dominant cerebellar ataxia (SCA27B-MIM:620174). Whether they represent a common cause of sporadic late-onset cerebellar ataxia (SLOCA) remains to be established. OBJECTIVES: To estimate the prevalence, characterize the phenotypic spectrum, identify discriminative features, and model longitudinal progression of SCA27B in a prospective cohort of SLOCA patients. METHODS: FGF14 expansions screening combined with longitudinal deep-phenotyping in a prospective cohort of 118 SLOCA patients (onset >40 years of age, no family history of cerebellar ataxia) without a definite diagnosis. RESULTS: Prevalence of SCA27B was 12.7% (15/118). Higher age of onset, higher Spinocerebellar Degeneration Functional Score, presence of vertigo, diplopia, nystagmus, orthostatic hypotension absence, and sensorimotor neuropathy were significantly associated with SCA27B. Ataxia progression was ≈0.4 points per year on the Scale for Assessment and Rating of Ataxia. CONCLUSIONS: FGF14 expansion is a major cause of SLOCA. Our natural history data will inform future FGF14 clinical trials. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

18FDG PET/CT Tumoral and Neurologic Therapeutic Response in a Case of Anti-GABABR Paraneoplastic Limbic Encephalitis.

ABSTRACT: A 70-year-old man with a history of small cell lung carcinoma 2 years earlier was addressed for the suspicion of a paraneoplastic limbic encephalitis. Brain 18FDG PET/CT revealed a bilateral amygdalian and hippocampal hypermetabolism, confirming a limbic encephalitis, and concurrent whole-body 18FDG PET/CT showed a small cell lung carcinoma plurifocal metastatic recurrence, consistent with a paraneoplastic limbic encephalitis. 18FDG PET/CT follow-up under chemotherapy revealed an almost complete normalization of brain metabolism and a partial metabolic response of the metastatic recurrence, consistent with the good clinical neurological evolution of the patient. This case highlights the clinical-metabolic imaging correlation in paraneoplastic limbic encephalitis.

68Ga-DOTATOC PET in Extracranial Hepatic and Bone Metastasis of Atypical Refractory Meningioma: A Case Report.

ABSTRACT: A falcine meningioma was diagnosed in a 66-year-old woman and was treated by surgery and 2 times by radiotherapy during 9 years of follow-up with the diagnosis of atypical meningioma. Three months after the last radiotherapy, incidental liver lesions were detected on chest CT realized for suspected pneumonia. In view of the predisposing factors for meningioma metastases, 68Ga-DOTATOC hepatic and cerebral PET/MRI was performed and completed by total body PET/CT demonstrating a somatostatin receptor 2 overexpression of the multiple liver lesions and several bone lesions. Biopsies from the liver and iliac bone confirmed the metastatic origin of meningioma.

Sequential Brain Perfusion Findings in a Case of Osmotic Demyelination Syndrome.

ABSTRACT: A 60-year-old man with chronic alcoholism for 30 years was admitted to the hospital for an acute alcoholic syndrome with global confusional state, cognitive disorders, and ataxia. MRI detected bilateral mamillary bodies T 2 hypersignal related to Wernicke encephalopathy. It was treated by oral thiamine supplementation with clinical improvement. Two months later, he was rehospitalized for rapidly progressive dementia symptoms. Brain perfusion scintigraphy revealed pontine hyperperfusion and right hippocampal hypoperfusion. One month after IV thiamine supplementation, brain perfusion scintigraphy showed normalization of perfusion abnormalities in the pons and right hippocampus, leading to the diagnosis of alcoholic-related osmotic demyelination syndrome.

Hypoxia-mediated stabilization of HIF1A in prostatic intraepithelial neoplasia promotes cell plasticity and malignant progression.

Prostate cancer (PCa) is a leading cause of cancer-related deaths. The slow evolution of precancerous lesions to malignant tumors provides a broad time frame for preventing PCa. To characterize prostatic intraepithelial neoplasia (PIN) progression, we conducted longitudinal studies on Pten(i)pe-/- mice that recapitulate prostate carcinogenesis in humans. We found that early PINs are hypoxic and that hypoxia-inducible factor 1 alpha (HIF1A) signaling is activated in luminal cells, thus enhancing malignant progression. Luminal HIF1A dampens immune surveillance and drives luminal plasticity, leading to the emergence of cells that overexpress Transglutaminase 2 (TGM2) and have impaired androgen signaling. Elevated TGM2 levels in patients with PCa are associated with shortened progression-free survival after prostatectomy. Last, we show that pharmacologically inhibiting HIF1A impairs cell proliferation and induces apoptosis in PINs. Therefore, our study demonstrates that HIF1A is a target for PCa prevention and that TGM2 is a promising prognostic biomarker of early relapse after prostatectomy.

18 F-FDOPA and MRI Findings in a Case of Multiple Sclerosis.

ABSTRACT: A 39-year-old woman with no significant medical history underwent a brain MRI because of headaches and dysarthria having lasted 3 weeks. A tumor lesion was suspected. PET imaging was decided. She underwent FDG and FDOPA PET, leading to the diagnosis of low-grade glioma. Three months later, a new imaging assessment was organized. It showed a decrease in the hypermetabolism of the lesion and the appearance of a second lesion questioning the diagnosis. Further assessment led to the conclusion of a multiple sclerosis. This case illustrates that FDOPA PET uptake should be interpreted with caution in patients with suspected primary brain tumors.

Evolution of Neuroimaging Findings in Severe COVID-19 Patients with Initial Neurological Impairment: An Observational Study.

BACKGROUND AND OBJECTIVES: Cerebral complications related to the COVID-19 were documented by brain MRIs during the acute phase. The purpose of the present study was to describe the evolution of these neuroimaging findings (MRI and FDG-PET/CT) and describe the neurocognitive outcomes of these patients. METHODS: During the first wave of the COVID-19 outbreak between 1 March and 31 May 2020, 112 consecutive COVID-19 patients with neurologic manifestations underwent a brain MRI at Strasbourg University hospitals. After recovery, during follow-up, of these 112 patients, 31 (initially hospitalized in intensive care units) underwent additional imaging studies (at least one brain MRI). RESULTS: Twenty-three men (74%) and eight women (26%) with a mean age of 61 years (range: 18-79) were included. Leptomeningeal enhancement, diffuse brain microhemorrhages, acute ischemic strokes, suspicion of cerebral vasculitis, and acute inflammatory demyelinating lesions were described on the initial brain MRIs. During follow-up, the evolution of the leptomeningeal enhancement was discordant, and the cerebral microhemorrhages were stable. We observed normalization of the vessel walls in all patients suspected of cerebral vasculitis. Four patients (13%) demonstrated new complications during follow-up (ischemic strokes, hypoglossal neuritis, marked increase in the white matter FLAIR hyperintensities with presumed vascular origin, and one suspected case of cerebral vasculitis). Concerning the grey matter volumetry, we observed a loss of volume of 3.2% during an average period of approximately five months. During follow-up, the more frequent FDG-PET/CT findings were hypometabolism in temporal and insular regions. CONCLUSION: A minority of initially severe COVID-19 patients demonstrated new complications on their brain MRIs during follow-up after recovery.

Targeted metabolomics analyses for brain tumor margin assessment during surgery.

MOTIVATION: Identification and removal of micro-scale residual tumor tissue during brain tumor surgery are key for survival in glioma patients. For this goal, High-Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HRMAS NMR) spectroscopy-based assessment of tumor margins during surgery has been an effective method. However, the time required for metabolite quantification and the need for human experts such as a pathologist to be present during surgery are major bottlenecks of this technique. While machine learning techniques that analyze the NMR spectrum in an untargeted manner (i.e. using the full raw signal) have been shown to effectively automate this feedback mechanism, high dimensional and noisy structure of the NMR signal limits the attained performance. RESULTS: In this study, we show that identifying informative regions in the HRMAS NMR spectrum and using them for tumor margin assessment improves the prediction power. We use the spectra normalized with the ERETIC (electronic reference to access in vivo concentrations) method which uses an external reference signal to calibrate the HRMAS NMR spectrum. We train models to predict quantities of metabolites from annotated regions of this spectrum. Using these predictions for tumor margin assessment provides performance improvements up to 4.6% the Area Under the ROC Curve (AUC-ROC) and 2.8% the Area Under the Precision-Recall Curve (AUC-PR). We validate the importance of various tumor biomarkers and identify a novel region between 7.97 ppm and 8.09 ppm as a new candidate for a glioma biomarker. AVAILABILITY AND IMPLEMENTATION: The code is released at https://github.com/ciceklab/targeted_brain_tumor_margin_assessment. The data underlying this article are available in Zenodo, at https://doi.org/10.5281/zenodo.5781769. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Metabolomic Impact of Lidocaine on a Triple Negative Breast Cancer Cell Line.

Background: Metabolomics and onco-anesthesia are two emerging research fields in oncology. Metabolomics (metabolites analysis) is a new diagnostic and prognostic tool that can also be used for predicting the therapeutic or toxic responses to anticancer treatments. Onco-anesthesia studies assess the impact of anesthesia on disease-free and overall survival after cancer surgery. It has been shown that local anesthetics (LA), particularly lidocaine (LIDO), exert antitumor properties both in vitro and in vivo and may alter the biologic fingerprints of cancer cells. As LA are known to impair mitochondrial bioenergetics and byproducts, the aim of the present study was to assess the impact of LIDO on metabolomic profile of a breast cancer cell line. Methods: Breast cancer MDA-MB-231 cells were exposed for 4 h to 0.5 mM LIDO or vehicle (n = 4). The metabolomic fingerprint was characterized by high resolution magic angle spinning NMR spectroscopy (HRMAS). The multivariate technique using the Algorithm to Determine Expected Metabolite Level Alteration (ADEMA) (Cicek et al., PLoS Comput. Biol., 2013, 9, e1002859), based on mutual information to identify expected metabolite level changes with respect to a specific condition, was used to determine the metabolites variations caused by LIDO. Results: LIDO modulates cell metabolites levels. Several pathways, including glutaminolysis, choline, phosphocholine and total choline syntheses were significantly downregulated in the LIDO group. Discussion: This is the first study assessing the impact of LIDO on metabolomic fingerprint of breast cancer cells. Among pathways downregulated by LIDO, many metabolites are reported to be associated with adverse prognosis when present at a high titer in breast cancer patients. These results fit with the antitumor properties of LIDO and suggest its impact on metabolomics profile of cancer cells. These effects of LIDO are of clinical significance because it is widely used for local anesthesia with cutaneous infiltration during percutaneous tumor biopsy. Future in vitro and preclinical studies are necessary to assess whether metabolomics analysis requires modification of local anesthetic techniques during tumor biopsy.

Progression of Nigrostriatal Denervation in Cerebellar Multiple System Atrophy: A Prospective Study.

OBJECTIVES: Nigrostriatal dopaminergic denervation (NSDD) remains poorly characterized in cerebellar multiple system atrophy (MSA-C). We aimed to study NSDD progression in MSA-C and evaluate the capacity for [123I]-FP-CIT-SPECT and parkinsonism to differentiate MSA-C from idiopathic late-onset cerebellar ataxia (ILOCA). METHODS: We included 85 patients successively referred for sporadic late-onset cerebellar ataxia (SLOCA). Every 6 months, SARA, UPDRS-III, and SDFS scores were measured, and MSA-C diagnostic criteria were searched for. Striatal/occipital dopaminergic binding ratio was evaluated every year with [123I]-FP-CIT-scintigraphy. RESULTS: After a mean follow-up of 33.8 months, 33 patients had probable MSA-C, 8 possible MSA-C, and 44 ILOCA. SARA and UPDRS-III scores worsened faster in the probable MSA-C group (p < 0.01) compared with the ILOCA group. The baseline striatal/occipital ratio was lower (2.3 vs 2.97; p < 0.01) and more decreasing among patients with probable MSA-C (p < 0.01). Weighting dysautonomia and parkinsonism and/or NSDD as additional and principal criterion, respectively, in the possible MSA-C diagnostic criteria slightly improved their specificity (81.6% vs 76.9%) and sensitivity (77.8% vs 72.2%) to predict a final diagnosis of probable MSA-C. DISCUSSION: Rapid symptom worsening and NSDD existence and progression predict MSA-C among patients with SLOCA. Parkinsonism, NSDD, and dysautonomia should be considered equivalent for possible MSA-C diagnosis.

Stroke-related restless legs syndrome: Clinical and anatomo-functional characterization of an emerging entity.

BACKGROUND AND PURPOSE: Stroke-related restless legs syndrome (sRLS) secondary to ischemic lesions is an emerging entity and an interesting condition, but there are limited available data to help us further understand its underlying pathways. In this study, we characterized sRLS clinically, neuroanatomically and functionally. METHODS: Consecutive patients hospitalized in the Stroke Unit of the University Hospital of Strasbourg were assessed clinically and electrophysiologically for sRLS characteristics. They underwent brain magnetic resonance imaging for the neuroanatomical study of involved structures, and received functional evaluations with 18 F-FDG (2-deoxy-2-[fluorine-18]fluoro-D-glucose) positron emission tomography (PET) for glucose consumption, 123 I-FP-CIT ([123]I-2beta-carbometoxy-3beta-[4-iodophenyl]-N-[3-fluoropropyl]nortropane) single-photon emission computed tomography for dopamine reuptake and PET with 18 F-FDOPA ((3,4-dihydroxy-6-[18]F-fluoro-l-phenylalanine) for presynaptic dopaminergic synthesis. RESULTS: Sixteen patients with sRLS, eight women and eight men, aged 41-81 years, were included. The clinical characteristics of sRLS and idiopathic RLS were similar. Most patients presented with bilateral and symmetric de novo RLS. Eight patients had infarction in the lenticulostriate area (middle cerebral artery and internal carotid arteria). The body of the caudate nucleus was most commonly affected. Seven patients had sRLS secondary to ventral brainstem infarction (perforating branches of the basilar arteria) affecting the pons in six patients and the medulla oblongata in one patient. Both the corticospinal tract and the cortico-pontocerebellar fibres were lesioned in all patients with brainstem stroke. One patient had infarction in the left posterior cerebellar vermis and occipital area (posterior cerebral artery and superior cerebellar artery). Isotopic explorations showed a significantly increased dopaminergic tone in the striatum ipsilateral to lenticulostriate infarction. Dopamine fixation was normal in patients with stroke outside of the lenticulostriate area. CONCLUSIONS: Clinicians should be aware of the characteristics of sRLS for the appropriate diagnosis and treatment of this condition.

Inferior Colliculus's Hypermetabolism: A New Finding on Brain FDG PET and Perfusion MRI in a Patient With COVID-19.

ABSTRACT: We present the case of a 64-year-old man presenting an episode of confusion during SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection with a positive oropharyngeal swab polymerase chain reaction test. He was hospitalized for dyspnea related to pneumonia demonstrated on chest CT. FDG PET performed after the confusion phase, but still in the COVID-19 (coronavirus disease 2019)-positive phase, showed high glucose metabolism of the inferior colliculi. Morphological MRI was normal. The first-pass perfusion MRI shows hyperperfusion of the inferior colliculi, corresponding to FDG PET hypermetabolism.

Three Different FDG Patterns in Periventricular Nodular Heterotopia Correlated to Video Stereoelectroencephalography.

ABSTRACT: A 40-year-old woman with a drug-resistant focal epilepsy underwent cerebral FDG PET in phase 1 presurgical epilepsy study. MRI essentially showed multiple periventricular nodular heterotopias. The stereoelectroencephalography coupled to MRI and FDG PET helped to define the anatomofunctional correlation of the epileptogenic zone network. This procedure brought to light 3 distinct patterns of FDG consumption, corresponding to different anatomoelectroclinical features. This pattern was already found in a previous FDG PET reflecting a "stable" permanent intralesional intercritical stereoelectroencephalography activity, an electrical "signature" of the lesion. Finally, functional imaging improved thermocoagulation in this patient and emphasized the use of FDG in drug-resistant epilepsy.

Panton-Valentine Leucocidin of Staphylococcus aureus Induces Oxidative Stress and Neurotransmitter Imbalance in a Retinal Explant Model.

Purpose: Endophthalmitis models have reported the virulent role of Panton-Valentine leucocidin (PVL) secreted by Staphylococcus aureus on the retina. PVL targets retinal ganglion cells (RGCs), expressing PVL membrane receptor C5aR. Interactions between PVL and retinal cells lead to glial activation, retinal inflammation, and apoptosis. In this study, we explored oxidative stress and retinal neurotransmitters in a rabbit retinal explant model incubated with PVL. Methods: Reactive oxygen species (ROS) production in RGCs has been assessed with fluorescent probes and immunohistochemistry. Nuclear magnetic resonance (NMR) spectroscopy quantified retinal concentrations of antioxidant molecules and neurotransmitters, and concentrations of neurotransmitters released in the culture medium. Quantifying the expression of some pro-inflammatory and anti-inflammatory factors was performed using RT-qPCR. Results: PVL induced a mitochondrial ROS production in RGCs after four hours' incubation with the toxin. Enzymatic sources of ROS, involving nicotinamide adenine dinucleotide phosphate-oxidase and xanthine oxidase, were also activated after four hours in PVL-treated retinal explants. Retinal antioxidants defenses, that is, glutathione, ascorbate and taurine, decreased after two hours' incubation with PVL. Glutamate retinal concentrations and glutamate release in the culture medium remained unaltered in PVL-treated retinas. GABA, glycine, and acetylcholine (Ach) retinal concentrations decreased after PVL treatment. Glycine release in the culture medium decreased, whereas Ach release increased after PVL treatment. Expression of proinflammatory and anti-inflammatory cytokines remained unchanged in PVL-treated explants. Conclusions: PVL activates oxidative pathways and alters neurotransmitter retinal concentrations and release, supporting the hypothesis that PVL could induce a neurogenic inflammation in the retina.

Effects of Warmed and Humidified CO2 Surgical Site Insufflation in a Novel Experimental Model of Magnetic Compression Colonic Anastomosis.

Background. Pneumoperitoneum insufflation with warmed and humidified carbon dioxide (WH-CO2) can prevent heat loss and increase tissue oxygenation. We evaluated the impact of localized WH-CO2 insufflation on the anastomotic healing process. Methods. Sixty male Wistar rats were randomized: Group 1 (control, n = 12), Group 2 (cold and dry CO2, CD-CO2, n = 24), and Group 3 (WH-CO2, n = 24). A magnetic compression side-to-side colonic anastomosis was performed under 60-minute local abdominal CO2 flow insufflation. Animal temperature was recorded. IL-1, IL-6, and CRP levels were assessed before and after insufflation and on postoperative day (POD) 7 and POD 10. Endoscopic follow-up was performed on POD 7 and POD 10. A burst pressure (BP) test of the specimen was performed on POD 10, and histopathological analysis was then performed. Metabolomics of the anastomotic site was determined. Results. Seven rats (5 CD-CO2 group, 1 WH-CO2 group, and 1 control group) died during the survival period. Necropsies revealed intestinal occlusions (n = 2). One additional rat from the CD-CO2 group was sacrificed on POD 7 due to intestinal perforation. The postoperative course was uneventful in the remaining cases. There was no difference in BP among the groups. Thermal monitoring confirmed that WH-CO2 insufflation was effective to reduce heat loss. IL-1 levels were statistically and significantly lower on POD 10 in the WH-CO2 group than the CD-CO2 group but not lower than the control group. CRP levels, histopathology, and metabolomics did not show any difference between the 3 groups. Conclusions. WH-CO2 was effective to preserve core temperature. However, it did not improve anastomotic healing.

Machine learning assisted intraoperative assessment of brain tumor margins using HRMAS NMR spectroscopy.

Complete resection of the tumor is important for survival in glioma patients. Even if the gross total resection was achieved, left-over micro-scale tissue in the excision cavity risks recurrence. High Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HRMAS NMR) technique can distinguish healthy and malign tissue efficiently using peak intensities of biomarker metabolites. The method is fast, sensitive and can work with small and unprocessed samples, which makes it a good fit for real-time analysis during surgery. However, only a targeted analysis for the existence of known tumor biomarkers can be made and this requires a technician with chemistry background, and a pathologist with knowledge on tumor metabolism to be present during surgery. Here, we show that we can accurately perform this analysis in real-time and can analyze the full spectrum in an untargeted fashion using machine learning. We work on a new and large HRMAS NMR dataset of glioma and control samples (n = 565), which are also labeled with a quantitative pathology analysis. Our results show that a random forest based approach can distinguish samples with tumor cells and controls accurately and effectively with a median AUC of 85.6% and AUPR of 93.4%. We also show that we can further distinguish benign and malignant samples with a median AUC of 87.1% and AUPR of 96.1%. We analyze the feature (peak) importance for classification to interpret the results of the classifier. We validate that known malignancy biomarkers such as creatine and 2-hydroxyglutarate play an important role in distinguishing tumor and normal cells and suggest new biomarker regions. The code is released at http://github.com/ciceklab/HRMAS_NC.