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This protocol outlines a prospective study aimed at enhancing the diagnosis and monitoring of brain tumors through advanced non-invasive imaging techniques. While magnetic resonance imaging (MRI) is a cornerstone of brain tumor diagnostics, it often lacks the specificity required for definitive diagnosis, which typically relies on invasive tissue sampling. To address this, the study will evaluate advanced MRI techniques—such as perfusion, diffusion, blood-oxygen-level-dependent imaging, magnetic resonance spectroscopy, and amide proton transfer-weighted imaging— that offer valuable physiological and molecular insights, beyond conventional anatomical imaging. Despite their potential, clinical adoption of these methods remains limited. MRI also plays a central role in treatment response assessment and follow-up, yet conventional anatomical sequences may not detect early physiological changes or differentiate true progression from pseudoprogression. Advanced imaging methods have shown promise in addressing these limitations, and predictive models for recurrence risk could further personalize treatment strategies. In this study, imaging will be performed using a standardized 3T MRI scanner at multiple time points: preoperatively, before radiotherapy, during treatment, and throughout follow-up. This protocol aims to establish a multiparametric imaging framework capable of capturing dynamic physiological and molecular changes in brain tumors. The primary goal is to determine whether combining advanced sequences improves diagnostic accuracy compared to conventional MRI, using histopathology as the reference. Secondary objectives include predicting treatment response, distinguishing true progression from pseudoprogression, and modeling spatial recurrence risk based on quantitative imaging biomarkers. We hypothesize that a multiparametric imaging approach will, enable earlier detection of tumor progression and support more precise, individualized treatment decisions.

The influence of external conditions on the dissolution of minerals within inorganic sidestreams, such as steel slags, is a critical factor when considering their utilization pathways. This study addresses the aqueous dissolution characteristics of electric arc furnace slag (EAFS) and one of its main crystal phases – brownmillerite (BM), and delves into the impact of high energy photon irradiation (HEPI). The untreated forms of EAFS and BM were exposed to HEPIs using Cs-137 isotope (0.662 MeV, 250 Gy) and medical linear accelerator (10 MeV, 52 kGy) for 72 h and 16 h, respectively. The impact of HEPIs on dissolution was quantified based on batch dissolution experiments in water under ambient conditions with a solid-to-liquid ratio of 1:100 g/mL. Afterward, a systematic characterization series is conducted to understand structural changes, surface alteration, and solution chemistry in EAFS and BM samples. XRD and FTIR analysis reveal that exposure to different HEPIs caused almost no structural changes in both powders. In contrast, SEM analysis shows that HEPIs led to prominent microcracks on BM’s surface, with slight variations on EAFS. The extent of dissolution for Al and Ca ranges from 5% to 10% and 3% to 5% over time for the untreated BM, respectively, and these values are, at least, doubled when HEPIs is applied. For the case of EAFS, similar enhancements via HEPIs are achieved compared to its untreated form, but with higher Ca and Al extents. The enhancement in dissolution is associated with the micro-cracks, as evidenced by SEM analysis. To conclude, HEPIs can affect the early-stage dissolution properties of EAFS and BM to a certain degree, and more elements can be released if a high-energy photon dose is applied.

Chemotherapy aided by opening of the blood-brain barrier with intra-arterial infusion of hyperosmolar mannitol improves the outcome in primary central nervous system lymphoma. Proper opening of the blood-brain barrier is crucial for the treatment, yet there are no means available for its real-time monitoring. The intact blood-brain barrier maintains a mV-level electrical potential difference between blood and brain tissue, giving rise to a measurable electrical signal at the scalp. Therefore, we used direct-current electroencephalography (DC-EEG) to characterize the spatiotemporal behavior of scalp-recorded slow electrical signals during blood-brain barrier opening. Nine anesthetized patients receiving chemotherapy were monitored continuously during 47 blood-brain barrier openings induced by carotid or vertebral artery mannitol infusion. Left or right carotid artery mannitol infusion generated a strongly lateralized DC-EEG response that began with a 2 min negative shift of up to 2000 μV followed by a positive shift lasting up to 20 min above the infused carotid artery territory, whereas contralateral responses were of opposite polarity. Vertebral artery mannitol infusion gave rise to a minimally lateralized and more uniformly distributed slow negative response with a posterior-frontal gradient. Simultaneously performed near-infrared spectroscopy detected a multiphasic response beginning with mannitol-bolus induced dilution of blood and ending in a prolonged increase in the oxy/deoxyhemoglobin ratio. The pronounced DC-EEG shifts are readily accounted for by opening and sealing of the blood-brain barrier. These data show that DC-EEG is a promising real-time monitoring tool for blood-brain barrier disruption augmented drug delivery.

Background and aimsPrepregnancy maternal obesity is a global health problem and has been associated with offspring metabolic and mental ill-health. However, there is a knowledge gap in understanding potential neurobiological factors related to these associations. This study explored the relation between maternal prepregnancy body mass index (BMI) and offspring brain white matter microstructure at the age of 6, 10, and 26 years in three independent cohorts.Subjects and methodsThe study used data from three European birth cohorts (n = 116 children aged 6 years, n = 2466 children aged 10 years, and n = 437 young adults aged 26 years). Information on maternal prepregnancy BMI was obtained before or during pregnancy and offspring brain white matter microstructure was measured at age 6, 10, or 26 years. We used magnetic resonance imaging-derived fractional anisotropy (FA) and mean diffusivity (MD) as measures of white matter microstructure in the brainstem, callosal, limbic, association, and projection tracts. Linear regressions were fitted to examine the association of maternal BMI and offspring white matter microstructure, adjusting for several socioeconomic and lifestyle-related confounders, including education, smoking, and alcohol use.ResultsMaternal BMI was associated with higher FA and lower MD in multiple brain tracts, for example, association and projection fibers, in offspring aged 10 and 26 years, but not at 6 years. In each cohort maternal BMI was related to different white matter tract and thus no common associations across the cohorts were found.ConclusionsMaternal BMI was associated with higher FA and lower MD in multiple brain tracts in offspring aged 10 and 26 years, but not at 6 years of age. Future studies should examine whether our observations can be replicated and explore the potential causal nature of the findings.

Studies show evidence of longitudinal brain volume decreases in schizophrenia. We studied brain volume changes and their relation to symptom severity, level of function, cognition, and antipsychotic medication in participants with schizophrenia and control participants from a general population based birth cohort sample in a relatively long follow-up period of almost a decade. All members of the Northern Finland Birth Cohort 1966 with any psychotic disorder and a random sample not having psychosis were invited for a MRI brain scan, and clinical and cognitive assessment during 1999-2001 at the age of 33-35 years. A follow-up was conducted 9 years later during 2008-2010. Brain scans at both time points were obtained from 33 participants with schizophrenia and 71 control participants. Regression models were used to examine whether brain volume changes predicted clinical and cognitive changes over time, and whether antipsychotic medication predicted brain volume changes. The mean annual whole brain volume reduction was 0.69% in schizophrenia, and 0.49% in controls (p = 0.003, adjusted for gender, educational level, alcohol use and weight gain). The brain volume reduction in schizophrenia patients was found especially in the temporal lobe and periventricular area. Symptom severity, functioning level, and decline in cognition were not associated with brain volume reduction in schizophrenia. The amount of antipsychotic medication (dose years of equivalent to 100 mg daily chlorpromazine) over the follow-up period predicted brain volume loss (p = 0.003 adjusted for symptom level, alcohol use and weight gain). In this population based sample, brain volume reduction continues in schizophrenia patients after the onset of illness, and antipsychotic medications may contribute to these reductions.

Background and purpose Radiation therapy (RT) is a cornerstone of head and neck squamous cell carcinoma (HNSCC) treatment, often used alongside surgical approaches, delivering curative doses between 50–70 Gy. Pre-RT dental screenings aim to prevent oral complications by extracting teeth with poor prognosis, particularly in high-dose areas exceeding 40 Gy. The aim of the present study was to measure the planned radiation doses received on dentition during definitive or postoperative radiation therapy for HNSCC. Material and methods This retrospective study analyzed 91 HNSCC cases treated with RT at Oulu University Hospital (2018–2021), assessing radiation doses to dentition, mandible, and parotid glands across different tumor sites. Results Results showed that ipsilateral RT spared contralateral and frontal dental regions more effectively than bilateral RT, particularly in oral cavity and oropharyngeal cancers. Conversely, hypopharyngeal and laryngeal cancers rarely exposed dentition to doses above 40 Gy. Bilateral RT often exceeded the 40 Gy threshold in mandibular and parotid regions, particularly in oral cavity cancers, underscoring the need for precise dose planning to balance tumor control with oral health preservation. Conclusion The findings highlight that ipsilateral RT can reduce the need for pre-RT dental extractions in contralateral regions and provide a basis for optimizing dental care strategies. By understanding dose distributions, balance can be addressed between minimizing oral health impacts and ensuring effective HNSCC treatment.

A commercial deep learning (DL)-based automated segmentation tool (AST) for computed tomography (CT) is evaluated for accuracy and efficiency gain within prostate cancer patients. Thirty patients from six clinics were reviewed with manual- (MC), automated- (AC) and automated and edited (AEC) contouring methods. In the AEC group, created contours (prostate, seminal vesicles, bladder, rectum, femoral heads and penile bulb) were edited, whereas the MC group included empty datasets for MC. In one clinic, lymph node CTV delineations were evaluated for interobserver variability. Compared to MC, the mean time saved using the AST was 12 min for the whole data set (46%) and 12 min for the lymph node CTV (60%), respectively. The delineation consistency between MC and AEC groups according to the Dice similarity coefficient (DSC) improved from 0.78 to 0.94 for the whole data set and from 0.76 to 0.91 for the lymph nodes. The mean DSCs between MC and AC for all six clinics were 0.82 for prostate, 0.72 for seminal vesicles, 0.93 for bladder, 0.84 for rectum, 0.69 for femoral heads and 0.51 for penile bulb. This study proves that using a general DL-based AST for CT images saves time and improves consistency.

This is a multi-institutional study to evaluate a head-and-neck CT auto-segmentation software across seven institutions globally. 11 lymph node levels and 7 organs-at-risk contours were evaluated in a two-phase study design. Time savings were measured in both phases, and the inter-observer variability across the seven institutions was quantified in phase two. Overall time savings were found to be 42% in phase one and 49% in phase two. Lymph node levels IA, IB, III, IVA, and IVB showed no significant time savings, with some centers reporting longer editing times than manual delineation. All the edited ROIs showed reduced inter-observer variability compared to manual segmentation. Our study shows that auto-segmentation plays a crucial role in harmonizing contouring practices globally. However, the clinical benefits of auto-segmentation software vary significantly across ROIs and between clinics. To maximize its potential, institution-specific commissioning is required to optimize the clinical benefits.

Functional connectivity of the resting-state networks of the brain is thought to be mediated by very-low-frequency fluctuations (VLFFs <0.1 Hz) in neuronal activity. However, vasomotor waves and cardiorespiratory pulsations influence indirect measures of brain function, such as the functional magnetic resonance imaging blood-oxygen-level-dependent (BOLD) signal. How strongly physiological oscillations correlate with spontaneous BOLD signals is not known, partially due to differences in the data-sampling rates of different methods. Recent ultrafast inverse imaging sequences, including magnetic resonance encephalography (MREG), enable critical sampling of these signals. In this study, we describe a multimodal concept, referred to as Hepta-scan, which incorporates synchronous MREG with scalp electroencephalography, near-infrared spectroscopy, noninvasive blood pressure, and anesthesia monitoring. Our preliminary results support the idea that, in the absence of aliased cardiorespiratory signals, VLFFs in the BOLD signal are affected by vasomotor and electrophysiological sources. Further, MREG signals showed a high correlation coefficient between the ventromedial default mode network (DMNvmpf) and electrophysiological signals, especially in the VLF range. Also, oxy- and deoxyhemoglobin and vasomotor waves were found to correlate with DMNvmpf. Intriguingly, usage of shorter time windows in these correlation measurements produced significantly (p<0.05) higher positive and negative correlation coefficients, suggesting temporal nonstationary behavior between the measurements. Focus on the VLF range strongly increased correlation strength.