Digging Deeper with Diffuse Correlation Spectroscopy

Patients with neurological diseases are vulnerable to cerebral ischemia, which can lead to brain injury. In the intensive care unit (ICU), neuromonitoring techniques that can detect flow reductions would enable timely administration of therapies aimed at restoring adequate cerebral perfusion, thereby avoiding damage to the brain. However, suitable bedside neuromonitoring methods sensitive to changes of blood flow and/or oxygen metabolism have yet to be established. Near-infrared spectroscopy (NIRS) is a promising technique capable of non-invasively monitoring flow and oxygenation. Specifically, diffuse correlation spectroscopy (DCS) and time-resolved (TR) NIRS can be used to monitor blood flow and tissue oxygenation, respectively, and combined to measuring oxidative metabolism. The work presented in this thesis focused on advancing a DCS/TR-NIRS hybrid system for acquiring these physiological measurements at the bedside. The application of NIRS for neuromonitoring is favourable in the neonatal ICU since the relatively thin scalp and skull of infants has minimal effect on the detected optical signal. Considering this application, the validation of a combined DCS/NIRS method for measuring the cerebral metabolic rate of oxygen (CMRO2) was investigated in Chapter 2. Although perfusion changes measured by DCS have been confirmed by various flow modalities, characterization of photon scattering in the brain is not clearly understood. Chapter 3 presents the first DCS study conducted directly on exposed cortex to confirm that the Brownian motion model is the best flow model for characterizing the DCS signal. Furthermore, a primary limitation of DCS is signal contamination from extracerebral tissues in the adult head, causing CBF to be underestimated. In Chapter 4, a multi-layered model was implemented to separate signal contributions from scalp and brain; derived CBF changes were compared to computed tomography perfusion. Overall, this thesis advances DCS techniques by (i) quantifying cerebral oxygen metabolism, (ii) confirming the more appropriate flow model for analyzing DCS data and (iii) demonstrating the ability of DCS to measure CBF accurately despite the presence of a thick (1-cm) extracerebral layer. Ultimately, the work completed in this thesis should help with the development of a hybrid DCS/NIRS system suitable for monitoring cerebral hemodynamics and energy metabolism in critical-ill patients

THE INFLUENCE OF TRP53 IN THE DOSE RESPONSE OF RADIATIONINDUCED APOPTOSIS, DNA REPAIR AND GENOMIC STABILITY IN MURINE HAEMATOPOIETIC CELLS

Apoptotic and DNA damage endpoints are frequently used as surrogate markers of cancer risk, and have been well-studied in the Trp53+/- mouse model. We report the effect of differing Trp53 gene status on the dose response of ionizing radiation exposures (0.01- 2 Gy), with the unique perspective of determining if effects of gene status remain at extended time points. Here we report no difference in the dose response for radiationinduced DNA double-strand breaks in bone marrow and genomic instability (MN-RET levels) in peripheral blood, between wild-type (Trp53+/+) and heterozygous (Trp53+/-) mice. The dose response for Trp53+/+ mice showed higher initial levels of radiation-induced lymphocyte apoptosis relative to Trp53+/- between 0 and 1 Gy. Although this trend was observed up to 12 hours post-irradiation, both genotypes ultimately reached the same level of apoptosis at 14 hours, suggesting the importance of late-onset p53-independent apoptotic responses in this mouse model. Expected radiation-induced G1 cell cycle delay was observed in Trp53+/+ but not Trp53+/-. Although p53 has an important role in cancer risk, we have shown its influence on radiation dose response can be temporally variable. This research highlights the importance of caution when using haematopoietic endpoints as surrogates to extrapolate radiation-induced cancer risk estimation

Calibration of diffuse correlation spectroscopy with a time-resolved near-infrared technique to yield absolute cerebral blood flow measurements: errata

Abstract: The authors provide corrections to tabular data and a figure, which do not alter the conclusions of the original paper [Biomed. Opt. Express 2, 2068 (2011)]

Assessing tumor physiology by dynamic contrast-enhanced near-infrared spectroscopy

The purpose of this study was to develop a dynamic contrast-enhanced (DCE) near-infrared spectroscopy (NIRS) technique to characterize tumor physiology. Dynamic data were acquired using two contrast agents of different molecular weights, indocyanine green (ICG) and IRDye 800CW carboxylate (IRDcxb). The DCE curves were analyzed using a kinetic model capable of extracting estimates of tumor blood flow (F), capillary transit time (t(c)) and the amount of dye that leaked into the extravascular space (EVS) - characterized by the extraction fraction (E). Data were acquired from five nude rats with tumor xenografts (\u3e10mm) implanted in the neck. Four DCE-NIR datasets (two from each contrast agent) were acquired for each rat. The dye concentration curve in arterial blood, which is required to quantify the model parameters, was measured non-invasively by dye densitometry. A modification to the kinetic model to characterize t(c) as a distribution of possible values, rather than finite, improved the fit of acquired tumor concentration curves, resulting in more reliable estimates. This modified kinetic model identified a difference between the extracted fraction of IRDcxb, 15 +/- 6 %, and ICG, 1.6 +/- 0.6 %, in the tumor, which can be explained by the difference in molecular weight: 67 kDa for ICG since it binds to albumin and 1.17 kDa for IRD. This study demonstrates the ability of DCE-NIRS to quantify tumor physiology. The next step is to adapt this approach with a dual-receptor approach

Iterative Prompt Refinement for Radiation Oncology Symptom Extraction Using Teacher-Student Large Language Models

This study introduces a novel teacher-student architecture utilizing Large Language Models (LLMs) to improve prostate cancer radiotherapy symptom extraction from clinical notes. Mixtral, the student model, initially extracts symptoms, followed by GPT-4, the teacher model, which refines prompts based on Mixtral's performance. This iterative process involved 294 single symptom clinical notes across 12 symptoms, with up to 16 rounds of refinement per epoch. Results showed significant improvements in extracting symptoms from both single and multi-symptom notes. For 59 single symptom notes, accuracy increased from 0.51 to 0.71, precision from 0.52 to 0.82, recall from 0.52 to 0.72, and F1 score from 0.49 to 0.73. In 375 multi-symptom notes, accuracy rose from 0.24 to 0.43, precision from 0.6 to 0.76, recall from 0.24 to 0.43, and F1 score from 0.20 to 0.44. These results demonstrate the effectiveness of advanced prompt engineering in LLMs for radiation oncology use

The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase 1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age  6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score  652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc = 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N = 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in Asia and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701

Trp53 status on induced DNA repair and genomic stability

Apoptotic and DNA damage endpoints are frequently used as surrogate markers of cancer risk, and have been well-studied in the Trp53+/- mouse model. We report the effect of differing Trp53 gene status on the dose response of ionizing radiation exposures (0.01- 2 Gy), with the unique perspective of determining if effects of gene status remain at extended time points. Here we report no difference in the dose response for radiationinduced DNA double-strand breaks in bone marrow and genomic instability (MN-RET levels) in peripheral blood, between wild-type (Trp53+/+) and heterozygous (Trp53+/-) mice. The dose response for Trp53+/+ mice showed higher initial levels of radiation-induced lymphocyte apoptosis relative to Trp53+/- between 0 and 1 Gy. Although this trend was observed up to 12 hours post-irradiation, both genotypes ultimately reached the same level of apoptosis at 14 hours, suggesting the importance of late-onset p53-independent apoptotic responses in this mouse model. Expected radiation-induced G1 cell cycle delay was observed in Trp53+/+ but not Trp53+/-. Although p53 has an important role in cancer risk, we have shown its influence on radiation dose response can be temporally variable. This research highlights the importance of caution when using haematopoietic endpoints as surrogates to extrapolate radiation-induced cancer risk estimation

Application of a three-layer model to multi-distance diffuse correlation spectroscopy: Validation experiments in pigs

© OSA 2016. A multi-distance diffuse correlation spectroscopy (DCS) technique that assesses cerebral blood flow changes in a three-layered adult model, which was verified by computed tomography perfusion

Assessment of the best flow model to characterize diffuse correlation spectroscopy data acquired directly on the brain

© 2015 Optical Society of America. Diffuse correlation spectroscopy (DCS) is a non-invasive optical technique capable of monitoring tissue perfusion. The normalized temporal intensity autocorrelation function generated by DCS is typically characterized by assuming that the movement of erythrocytes can be modeled as a Brownian diffusion-like process instead of by the expected random flow model. Recently, a hybrid model, referred to as the hydrodynamic diffusion model, was proposed, which combines the random and Brownian flow models. The purpose of this study was to investigate the best model to describe autocorrelation functions acquired directly on the brain in order to avoid confounding effects of extracerebral tissues. Data were acquired from 11 pigs during normocapnia and hypocapnia, and flow changes were verified by computed tomography perfusion (CTP). The hydrodynamic diffusion model was found to provide the best fit to the autocorrelation functions; however, no significant difference for relative flow changes measured by the Brownian and hydrodynamic diffusion models was observed

Application of a three-layer model to multi-distance diffuse correlation spectroscopy: Validation experiments in pigs

© OSA 2016. A multi-distance diffuse correlation spectroscopy (DCS) technique that assesses cerebral blood flow changes in a three-layered adult model, which was verified by computed tomography perfusion