Association of bilateral oophorectomy with incidence of Parkinson's disease: A systematic review and meta-analysis.

INTRODUCTION: Current evidence in the literature is inconclusive due to conflicting results with regards to an association between B/L (B/L) oophorectomy and Parkinson's disease (PD). We included large, powered studies to assess the association of PD in women who have undergone B/L oophorectomy. METHODS: We conducted a comprehensive search across three databases from inception to October 2022 for observational studies including pre-menopausal or post-menopausal women undergoing B/L oophorectomy. Primary outcome of interest was incidence of PD or parkinsonism. The results for these associations were presented as Risk Ratios (RR) with 95% confidence intervals (CI), which were pooled using a generic invariance weighted random effects model using Review Manager (RevMan). RESULTS: Data was included from a total of 4 studies. No significant association was found between B/L oophorectomy and PD (RR: 1.38; 95% CI: 0.76 to 2.49; I2:89 %) in contrast significant association was found with parkinsonism (RR: 1.80; 95% CI: 1.29 to 2.52). Age at surgery didn't significantly affect Parkinsonism incidence (RR: 0.88; 95% CI: 0.59 to 1.3). No significant association was found between ovarian indication and Parkinsonism (RR: 1.08; 95% CI: 0.69 to 1.68). B/L oophorectomy with hysterectomy was associated with higher Parkinson's risk compared to without hysterectomy (RR: 1.4; 95% CI: 1.13 to 1.74). Lastly, there was no significant association between Post Menopausal Hormonal (PMH) use and Parkinson's disease (RR: 1.07; 95% CI: 0.92 to 1.26). CONCLUSION: Our findings suggest that B/L oophorectomy is significantly associated with the incidence of Parkinsonism. Further research is needed to understand the potential relationship between oophorectomy and Parkinson's disease.

Clinical translation of noninvasive intracranial pressure sensing with diffuse correlation spectroscopy.

OBJECTIVE: Intracranial pressure (ICP) is an important therapeutic target in many critical neuropathologies. The current tools for ICP measurements are invasive; hence, these are only selectively applied in critical cases where the benefits surpass the risks. To address the need for low-risk ICP monitoring, the authors developed a noninvasive alternative. METHODS: The authors recently demonstrated noninvasive quantification of ICP in an animal model by using morphological analysis of microvascular cerebral blood flow (CBF) measured with diffuse correlation spectroscopy (DCS). The current prospective observational study expanded on this preclinical study by translating the method to pediatric patients. Here, the CBF features, along with mean arterial pressure (MAP) and heart rate (HR) data, were used to build a random decision forest, machine learning model for estimation of ICP; the results of this model were compared with those of invasive monitoring. RESULTS: Fifteen patients (mean age ± SD [range] 9.8 ± 5.1 [0.3-17.5] years; median age [interquartile range] 11 [7.4] years; 10 males and 5 females) who underwent invasive neuromonitoring for any purpose were enrolled. Estimated ICP (ICPest) very closely matched invasive ICP (ICPinv), with a root mean square error (RMSE) of 1.01 mm Hg and 95% limit of agreement of ≤ 1.99 mm Hg for ICPinv 0.01-41.25 mm Hg. When the ICP range (ICPinv 0.01-29.05 mm Hg) was narrowed on the basis of the sample population, both RMSE and limit of agreement improved to 0.81 mm Hg and ≤ 1.6 mm Hg, respectively. In addition, 0.3% of the test samples for ICPinv ≤ 20 mm Hg and 5.4% of the test samples for ICPinv > 20 mm Hg had a limit of agreement > 5 mm Hg, which may be considered the acceptable limit of agreement for clinical validity of ICP sensing. For the narrower case, 0.1% of test samples for ICPinv ≤ 20 mm Hg and 1.1% of the test samples for ICPinv > 20 mm Hg had a limit of agreement > 5 mm Hg. Although the CBF features were crucial, the best prediction accuracy was achieved when these features were combined with MAP and HR data. Lastly, preliminary leave-one-out analysis showed model accuracy with an RMSE of 6 mm Hg and limit of agreement of ≤ 7 mm Hg. CONCLUSIONS: The authors have shown that DCS may enable ICP monitoring with additional clinical validation. The lower risk of such monitoring would allow ICP to be estimated for a wide spectrum of indications, thereby both reducing the use of invasive monitors and increasing the types of patients who may benefit from ICP-directed therapies.

Genomic landscape of prominent XDR Acinetobacter clonal complexes from Dhaka, Bangladesh.

BACKGROUND: Acinetobacter calcoaceticus-A. baumannii (ACB) complex pathogens are known for their prevalence in nosocomial infections and extensive antimicrobial resistance (AMR) capabilities. While genomic studies worldwide have elucidated the genetic context of antibiotic resistance in major international clones (ICs) of clinical Acinetobacter spp., not much information is available from Bangladesh. In this study, we analysed the AMR profiles of 63 ACB complex strains collected from Dhaka, Bangladesh. Following this, we generated draft genomes of 15 of these strains to understand the prevalence and genomic environments of AMR, virulence and mobilization associated genes in different Acinetobacter clones. RESULTS: Around 84% (n = 53) of the strains were extensively drug resistant (XDR) with two showing pan-drug resistance. Draft genomes generated for 15 strains confirmed 14 to be A. baumannii while one was A. nosocomialis. Most A. baumannii genomes fell under three clonal complexes (CCs): the globally dominant CC1 and CC2, and CC10; one strain had a novel sequence type (ST). AMR phenotype-genotype agreement was observed and the genomes contained various beta-lactamase genes including blaOXA-23 (n = 12), blaOXA-66 (n = 6), and blaNDM-1 (n = 3). All genomes displayed roughly similar virulomes, however some virulence genes such as the Acinetobactin bauA and the type IV pilus gene pilA displayed high genetic variability. CC2 strains carried highest levels of plasmidic gene content and possessed conjugative elements carrying AMR genes, virulence factors and insertion sequences. CONCLUSION: This study presents the first comparative genomic analysis of XDR clinical Acinetobacter spp. from Bangladesh. It highlights the prevalence of different classes of beta-lactamases, mobilome-derived heterogeneity in genetic architecture and virulence gene variability in prominent Acinetobacter clonal complexes in the country. The findings of this study would be valuable in understanding the genomic epidemiology of A. baumannii clones and their association with closely related pathogenic species like A. nosocomialis in Bangladesh.

Two-layer analytical model for estimation of layer thickness and flow using Diffuse Correlation Spectroscopy.

Diffuse correlation spectroscopy (DCS) has been widely explored for its ability to measure cerebral blood flow (CBF), however, mostly under the assumption that the human head is homogenous. In addition to CBF, knowledge of extracerebral layers, such as skull thickness, can be informative and crucial for patient with brain complications such as traumatic brain injuries. To bridge the gap, this study explored the feasibility of simultaneously extracting skull thickness and flow in the cortex layer using DCS. We validated a two-layer analytical model that assumed the skull as top layer with a finite thickness and the brain cortex as bottom layer with semi-infinite geometry. The model fitted for thickness of the top layer and flow of the bottom layer, while assumed other parameters as constant. The accuracy of the two-layer model was tested against the conventional single-layer model using measurements from custom made two-layer phantoms mimicking skull and brain. We found that the fitted top layer thickness at each source detector (SD) distance is correlated with the expected thickness. For the fitted bottom layer flow, the two-layer model fits relatively consistent flow across all top layer thicknesses. In comparison, the conventional one-layer model increasingly underestimates the bottom layer flow as top layer thickness increases. The overall accuracy of estimating first layer thickness and flow depends on the SD distance in relationship to first layer thickness. Lastly, we quantified the influence of uncertainties in the optical properties of each layer. We found that uncertainties in the optical properties only mildly influence the fitted thickness and flow. In this work we demonstrate the feasibility of simultaneously extracting of layer thickness and flow using a two-layer DCS model. Findings from this work may introduce a robust and cost-effective approach towards simultaneous bedside assessment of skull thickness and cerebral blood flow.

Optical scattering as an early marker of apoptosis during chemotherapy and antiangiogenic therapy in murine models of prostate and breast cancer.

Monitoring of the in vivo tumor state to track therapeutic response in real time may help to evaluate new drug candidates, maximize treatment efficacy, and reduce the burden of overtreatment. Current preclinical tumor imaging methods have largely focused on anatomic imaging (e.g., MRI, ultrasound), functional imaging (e.g., FDG-PET), and molecular imaging with exogenous contrast agents (e.g., fluorescence optical tomography). Here we utalize spatial frequency domain imaging (SFDI), a noninvasive, label-free optical technique, for the wide-field quantification of changes in tissue optical scattering in preclinical tumor models during treatment with chemotherapy and antiangiogenic agents. Optical scattering is particularly sensitive to tissue micro-architectural changes, including those that occur during apoptosis, an early indicator of response to cytotoxicity induced by chemotherapy, thermotherapy, cryotherapy, or radiation therapy. We utilized SFDI to monitor responses of PC3/2G7 prostate tumors and E0771 mammary tumors to treatment with cyclophosphamide or the antiangiogenic agent DC101 for up to 49 days. The SFDI-derived scattering amplitude was highly correlated with cleaved caspase-3, a marker of apoptosis (ρp = 0.75), while the exponent of the scattering wavelength-dependence correlated with the cell proliferation marker PCNA (ρp = 0.69). These optical parameters outperformed tumor volume and several functional parameters (e.g., oxygen saturation and hemoglobin concentration) as an early predictive biomarker of treatment response. Quantitative diffuse optical scattering is thus a promising new early marker of treatment response, which does not require radiation or exogenous contrast agents.

Diffuse optical spectroscopic imaging reveals distinct early breast tumor hemodynamic responses to metronomic and maximum tolerated dose regimens.

BACKGROUND: Breast cancer patients with early-stage disease are increasingly administered neoadjuvant chemotherapy (NAC) to downstage their tumors prior to surgery. In this setting, approximately 31% of patients fail to respond to therapy. This demonstrates the need for techniques capable of providing personalized feedback about treatment response at the earliest stages of therapy to identify patients likely to benefit from changing treatment. Diffuse optical spectroscopic imaging (DOSI) has emerged as a promising functional imaging technique for NAC monitoring. DOSI uses non-ionizing near-infrared light to provide non-invasive measures of absolute concentrations of tissue chromophores such as oxyhemoglobin. In 2011, we reported a new DOSI prognostic marker, oxyhemoglobin flare: a transient increase in oxyhemoglobin capable of discriminating NAC responders within the first day of treatment. In this follow-up study, DOSI was used to confirm the presence of the flare as well as to investigate whether DOSI markers of NAC response are regimen dependent. METHODS: This dual-center study examined 54 breast tumors receiving NAC measured with DOSI before therapy and the first week following chemotherapy administration. Patients were treated with either a standard of care maximum tolerated dose (MTD) regimen or an investigational metronomic (MET) regimen. Changes in tumor chromophores were tracked throughout the first week and compared to pathologic response and treatment regimen at specific days utilizing generalized estimating equations (GEE). RESULTS: Within patients receiving MTD therapy, the oxyhemoglobin flare was confirmed as a prognostic DOSI marker for response appearing as soon as day 1 with post hoc GEE analysis demonstrating a difference of 48.77% between responders and non-responders (p < 0.0001). Flare was not observed in patients receiving MET therapy. Within all responding patients, the specific treatment was a significant predictor of day 1 changes in oxyhemoglobin, showing a difference of 39.45% (p = 0.0010) between patients receiving MTD and MET regimens. CONCLUSIONS: DOSI optical biomarkers are differentially sensitive to MTD and MET regimens at early timepoints suggesting the specific treatment regimen should be considered in future DOSI studies. Additionally, DOSI may help to identify regimen-specific responses in a more personalized manner, potentially providing critical feedback necessary to implement adaptive changes to the treatment strategy.

OpenSFDI: an open-source guide for constructing a spatial frequency domain imaging system.

Significance: Spatial frequency domain imaging (SFDI) is a diffuse optical measurement technique that can quantify tissue optical absorption (µa) and reduced scattering (µs') on a pixel-by-pixel basis. Measurements of µa at different wavelengths enable the extraction of molar concentrations of tissue chromophores over a wide field, providing a noncontact and label-free means to assess tissue viability, oxygenation, microarchitecture, and molecular content. We present here openSFDI: an open-source guide for building a low-cost, small-footprint, three-wavelength SFDI system capable of quantifying µa and µs' as well as oxyhemoglobin and deoxyhemoglobin concentrations in biological tissue. The companion website provides a complete parts list along with detailed instructions for assembling the openSFDI system.

Aim: We describe the design of openSFDI and report on the accuracy and precision of optical property extractions for three different systems fabricated according to the instructions on the openSFDI website.

Approach: Accuracy was assessed by measuring nine tissue-simulating optical phantoms with a physiologically relevant range of µa and µs' with the openSFDI systems and a commercial SFDI device. Precision was assessed by repeatedly measuring the same phantom over 1 h.

Results: The openSFDI systems had an error of 0 ± 6 % in µa and -2 ± 3 % in µs', compared to a commercial SFDI system. Bland-Altman analysis revealed the limits of agreement between the two systems to be ± 0.004 mm - 1 for µa and -0.06 to 0.1 mm - 1 for µs'. The openSFDI system had low drift with an average standard deviation of 0.0007 mm - 1 and 0.05 mm - 1 in µa and µs', respectively.

Conclusion: The openSFDI provides a customizable hardware platform for research groups seeking to utilize SFDI for quantitative diffuse optical imaging.

Diffuse and nonlinear imaging of multiscale vascular parameters for in vivo monitoring of preclinical mammary tumors.

Diffuse optical imaging (DOI) techniques provide a wide-field or macro assessment of the functional tumor state and have shown substantial promise for monitoring treatment efficacy in cancer. Conversely, intravital microscopy provides a high-resolution view of the tumor state and has played a key role in characterizing treatment response in the preclinical setting. There has been little prior work in investigating how the macro and micro spatial scales can be combined to develop a more comprehensive and translational view of treatment response. To address this, a new multiscale preclinical imaging technique called diffuse and nonlinear imaging (DNI) was developed. DNI combines multiphoton microscopy with spatial frequency domain imaging (SFDI) to provide multiscale data sets of tumor microvascular architecture coregistered within wide-field hemodynamic maps. A novel method was developed to match the imaging depths of both modalities by utilizing informed SFDI spatial frequency selection. An in vivo DNI study of murine mammary tumors revealed multiscale relationships between tumor oxygen saturation and microvessel diameter, and tumor oxygen saturation and microvessel length (|Pearson's ρ| ≥ 0.5, P < 0.05). Going forward, DNI will be uniquely enabling for the investigation of multiscale relationships in tumors during treatment.

Two-layer inverse model for improved longitudinal preclinical tumor imaging in the spatial frequency domain.

Spatial frequency domain imaging (SFDI) is a widefield, noncontact, and label-free imaging modality that is currently being explored as a new tool for longitudinal tracking of cancer therapies in the preclinical setting. We describe a two-layer look-up-table (LUT) inversion algorithm for SFDI that better accounts for the skin (top layer) and tumor (bottom layer) tissue geometry in subcutaneous tumor models. Monte Carlo (MC) simulations were conducted natively in the spatial frequency domain, avoiding discretization errors associated with Fourier or Hankel transforms of conventional MC simulation results. The two-layer LUT was validated using two-layer tissue mimicking optical phantoms, in which the optical property extractions of the bottom (tumor) layer were determined to be within 20% and 11% of the true values for µa and µs', respectively. A sensitivity analysis was conducted to evaluate how imperfect top layer estimates affect bottom-layer optical property extractions. Finally, the two-layer LUT was used to reanalyze a prior longitudinal data set, which revealed larger therapy-induced changes in optical scattering and a more hypoxic tumor environment compared to the homogeneous LUT. The two-layer LUT described here improves the accuracy of subcutaneous tumor imaging, and the general methodology can be applied for arbitrary multilayer SFDI applications.

Optical property uncertainty estimates for spatial frequency domain imaging.

Spatial frequency domain imaging (SFDI) is a wide-field diffuse optical imaging modality that has attracted considerable interest in recent years. Typically, diffuse reflectance measurements of spatially modulated light are used to quantify the optical absorption and reduced scattering coefficients of tissue, and with these, chromophore concentrations are extracted. However, uncertainties in estimated absorption and reduced scattering coefficients are rarely reported, and we know of no method capable of providing these when look-up table (LUT) algorithms are used to recover the optical properties. We present a method to generate optical property uncertainty estimates from knowledge of diffuse reflectance measurement errors. By employing the Cramér-Rao bound, we can quickly and efficiently explore theoretical SFDI performance as a function of spatial frequencies and sample optical properties, allowing us to optimize spatial frequency selection for a given application. In practice, we can also obtain useful uncertainty estimates for optical properties recovered with a two-frequency LUT algorithm, as we demonstrate with tissue-simulating phantom and in vivo experiments. Finally, we illustrate how absorption coefficient uncertainties can be propagated forward to yield uncertainties for chromophore concentrations, which could significantly impact the interpretation of experimental results.

Feasibility of spatial frequency domain imaging (SFDI) for optically characterizing a preclinical oncology model.

Determination of chemotherapy efficacy early during treatment would provide more opportunities for physicians to alter and adapt treatment plans. Diffuse optical technologies may be ideally suited to track early biological events following chemotherapy administration due to low cost and high information content. We evaluated the use of spatial frequency domain imaging (SFDI) to characterize a small animal tumor model in order to move towards the goal of endogenous optical monitoring of cancer therapy in a controlled preclinical setting. The effects of key measurement parameters including the choice of imaging spatial frequency and the repeatability of measurements were evaluated. The precision of SFDI optical property extractions over repeat mouse measurements was determined to be within 3.52% for move and replace experiments. Baseline optical properties and chromophore values as well as intratumor heterogeneity were evaluated over 25 tumors. Additionally, tumor growth and chemotherapy response were monitored over a 45 day longitudinal study in a small number of mice to demonstrate the ability of SFDI to track treatment effects. Optical scattering and oxygen saturation increased as much as 70% and 25% respectively in treated tumors, suggesting SFDI may be useful for preclinical tracking of cancer therapies.

Angle correction for small animal tumor imaging with spatial frequency domain imaging (SFDI).

Spatial frequency domain imaging (SFDI) is a widefield imaging technique that allows for the quantitative extraction of tissue optical properties. SFDI is currently being explored for small animal tumor imaging, but severe imaging artifacts occur for highly curved surfaces (e.g. the tumor edge). We propose a modified Lambertian angle correction, adapted from the Minnaert correction method for satellite imagery, to account for tissue surface angles up to 75°. The method was tested in a hemisphere phantom study as well as a small animal tumor model. The proposed method reduced µa and µs` extraction errors by an average of 64% and 16% respectively compared to performing no angle correction, and provided more physiologically agreeable optical property and chromophore values on tumors.

Three-dimensional printed optical phantoms with customized absorption and scattering properties.

Three-dimensional (3D) printing offers the promise of fabricating optical phantoms with arbitrary geometry, but commercially available thermoplastics provide only a small range of physiologically relevant absorption (µa) and reduced scattering (µs`) values. Here we demonstrate customizable acrylonitrile butadiene styrene (ABS) filaments for dual extrusion 3D printing of tissue mimicking optical phantoms. µa and µs` values were adjusted by incorporating nigrosin and titanium dioxide (TiO2) in the filament extrusion process. A wide range of physiologically relevant optical properties was demonstrated with an average repeatability within 11.5% for µa and 7.71% for µs`. Additionally, a mouse-simulating phantom, which mimicked both the geometry and optical properties of a hairless mouse with an implanted xenograft tumor, was printed using dual extrusion methods. 3D printed tumor optical properties matched the live tumor with less than 3% error at a wavelength of 659 nm. 3D printing with user defined optical properties may provide a viable method for durable optically diffusive phantoms for instrument characterization and calibration.