Pregnant in a Pandemic: Mental Wellbeing and Associated Healthy Behaviors Among Pregnant People in California During COVID-19.

INTRODUCTION: Pregnancy is a time of increased vulnerability to mental health disorders. Additionally, the COVID-19 pandemic has increased the incidence of depression and anxiety. Thus, we aimed to assess mental health and associated healthy behaviors of pregnant people in California during the pandemic in order to contextualize prenatal well-being during the first pandemic of the twenty-first century. METHODS: We conducted an online cross-sectional study of 433 pregnant people from June 6 through July 29, 2020. We explored 3 hypotheses: (1) mental health would be worse during the pandemic than in general pregnant samples to date; (2) first-time pregnant people would have worse mental health; and (3) healthy behaviors would be positively related to mental health. RESULTS: Many of our participants (22%) reported clinically significant depressive symptoms and 31% reported clinically significant anxiety symptoms. Multiparous pregnant people were more likely to express worries about their own health and wellbeing and the process of childbirth than were primiparous pregnant people. Additionally, as pregnancy advanced, sleep and nutrition worsened, while physical activity increased. Lastly, anxious-depressive symptomology was significantly predictive of participant sleep behaviors, nutrition, and physical activity during the past week. DISCUSSION: Pregnant people had worse mental health during the pandemic, and this was associated with worse health-promoting behaviors. Given that the COVID-19 pandemic and associated risks are likely to persist due to low vaccination rates and the emergence of variants with high infection rates, care that promotes mental and physical well-being for the pregnant population should be a public health priority.

Perinatal health care access, childbirth concerns, and birthing decision-making among pregnant people in California during COVID-19.

BACKGROUND: During public health emergencies, including the COVID-19 pandemic, access to adequate healthcare is crucial for providing for the health and wellbeing of families. Pregnant and postpartum people are a particularly vulnerable subgroup to consider when studying healthcare access. Not only are perinatal people likely at higher risk for illness, mortality, and morbidity from COVID-19 infection, they are also at higher risk for negative outcomes due to delayed or inadequate access to routine care. METHODS: We surveyed 820 pregnant people in California over two waves of the COVID-19 pandemic: (1) a 'non-surge' wave (June 2020, n = 433), and (2) during a 'surge' in cases (December 2020, n = 387) to describe current access to perinatal healthcare, as well as concerns and decision-making regarding childbirth, over time. We also examined whether existing structural vulnerabilities - including acute financial insecurity and racial/ethnic minoritization - are associated with access, concerns, and decision-making over these two waves. RESULTS: Pregnant Californians generally enjoyed more access to, and fewer concerns about, perinatal healthcare during the winter of 2020-2021, despite surging COVID-19 cases and hospitalizations, as compared to those surveyed during the COVID-19 'lull' in the summer of 2020. However, across 'surge' and 'non-surge' pandemic circumstances, marginalized pregnant people continued to fare worse - especially those facing acute financial difficulty, and racially minoritized individuals identifying as Black or Indigenous. CONCLUSIONS: It is important for clinicians, researchers, and policymakers to understand whether and how shifting community transmission and infection rates may impact access to perinatal healthcare. Targeting minoritized and financially insecure communities for increased upstream perinatal healthcare supports are promising avenues to blunt the negative impacts of the COVID-19 pandemic on pregnant people in California.

An Outbreak Preparedness and Mitigation Approach in Home Health and Personal Home Care During the COVID-19 Pandemic.

The acute respiratory disease COVID-19, caused by the novel Coronavirus SARS-CoV-2, is a worldwide pandemic affecting millions of people. The methodology that organizations who provide home health and personal home care services are using to respond to this pandemic has not yet been characterized. In this report, we describe our approach to comprehensive outbreak suppression and report an initial case series of COVID-19 positive patients receiving home-based services. We implemented enhanced infection control procedures across our affiliates, and we communicated these protocols to our offices using multi-faceted methods. Using custom built software applications enabling us to track patient and employee cases and exposures, we leveraged current public health recommendations to identify cases and to suppress transmission. In the 100-day period between January 20, 2020 and April 30, 2020, our affiliates provided services to 67 COVID-19 positive patients (<0.3% of census). Twenty patients were referred to home health post hospitalization for COVID-19 related illness, whereas 47 were found to have COVID-19 while living in community settings. Of those who were found to have COVID-19 in the community, 17 (39%) required subsequent hospitalization. Hospitalized patients had an average age of 74.5 ± 18, and 53% were male. There were 13 deaths (76%) among those hospitalized from the community with COVID-19 related illness. A highly coordinated and frequently communicated approach to infection control, case identification and employee screening can be performed by home health and personal home care organizations. Studies that further assess risks and predictors of illness severity in home-based COVID-19 patients are needed.

Simultaneous, label-free, multispectral fluorescence lifetime imaging and optical coherence tomography using a double-clad fiber.

We present a novel fiber-based imaging platform that allows simultaneous fluorescence lifetime imaging (FLIm) and optical coherence tomography (OCT) using a double-clad fiber. This platform acquires co-registered images showing structural and compositional contrast in unlabeled biological samples by scanning the fiber tip across the sample surface. In this Letter, we report a characterization of each modality and show examples of co-registered FLIm and OCT images acquired from a lemon segment and a section of human coronary artery. The close comparison between the combined FLIm and OCT images and a co-registered histology section provides a qualitative validation of the technique and highlights its potential for minimally invasive, multimodal imaging of tissue structure and composition.

Detection of plaque structure and composition using OCT combined with two-photon luminescence (TPL) imaging.

BACKGROUND AND OBJECTIVES: Atherosclerosis and plaque rupture leads to myocardial infarction and stroke. A novel hybrid optical coherence tomography (OCT) and two-photon luminescence (TPL) fiber-based imaging system was developed to characterize tissue constituents in the context of plaque morphology. STUDY DESIGN/MATERIALS AND METHODS: Ex vivo coronary arteries (34 regions of interest) from three human hearts with atherosclerotic plaques were examined by OCT-TPL imaging. Histological sections (4 µm in thickness) were stained with Oil Red O for lipid, Von Kossa for calcium, and Verhoeff-Masson Tri-Elastic for collagen/elastin fibers and compared with imaging results. RESULTS: Biochemical components in plaques including lipid, oxidized-LDL, and calcium, as well as a non-tissue component (metal) are distinguished by multi-channel TPL images with statistical significance (P < 0.001). TPL imaging provides complementary optical contrast to OCT (two-photon absorption/emission vs scattering). Merged OCT-TPL images demonstrate the distribution of lipid deposits in registration with detailed plaque surface profile. CONCLUSIONS: Results suggest that multi-channel TPL imaging can effectively identify lipid sub-types and different plaque components. Furthermore, fiber-based hybrid OCT-TPL imaging simultaneously detects plaque structure and composition, improving the efficacy of vulnerable plaque detection and characterization.

Patient-Provider Trust as a Key Component of Prenatal Screening for Adverse Childhood Experiences (ACES): A Concept Analysis.

INTRODUCTION: The concept of patient-provider trust in prenatal adverse childhood experiences (ACEs) screening remains unexplored. This concept analysis illuminates the role of trust in prenatal ACE screening to improve patient-provider relationships, increase patient uptake of ACE screening, and ensure that ACE screening is implemented in a strengths-based, trauma-informed way. METHODS: A concept analysis was conducted using the Rodgers' evolutionary method to define the antecedents, attributes, and consequences of this construct. The databases searched were PubMed, PsychInfo, and Scopus between 2010 and 2021. A total of 389 articles were retrieved using the search terms prenatal, adverse childhood experiences screening, adverse childhood experiences, and adverse childhood experiences questionnaire. Included articles for detailed review contained prenatal screening, trauma screening (ACE or other), trust or building trust between patient and health care provider, patient engagement, and shared decision making. Excluded articles were those not in the context of prenatal care and that were exclusively about screening with no discussion about the patient-provider relationship or patient perspectives. A total of 32 articles were reviewed for this concept analysis. RESULTS: We define trust in prenatal ACE screening as a network of evidence-based attributes that include the timing of the screening, patient familiarity with the health care provider, cultural competence, demystifying trauma, open dialogue between the patient and health care provider, and patient comfort and respect. DISCUSSION: This concept analysis elucidates the importance of ACE screening and provides suggestions for establishing trust in the context of prenatal ACE screening. Results give insight and general guidance for health care providers looking to implement ACE screening in a trauma-informed way. Further research is needed to evaluate pregnant patients' attitudes toward ACE screening and how a health care provider's trauma history might influence their care. More inquiry is needed to understand the racial, ethnic, and cultural barriers to ACE screening.

Endoscopic fluorescence lifetime imaging for in vivo intraoperative diagnosis of oral carcinoma.

A clinically compatible fluorescence lifetime imaging microscopy (FLIM) system was developed. The system was applied to intraoperative in vivo imaging of head and neck squamous cell carcinoma (HNSCC). The endoscopic FLIM prototype integrates a gated (down to 0.2 ns) intensifier imaging system and a fiber-bundle endoscope (0.5-mm-diameter, 10,000 fibers with a gradient index lens objective 0.5 NA, 4-mm field of view), which provides intraoperative access to the surgical field. Tissue autofluorescence was induced by a pulsed laser (337 nm, 700 ps pulse width) and collected in the 460 ± 25 nm spectral band. FLIM experiments were conducted at 26 anatomic sites in ten patients during head and neck cancer surgery. HNSCC exhibited a weaker florescence intensity (~50% less) when compared with healthy tissue and a shorter average lifetime (τ(HNSCC) = 1.21 ± 0.04 ns) than the surrounding normal tissue (τN = 1.49 ± 0.06 ns). This work demonstrates the potential of FLIM for label-free head and neck tumor demarcation during intraoperative surgical procedures.

A fluorescence lifetime imaging classification method to investigate the collagen to lipid ratio in fibrous caps of atherosclerotic plaque.

BACKGROUND AND OBJECTIVE: This study describes a novel fluorescence lifetime imaging (FLIM) classification method to determine the ratio of collagen to lipid content in the fibrous cap of atherosclerotic plaques. Additionally, an analytical process to assess risk of plaque rupture based on this ratio is proposed. Collagen to lipid ratio has been shown to be an important parameter to evaluate structural integrity of the fibrous cap. FLIM and other time-resolved fluorescence techniques have recently been applied to the study of atherosclerosis based on the ability to assess biochemical composition. STUDY DESIGN/MATERIALS AND METHODS: Autofluorescence of specimens retrieved during carotid endarterectomy procedures was measured through three optical filters, F377: 377/50 nm, F460: 460/66 nm, and F510: 510/84 nm (center wavelength/bandwidth). A Laguerre deconvolution technique was used for the evaluation of fluorescence decay dynamics. The resulting decay parameters (average fluorescence lifetime and 4 Laguerre coefficients at each of the recorded bandwidths) were used for sample characterization. Linear discriminant analysis (LDA) was used to classify each image into collagen or lipid-rich regions based on these parameters. Ultimately, a risk-level was assigned based on the ratio of collagen to lipid on the surface of the fibrous cap. RESULTS: FLIM images were acquired in 18 carotid plaque specimens at 43 locations. Classification of collagen and lipid-rich regions within the fibrous cap was performed with sensitivity and specificity of 80% and 82%, respectively. CONCLUSIONS: Results from this study show that an LDA method of classifying regions of FLIM images of carotid plaque into collagen and lipid-rich regions is capable of being automated and used to rate the risk of plaque rupture based on autofluorescence decay dynamics and without the need for fluorescence intensity or contrast agents.

Measuring Evidence-Based Viral Respiratory Illness Mitigation Behaviors in Pregnant Populations: Development and Validation of a Short, Single-Factor Scale During the COVID-19 Pandemic.

OBJECTIVE: Researchers and public health professionals need to better understand individual engagement in coronavirus disease 2019 (COVID-19) mitigation behaviors to reduce the human and societal costs of the current pandemic and prepare for future respiratory pandemics. We suggest that developing measures of individual mitigation behaviors and testing them among high-risk individuals, including pregnant people, may help to reduce overall morbidity and mortality by quickly identifying targets for messaging around mitigation until sufficient vaccination uptake is reached. METHODS: We surveyed pregnant people in California over 2 waves of the COVID-19 pandemic to explore mitigation behaviors. We developed and validated a novel Viral Respiratory Illness Mitigation Scale (VRIMS). RESULTS: Seven measures loaded onto a single factor with good psychometric properties. The overall sample scale average was high over both waves, indicating that most pregnant Californians engaged in most of the strategies most of the time. Older participants, minoritized participants, those living in more urban contexts, and those surveyed during a surge reported engaging in these strategies most frequently. CONCLUSIONS: Clinicians and researchers should consider using reliable, validated measures like the VRIMS to identify individuals and communities that may benefit from additional education on reducing risk for COVID-19, future respiratory pandemics, or even seasonal flu.

Understanding COVID-19 vaccine uptake during pregnancy: 'Hesitance', knowledge, and evidence-based decision-making.

BACKGROUND: A key mitigation strategy to the COVID-19 pandemic has been the development and roll-out of vaccines. However, pregnant and lactating people were not included in initial vaccine trials and this population is hesitant to receive the vaccine, despite contrary recommendations from the American College of Obstetrics and Gynecology and the Centers for Disease Control and Prevention. Understanding the reasons behind this hesitancy is vital to promote vaccine uptake. METHODS: We surveyed pregnant people in California from December 2020 to January 2021 (n = 387) to describe cognitions and decision-making regarding COVID-19 vaccination. Using descriptive, regression-based analyses, we examined rates of planned uptake and reasoning among individuals who reported COVID-19 vaccine hesitancy. RESULTS: Overall, the pregnant Californians that we surveyed were aware of the COVID-19 vaccines. Of 387 participants, 43% reported planning to get the vaccine as soon as possible. The remaining 57% were hesitant: 27% responded that they would not receive the vaccine. Some demographic features did predict more COVID-19 vaccine hesitancy, particularly younger age (AOR = 0.95, p = 0.025) and living in a less urban context (AOR = 0.80, p = 0.041). Essential worker status also was associated with vaccine hesitancy. Having had, or intending to have, a flu vaccine was negatively associated with COVID-19 vaccine hesitancy (p < 0.001). The most commonly reported reason for COVID-19 vaccine hesitancy was "I don't know enough about the vaccine." Low levels of self-reported knowledge were highly predictive of hesitancy. CONCLUSIONS: Terms like "vaccine hesitance" and "anti-vax" do not adequately characterize decisions regarding delaying COVID-19 vaccination. Rather, these decisions are largely based on the lack of knowledge about the impacts of vaccination on pregnancy, fetal development, and later child wellbeing. This lack of knowledge should be countered by conversations between individual healthcare providers and their pregnant patients, and better inclusion of pregnant people and children in vaccine trials.

Goals for Reaching Optimal Wellness (GROWell): A clinical trial protocol of a digital dietary intervention for pregnant and postpartum people with prenatal overweight or obesity.

BACKGROUND: Excess gestational weight gain (EGWG) is associated with multiple pregnancy complications and health risks for birthing people and their infants. Likewise, postpartum weight retention (PPWR), or not losing all pregnancy weight, has long-term health consequences. EGWG among people who enter pregnancy with overweight or obesity have worse obstetric outcomes and increased PPWR compared to women who gain within Institute of Medicine guidelines. METHODS: This study protocol describes the details of a blinded, randomized clinical trial of GROWell: Goals for Reaching Optimal Wellness, a mHealth tool designed to improve diet quality among people who enter pregnancy with overweight or obese BMIs to help them achieve appropriate GWG and safe postpartum pregnancy weight loss. Individuals with overweight and obesity will be randomly assigned to an attention control or intervention arm. The intervention group will receive personalized, goal-oriented text messages regarding dietary choices, while the attention control group will receive text messages about healthy pregnancy, labor, delivery, and early infancy. Both groups will complete online surveys at baseline, follow up, 3 and 6 months postpartum. RESULTS AND DISCUSSION: Currently, 162 subjects have been enrolled. Outcomes associated with GWG and pregnancy are expected in late 2023, while outcomes on postpartum weight retention GROWell adherence are expected in late 2024. The results of this trial will support the use of an evidence-based mHealth tool to be integrated into clinical practice to reduce EGWG and PPWR among pregnant people with overweight and obese BMIs, a resource that is currently lacking. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT04449432. Registered on June 26, 2020.

From hybrid to fully remote clinical trial amidst the COVID-19 pandemic: Strategies to promote recruitment, retention, and engagement in a randomized mHealth trial.

Clinical trials worldwide were disrupted when the COVID-19 pandemic began in early 2020. Most intervention trials moved to some form of remote implementation due to restrictions on in-person research activities. Although the proportion of remote trials is growing, they remain the vast minority of studies in part due to few successful examples. Our team transitioned Goals for Reaching Optimal Wellness (GROWell), an NIH-funded (R01NR017659) randomized control trial (RCT; ClinicalTrials.gov identifier NCT04449432) originally designed as a hybrid intervention, into a fully remote clinical trial. GROWell is a digital dietary intervention for people who enter pregnancy with overweight or obesity. Primary outcomes include gestational weight gain and six-month postpartum weight retention. Strategies that we have tested, refined, and deployed include: (a) use of a HIPAA-compliant, web-based participant recruitment and engagement platform; (b) use of a HIPAA-compliant digital health platform to disseminate GROWell and conduct study visits (c) interconnectivity of these two platforms for seamless recruitment, consent, enrollment, intervention delivery, follow-up, and study team blinding; (d) detailed SMS messages to address initial challenges with protocol adherence; (e) email notifications alerting the study team about missed participant surveys so they can follow-up; (f) remuneration using email gift cards with recipient choice of vendor; and (g) geotargeting social media campaigns to improve participation of Black Indigenous and People of Color Communities. These strategies have resulted in screen failure rates improving by 7%, study task adherence improving by an average of 20-30% across study visits, and study completion rates of 82%. Researchers may consider some or all of these approaches in future remote mHealth trials.

Dynamic tissue analysis using time- and wavelength-resolved fluorescence spectroscopy for atherosclerosis diagnosis.

Simultaneous time- and wavelength-resolved fluorescence spectroscopy (STWRFS) was developed and tested for the dynamic characterization of atherosclerotic tissue ex vivo and arterial vessels in vivo. Autofluorescence, induced by a 337 nm, 700 ps pulsed laser, was split to three wavelength sub-bands using dichroic filters, with each sub-band coupled into a different length of optical fiber for temporal separation. STWRFS allows for fast recording/analysis (few microseconds) of time-resolved fluorescence emission in these sub-bands and rapid scanning. Distinct compositions of excised human atherosclerotic aorta were clearly discriminated over scanning lengths of several centimeters based on fluorescence lifetime and the intensity ratio between 390 and 452 nm. Operation of STWRFS blood flow was further validated in pig femoral arteries in vivo using a single-fiber probe integrated with an ultrasound imaging catheter. Current results demonstrate the potential of STWRFS as a tool for real-time optical characterization of arterial tissue composition and for atherosclerosis research and diagnosis.

Label-Free Visualization and Quantification of Biochemical Markers of Atherosclerotic Plaque Progression Using Intravascular Fluorescence Lifetime.

OBJECTIVES: This study aimed to systematically investigate whether plaque autofluorescence properties assessed with intravascular fluorescence lifetime imaging (FLIm) can provide qualitative and quantitative information about intimal composition and improve the characterization of atherosclerosis lesions. BACKGROUND: Despite advances in cardiovascular diagnostics, the analytic tools and imaging technologies currently available have limited capabilities for evaluating in situ biochemical changes associated with luminal surface features. Earlier studies of small number of samples have shown differences among the autofluorescence lifetime signature of well-defined lesions, but a systematic pixel-level evaluation of fluorescence signatures associated with various histological features is lacking and needed to better understand the origins of fluorescence contrast. METHODS: Human coronary artery segments (n = 32) were analyzed with a bimodal catheter system combining multispectral FLIm with intravascular ultrasonography compatible with in vivo coronary imaging. Various histological components present along the luminal surface (200-µm depth) were systematically tabulated (12 sectors) from each serial histological section (n = 204). Morphological information provided by ultrasonography allowed for the accurate registration of imaging data with histology data. The relationships between histological findings and FLIm parameters obtained from 3 spectral channels at each measurement location (n = 33,980) were characterized. RESULTS: Our findings indicate that fluorescence lifetime from different spectral bands can be used to quantitatively predict the superficial presence of macrophage foam cells (mFCs) (area under the receiver-operator characteristic curve: 0.94) and extracellular lipid content in advanced lesions (lifetime increase in 540-nm band), detect superficial calcium (lifetime decrease in 450-nm band area under the receiver-operator characteristic curve: 0.90), and possibly detect lesions consistent with active plaque formation such as pathological intimal thickening and healed thrombus regions (lifetime increase in 390-nm band). CONCLUSIONS: Our findings indicate that autofluorescence lifetime provides valuable information for characterizing atherosclerotic lesions in coronary arteries. Specifically, FLIm can be used to identify key phenomena linked with plaque progression (e.g., peroxidized-lipid-rich mFC accumulation and recent plaque formation).

Real-time diagnosis and visualization of tumor margins in excised breast specimens using fluorescence lifetime imaging and machine learning.

Tumor-free surgical margins are critical in breast-conserving surgery. In up to 38% of the cases, however, patients undergo a second surgery since malignant cells are found at the margins of the excised resection specimen. Thus, advanced imaging tools are needed to ensure clear margins at the time of surgery. The objective of this study was to evaluate a random forest classifier that makes use of parameters derived from point-scanning label-free fluorescence lifetime imaging (FLIm) measurements of breast specimens as a means to diagnose tumor at the resection margins and to enable an intuitive visualization of a probabilistic classifier on tissue specimen. FLIm data from fresh lumpectomy and mastectomy specimens from 18 patients were used in this study. The supervised training was based on a previously developed registration technique between autofluorescence imaging data and cross-sectional histology slides. A pathologist's histology annotations provide the ground truth to distinguish between adipose, fibrous, and tumor tissue. Current results demonstrate the ability of this approach to classify the tumor with 89% sensitivity and 93% specificity and to rapidly (∼ 20 frames per second) overlay the probabilistic classifier overlaid on excised breast specimens using an intuitive color scheme. Furthermore, we show an iterative imaging refinement that allows surgeons to switch between rapid scans with a customized, low spatial resolution to quickly cover the specimen and slower scans with enhanced resolution (400 µm per point measurement) in suspicious regions where more details are required. In summary, this technique provides high diagnostic prediction accuracy, rapid acquisition, adaptive resolution, nondestructive probing, and facile interpretation of images, thus holding potential for clinical breast imaging based on label-free FLIm.

Home-Based Primary Care Led-Outbreak Mitigation in Assisted Living Facilities in the First 100 Days of Coronavirus Disease 2019.

Residents of congregate care settings have been severely impacted by the current Coronavirus disease 2019 (COVID-19) pandemic. In this report, we describe the methods our home-based primary care practice has developed to mitigate the spread of COVID-19 in assisted living facilities (ALFs) and we present an initial evaluation of this innovation. Shortly after the first COVID-19 case was reported in the United States, our organization assembled an outbreak committee, designed to support the 1794 ALF residents and the 101 communities in which they reside. The committee led the development and deployment of a comprehensive COVID-19 prevention and suppression strategy. The average age of the cohort was 83 ± 11 years, and 74% were female. Seven individuals (0.4% of census) tested positive for SARS-CoV-2. The positive individuals were located in 3 ALFs, representing 3% of our total number of ALFs. There has been 1 death. Home-based primary care-led outbreak mitigation may be an enabler to suppress COVID-19 in ALFs.

Method for accurate registration of tissue autofluorescence imaging data with corresponding histology: a means for enhanced tumor margin assessment.

An important step in establishing the diagnostic potential for emerging optical imaging techniques is accurate registration between imaging data and the corresponding tissue histopathology typically used as gold standard in clinical diagnostics. We present a method to precisely register data acquired with a point-scanning spectroscopic imaging technique from fresh surgical tissue specimen blocks with corresponding histological sections. Using a visible aiming beam to augment point-scanning multispectral time-resolved fluorescence spectroscopy on video images, we evaluate two different markers for the registration with histology: fiducial markers using a 405-nm CW laser and the tissue block's outer shape characteristics. We compare the registration performance with benchmark methods using either the fiducial markers or the outer shape characteristics alone to a hybrid method using both feature types. The hybrid method was found to perform best reaching an average error of 0.78±0.67 mm. This method provides a profound framework to validate diagnostical abilities of optical fiber-based techniques and furthermore enables the application of supervised machine learning techniques to automate tissue characterization.

Automated detection of breast cancer in resected specimens with fluorescence lifetime imaging.

Re-excision rates for breast cancer lumpectomy procedures are currently nearly 25% due to surgeons relying on inaccurate or incomplete methods of evaluating specimen margins. The objective of this study was to determine if cancer could be automatically detected in breast specimens from mastectomy and lumpectomy procedures by a classification algorithm that incorporated parameters derived from fluorescence lifetime imaging (FLIm). This study generated a database of co-registered histologic sections and FLIm data from breast cancer specimens (N = 20) and a support vector machine (SVM) classification algorithm able to automatically detect cancerous, fibrous, and adipose breast tissue. Classification accuracies were greater than 97% for automated detection of cancerous, fibrous, and adipose tissue from breast cancer specimens. The classification worked equally well for specimens scanned by hand or with a mechanical stage, demonstrating that the system could be used during surgery or on excised specimens. The ability of this technique to simply discriminate between cancerous and normal breast tissue, in particular to distinguish fibrous breast tissue from tumor, which is notoriously challenging for optical techniques, leads to the conclusion that FLIm has great potential to assess breast cancer margins. Identification of positive margins before waiting for complete histologic analysis could significantly reduce breast cancer re-excision rates.

In vivo label-free structural and biochemical imaging of coronary arteries using an integrated ultrasound and multispectral fluorescence lifetime catheter system.

Existing clinical intravascular imaging modalities are not capable of accurate detection of critical plaque pathophysiology in the coronary arteries. This study reports the first intravascular catheter combining intravascular ultrasound (IVUS) with multispectral fluorescence lifetime imaging (FLIm) that enables label-free simultaneous assessment of morphological and biochemical features of coronary vessels in vivo. A 3.7 Fr catheter with a fiber-optic channel was constructed based on a 40 MHz clinical IVUS catheter. The ability to safely acquire co-registered FLIm-IVUS data in vivo using Dextran40 solution flushing was demonstrated in swine coronary arteries. FLIm parameters from the arterial wall were consistent with the emission of fluorophores present in healthy arterial wall (collagen, elastin). Additionally, structural and biochemical features from atherosclerotic lesions were acquired in ex vivo human coronary samples and corroborated with histological findings. Current results show that FLIm parameters linked to the amount of structural proteins (e.g. collagen, elastin) and lipids (e.g. foam cells, extracellular lipids) in the first 200 µm of the intima provide important biochemical information that can supplement IVUS data for a comprehensive assessment of plaques pathophysiology. The unique FLIm-IVUS system evaluated here has the potential to provide a comprehensive insight into atherosclerotic lesion formation, diagnostics and response to therapy.