Application of unsupervised deep learning algorithms for identification of specific clusters of chronic cough patients from EMR data.

BACKGROUND: Chronic cough affects approximately 10% of adults. The lack of ICD codes for chronic cough makes it challenging to apply supervised learning methods to predict the characteristics of chronic cough patients, thereby requiring the identification of chronic cough patients by other mechanisms. We developed a deep clustering algorithm with auto-encoder embedding (DCAE) to identify clusters of chronic cough patients based on data from a large cohort of 264,146 patients from the Electronic Medical Records (EMR) system. We constructed features using the diagnosis within the EMR, then built a clustering-oriented loss function directly on embedded features of the deep autoencoder to jointly perform feature refinement and cluster assignment. Lastly, we performed statistical analysis on the identified clusters to characterize the chronic cough patients compared to the non-chronic cough patients. RESULTS: The experimental results show that the DCAE model generated three chronic cough clusters and one non-chronic cough patient cluster. We found various diagnoses, medications, and lab tests highly associated with chronic cough patients by comparing the chronic cough cluster with the non-chronic cough cluster. Comparison of chronic cough clusters demonstrated that certain combinations of medications and diagnoses characterize some chronic cough clusters. CONCLUSIONS: To the best of our knowledge, this study is the first to test the potential of unsupervised deep learning methods for chronic cough investigation, which also shows a great advantage over existing algorithms for patient data clustering.

Development of a natural language processing algorithm to detect chronic cough in electronic health records.

BACKGROUND: Chronic cough (CC) is difficult to identify in electronic health records (EHRs) due to the lack of specific diagnostic codes. We developed a natural language processing (NLP) model to identify cough in free-text provider notes in EHRs from multiple health care providers with the objective of using the model in a rules-based CC algorithm to identify individuals with CC from EHRs and to describe the demographic and clinical characteristics of individuals with CC. METHODS: This was a retrospective observational study of enrollees in Optum's Integrated Clinical + Claims Database. Participants were 18-85 years of age with medical and pharmacy health insurance coverage between January 2016 and March 2017. A labeled reference standard data set was constructed by manually annotating 1000 randomly selected provider notes from the EHRs of enrollees with ≥ 1 cough mention. An NLP model was developed to extract positive or negated cough contexts. NLP, cough diagnosis and medications identified cough encounters. Patients with ≥ 3 encounters spanning at least 56 days within 120 days were defined as having CC. RESULTS: The positive predictive value and sensitivity of the NLP algorithm were 0.96 and 0.68, respectively, for positive cough contexts, and 0.96 and 0.84, respectively, for negated cough contexts. Among the 4818 individuals identified as having CC, 37% were identified using NLP-identified cough mentions in provider notes alone, 16% by diagnosis codes and/or written medication orders, and 47% through a combination of provider notes and diagnosis codes/medications. Chronic cough patients were, on average, 61.0 years and 67.0% were female. The most prevalent comorbidities were respiratory infections (75%) and other lower respiratory disease (82%). CONCLUSIONS: Our EHR-based algorithm integrating NLP methodology with structured fields was able to identify a CC population. Machine learning based approaches can therefore aid in patient selection for future CC research studies.

Neuromuscular Blockade and Reversal Practice Variability in the Outpatient Setting: Insights From US Utilization Patterns.

BACKGROUND: Neuromuscular blockade (NMB) is a critical part of many surgical procedures. Data on practice patterns of NMB agents (NMBAs) and NMB reversal in recent years in the US ambulatory surgical care setting are limited. METHODS: This retrospective analysis of US adult outpatients was conducted using the Premier Healthcare Database. We describe anesthesia practice trends in NMB management and assess the association of patient, procedural, and site characteristics with NMB reversal approach using multivariable logistic regression. RESULTS: Approximately 5.2 million outpatient surgical encounters involving NMB and 4.6 million involving rocuronium or vecuronium between January 2014 and June 2019 were included. Following the introduction of sugammadex to US clinical practice (~2016), there was an increased use of rocuronium or vecuronium and a decrease in succinylcholine alone. Before 2016, NMB was pharmacologically reversed with neostigmine in approximately two-thirds of outpatient encounters. Over time, active reversal increased; by 2019, 42.3% and 36.0% of encounters were reversed by neostigmine and sugammadex, respectively, with 21.7% undergoing spontaneous recovery. Choice of NMBA (rocuronium or vecuronium alone), time since 2016, obesity, peripheral vascular disease, and procedures on the digestive, ocular, and female genital systems (vs musculoskeletal procedures) were independently and positively associated with pharmacologic reversal (versus spontaneous reversal). Conversely, advanced age; Western geography; and cardiovascular, endocrine, hemic/lymphatic, respiratory, and ear, nose, and throat procedures were independently and negatively associated with pharmacologic reversal of NMB.Among pharmacologic reversals, time since 2016 was positively and independently associated with sugammadex compared with neostigmine (odds ratios [ORs], ranged from 1.8 in 2017 to 3.2, P < .0001 in 2019). Those administered rocuronium or vecuronium without succinylcholine, with increased age and history of certain comorbidities, and those undergoing ocular or respiratory procedures (compared with musculoskeletal) were positively associated with reversal with sugammadex and endocrine procedure negatively and independently associated with reversal with sugammadex. There was variability in the association of several factors with NMB reversal choices by geographic region, particularly in patients' race, ethnicity, and size of affiliated hospital. CONCLUSIONS: Overall, active pharmacological reversal of NMB increased in US adult outpatients following the introduction of sugammadex, although there remains significant practice variability. The multifactorial relationship between patient-, procedural-, and environmental-level characteristics and NMB management is rapidly evolving. Additional research on how these anesthesia practice patterns may be impacted by the shift to the ambulatory care setting and how they may impact patient outcomes and health disparities is warranted.

Rapid detection and identification of bacteria directly from whole blood with light scattering spectroscopy based biosensor.

Bacterial infections are one of the major causes of death worldwide. The identification of a bacterial species that is the source of an infection generally takes a long time, and often exceeds the treatment window for seriously ill patients. Many of these deaths are preventable if the bacterial species can be identified quickly. Here we present an optical spectroscopic method for rapid detection and identification of bacteria directly from whole blood using a light scattering spectroscopy technique. This technique was originally developed to detect pre-cancerous changes in epithelial tissues, characterize changes in tissue on the cellular scale, and characterize biological structures comparable to or smaller than a single wavelength. We demonstrate here that not only can an inexpensive light scattering spectroscopy-based biosensor rapidly detect and identify four bacteria species in the blood, responsible for the majority of death causing infections, but that species-level identification can potentially be made based on approximately one thousand bacterial cells per milliliter of blood. Observing entire colonies or performing susceptibility testing is therefore not required.

Multispectral Endoscopy with Light Gating for Early Cancer Detection.

This paper reports the application of endoscopic light scattering spectroscopy (LSS) with light gating to detect malignancies in the biliary and pancreatic ducts, and also reviews the application of endoscopic LSS for differentiating cystic neoplasms in the pancreas and detecting invisible dysplasia in Barrett's esophagus. Information about tissue structure within the superficial epithelium where malignancy starts is present within the spectra of reflected light. Fortunately, this component of the reflected light is not yet randomized. However multiple scattering randomizes the signal from the underlying connective tissue which obscures the desired signal. In order to extract diagnostic information from the reflected signal the multiple scattering component related to connective tissue scattering and absorption must be removed. This is accomplished using described here spatial or polarization gating implemented with endoscopically compatible fiber optic probes.

Picoanalysis of Drugs in Biofluids with Quantitative Label-Free Surface-Enhanced Raman Spectroscopy.

The enormous increase of Raman signal in the vicinity of metal nanoparticles allows surface-enhanced Raman spectroscopy (SERS) to be employed for label-free detection of substances at extremely low concentrations. However, the ultimate potential of label-free SERS to identify pharmaceutical compounds at low concentrations, especially in relation to biofluid sensing, is far from being fully realized. Opioids are a particular challenge for rapid clinical identification because their molecular structural similarities prevent their differentiation with immunolabeling approaches. In this paper, a new method called quantitative label-free SERS (QLF-SERS) which involves the formation of halide-conjugated gold nanoclusters trapping the analyte of interest near the SERS hot spots is reported, and it is demonstrated that it yields a 105 fold improvement in the detection limit over previously reported results for the entire class of clinically relevant opioids and their metabolites. Measurements of opioid concentrations in multicomponent mixtures are also demonstrated. QLF-SERS has comparable detection limits as currently existing laboratory urine drug testing techniques but is significantly faster and inexpensive and, therefore, can be easily adapted as part of a rapid clinical laboratory routine.

Spectral biomarkers for chemoprevention of colonic neoplasia: a placebo-controlled double-blinded trial with aspirin.

OBJECTIVE: A major impediment to translating chemoprevention to clinical practice has been lack of intermediate biomarkers. We previously reported that rectal interrogation with low-coherence enhanced backscattering spectroscopy (LEBS) detected microarchitectural manifestations of field carcinogenesis. We now wanted to ascertain if reversion of two LEBS markers spectral slope (SPEC) and fractal dimension (FRAC) could serve as a marker for chemopreventive efficacy. DESIGN: We conducted a multicentre, prospective, randomised, double-blind placebo-controlled, clinical trial in subjects with a history of colonic neoplasia who manifested altered SPEC/FRAC in histologically normal colonic mucosa. Subjects (n=79) were randomised to 325 mg aspirin or placebo. The primary endpoint changed in FRAC and SPEC spectral markers after 3 months. Mucosal levels of prostaglandin E2 (PGE2) and UDP-glucuronosyltransferase (UGT)1A6 genotypes were planned secondary endpoints. RESULTS: At 3 months, the aspirin group manifested alterations in SPEC (48.9%, p=0.055) and FRAC (55.4%, p=0.200) with the direction towards non-neoplastic status. As a measure of aspirin's pharmacological efficacy, we assessed changes in rectal PGE2 levels and noted that it correlated with SPEC and FRAC alterations (R=-0.55, p=0.01 and R=0.57, p=0.009, respectively) whereas there was no significant correlation in placebo specimens. While UGT1A6 subgroup analysis did not achieve statistical significance, the changes in SPEC and FRAC to a less neoplastic direction occurred only in the variant consonant with epidemiological evidence of chemoprevention. CONCLUSIONS: We provide the first proof of concept, albeit somewhat underpowered, that spectral markers reversion mirrors antineoplastic efficacy providing a potential modality for titration of agent type/dose to optimise chemopreventive strategies in clinical practice. TRIAL NUMBER: NCT00468910.

Post-operative urinary retention is impacted by neuromuscular block reversal agent choice: A retrospective cohort study in US hospital setting.

STUDY OBJECTIVE: Perioperative neuromuscular blocking agents are pharmacologically reversed to minimize complications associated with residual neuromuscular block. Neuromuscular block reversal with anticholinesterases (e.g., neostigmine) require coadministration of an anticholinergic agent (e.g., glycopyrrolate) to mitigate muscarinic activity; however, sugammadex, devoid of cholinergic activity, does not require anticholinergic coadministration. Single-institution studies have found decreased incidence of post-operative urinary retention associated with sugammadex reversal. This study used a multicenter database to better understand the association between neuromuscular block reversal technique and post-operative urinary retention. DESIGN: Retrospective cohort study utilizing large healthcare database. SETTING: Non-profit, non-governmental and community and teaching hospitals and health systems from rural and urban areas. PATIENTS: 61,898 matched adult inpatients and 95,500 matched adult outpatients. INTERVENTIONS: Neuromuscular block reversal with sugammadex or neostigmine plus glycopyrrolate. MEASUREMENTS: Incidence of post-operative urinary retention by neuromuscular block reversal agent and the independent association of neuromuscular block reversal technique and risk of post-operative urinary retention. MAIN RESULTS: The incidence of post-operative urinary retention was 2-fold greater among neostigmine with glycopyrrolate compared to sugammadex patients (5.0% vs 2.4% inpatients; 0.9% vs 0.4% outpatients; both p < 0.0001). Multivariable logistic regression identified reversal with neostigmine to be independently associated with greater risk of post-operative urinary retention (inpatients: odds ratio, 2.20; 95% confidence interval, 2.00 to 2.41; p < 0.001; outpatients: odds ratio, 2.57; 95% confidence interval, 2.13 to 3.10; p < 0.001). Post-operative urinary retention-related visits within 2 days following discharge were five-fold higher among those reversed with neostigmine than sugammadex among inpatients (0.05% vs. 0.01%, respectively; p = 0.018) and outpatients (0.5% vs. 0.1%; p < 0.0001). CONCLUSION: Though this study suggests that neuromuscular block reversal with neostigmine can increase post-operative urinary retention risk, additional studies are needed to fully understand the association.

Real-world evaluation of imipenem/cilastatin/relebactam across US medical centres.

We assessed 160 patients who received imipenem/cilastatin/relebactam for ≥2 days. At treatment initiation, the median Charlson Comorbidity Index was 5, 45% were in the intensive care unit, and 19% required vasopressor support. The in-hospital mortality rate was 24%. These data advance our understanding of real-world indications and outcomes of imipenem/cilastatin/relebactam use.

Machine learning to identify chronic cough from administrative claims data.

Accurate identification of patient populations is an essential component of clinical research, especially for medical conditions such as chronic cough that are inconsistently defined and diagnosed. We aimed to develop and compare machine learning models to identify chronic cough from medical and pharmacy claims data. In this retrospective observational study, we compared 3 machine learning algorithms based on XG Boost, logistic regression, and neural network approaches using a large claims and electronic health record database. Of the 327,423 patients who met the study criteria, 4,818 had chronic cough based on linked claims-electronic health record data. The XG Boost model showed the best performance, achieving a Receiver-Operator Characteristic Area Under the Curve (ROC-AUC) of 0.916. We selected a cutoff that favors a high positive predictive value (PPV) to minimize false positives, resulting in a sensitivity, specificity, PPV, and negative predictive value of 18.0%, 99.6%, 38.7%, and 98.8%, respectively on the held-out testing set (n = 82,262). Logistic regression and neural network models achieved slightly lower ROC-AUCs of 0.907 and 0.838, respectively. The XG Boost and logistic regression models maintained their robust performance in subgroups of individuals with higher rates of chronic cough. Machine learning algorithms are one way of identifying conditions that are not coded in medical records, and can help identify individuals with chronic cough from claims data with a high degree of classification value.

Real-world treatment patterns and clinical outcomes for chemotherapy-based regimens in first-line MSI-H/dMMR metastatic colorectal cancer.

MICRO ABSTRACT: This retrospective observational study assessed real-world treatment patterns and clinical outcomes among first-line MSI-H/dMMR metastatic colorectal cancer patients. Of 150 patients in the study cohort, 38.7% were treated with chemotherapy and 61.3% with chemotherapy + EGFR/VEGF inhibitor (EGFRi/VEGFi). Clinical outcomes were better among patients who received chemotherapy + EGFR/VEGF inhibitor than those who received chemotherapy. INTRODUCTION: Prior to pembrolizumab approval in first-line (1L) treatment of MSI-H/dMMR metastatic colorectal cancer (mCRC), patients were managed with chemotherapy with or without an EGFRi or VEGFi, agnostic of biomarker testing or mutation status. This study assessed real-world treatment patterns and clinical outcomes among 1L MSI-H/dMMR mCRC patients treated with standard of care (SOC). PATIENTS AND METHODS: Retrospective observational evaluation of patients ≥18 years diagnosed with stage IV MSI-H/dMMR mCRC who received community-based oncology care. Eligible patients were identified (01-Jun-2017 - 29-Feb-2020) and followed longitudinally until 31-Aug-2020/the last patient record/date of death. Descriptive statistics and Kaplan-Meier analyses were conducted. RESULTS: Of 150 1L MSI-H/dMMR mCRC patients, 38.7% were treated with chemotherapy and 61.3% with chemotherapy + EGFRi/VEGFi. Accounting for censoring, the overall median real-world time to treatment discontinuation (95% CI) was 5.3 (4.4, 5.8) months; 3.0 (2.1, 4.4) and 6.2 (5.5, 7.6) months in the chemotherapy and chemotherapy + EGFRi/VEGFi cohorts, respectively. The combined median overall survival was 27.7 (23.2, not reached [NR]) months; 25.3 (14.5, NR) and 29.8 (23.2, NR) months in the chemotherapy and chemotherapy + EGFRi/VEGFi cohorts, respectively. The overall median real-world progression-free survival was 6.8 (5.3, 7.8) months; 4.2 (2.8, 6.1) and 7.7 (6.1, 10.2) months in the chemotherapy and chemotherapy + EGFRi/VEGFi cohorts, respectively. CONCLUSIONS: 1L MSI-H/dMMR mCRC patients receiving chemotherapy with EGFRi/VEGFi had better outcomes than those receiving only chemotherapy. An unmet need and opportunity to improve outcomes exists in this population that may be addressed by newer treatments like immunotherapies.

Real-world treatment patterns and outcomes among individuals receiving first-line pembrolizumab therapy for recurrent/metastatic head and neck squamous cell carcinoma.

Background: Pembrolizumab, a PD-1 immune checkpoint inhibitor, is approved as first-line (1L) treatment for recurrent or metastatic head and neck squamous cell carcinoma (R/M HNSCC) as monotherapy or in combination with platinum and 5-fluorouracil chemotherapy. Limited data exist on the use of these regimens in real-world settings. Objective: Our primary objectives were to describe baseline characteristics and real-world overall survival (rwOS), time on treatment (rwToT), and time to next treatment (rwTTNT) among individuals with R/M HNSCC receiving approved 1L pembrolizumab therapies. We also aimed to identify baseline factors associated with choice of 1L pembrolizumab therapy and with rwOS. Methods: This was a retrospective cohort study of adults with R/M HNSCC receiving 1L pembrolizumab monotherapy or pembrolizumab plus chemotherapy. We used Kaplan-Meier analyses to assess real-world outcomes, logistic regression modeling to identify factors associated with choice of 1L pembrolizumab therapy, and Cox proportional hazards models to identify factors associated with rwOS. Results: The study population included 431 individuals receiving 1L pembrolizumab monotherapy and 215 receiving 1L pembrolizumab plus chemotherapy. The use of 1L pembrolizumab monotherapy was associated with higher baseline combined positive score for PD-L1 expression, older age, higher Eastern Cooperative Oncology Group performance status (ECOG PS), laryngeal tumor site, and human papillomavirus (HPV)-positive tumor status. The pembrolizumab monotherapy group had a median (95% CI) rwOS of 12.1 (9.2-15.1) months, rwToT of 4.2 (3.5-4.6) months, and rwTTNT of 6.5 (5.4-7.4) months. Among this group, HPV-positive tumor status and lower ECOG PS were associated with longer rwOS, and oral cavity tumor site with shorter rwOS. The pembrolizumab plus chemotherapy cohort had a median (95% CI) rwOS of 11.9 (9.0-16.0) months, rwToT of 4.9 (3.8-5.6) months, and rwTTNT of 6.6 (5.8-8.3) months. In this group, HPV-positive tumor status was associated with longer rwOS. Conclusions: This study adds to clinical trial data by summarizing real-world treatment outcomes with 1L pembrolizumab-containing therapies in a more heterogeneous population. Overall survival outcomes in both treatment groups were similar to those observed in the registration clinical trial. These findings support the use of pembrolizumab as standard of care for R/M HNSCC.

Evaluation of a Natural Language Processing Model to Identify and Characterize Patients in the United States With High-Risk Non-Muscle-Invasive Bladder Cancer.

PURPOSE: Treatment of non-muscle-invasive bladder cancer (NMIBC) is guided by risk stratification using clinical and pathologic criteria. This study aimed to develop a natural language processing (NLP) model for identifying patients with high-risk NMIBC retrospectively from unstructured electronic medical records (EMRs) and to apply the model to describe patient and tumor characteristics. METHODS: We used three independent EMR-derived data sets including adult patients with a bladder cancer diagnosis in 2011-2020 for NLP model development and training (n = 140), validation (n = 697), and application for the retrospective cohort analysis (n = 4,402). Deep learning methods were used to train NLP recognition of medical chart terminology to identify seven high-risk NMIBC criteria; model performance was assessed using the F1 score, weighted across features. An algorithm was then used to classify each patient as high-risk NMIBC (yes/no). Manually reviewed records served as the gold standard. RESULTS: The F1 scores after model training were >0.7 for all but one uncommon feature (prostatic urethral involvement). The highest area under the receiver operating curves (AUC) was observed for Ta (0.897) and T1 (0.897); the lowest AUC was for carcinoma in situ (CIS; 0.617). For high-risk NMIBC classification, positive predictive value was 79.4%, negative predictive value was 93.2%, and false-positive rate was 8.9%. Sensitivity and specificity were 83.7% and 91.1%, respectively. Of 748 patients manually confirmed as having high-risk NMIBC, 196 (26%) had CIS (of whom 19% also had T1 and 23% also had Ta disease); 552 tumors (74%) had no associated CIS. CONCLUSION: The NLP model, combined with a rule-based algorithm, identified high-risk NMIBC with good performance and will enable future work to study real-world treatment patterns and clinical outcomes for high-risk NMIBC.

Corrigendum: Real-world treatment patterns and outcomes among individuals receiving first-line pembrolizumab therapy for recurrent/metastatic head and neck squamous cell carcinoma.

[This corrects the article DOI: 10.3389/fonc.2023.1160144.].

A fiber optic probe design to measure depth-limited optical properties in-vivo with low-coherence enhanced backscattering (LEBS) spectroscopy.

Low-coherence enhanced backscattering (LEBS) spectroscopy is an angular resolved backscattering technique that is sensitive to sub-diffusion light transport length scales in which information about scattering phase function is preserved. Our group has shown the ability to measure the spatial backscattering impulse response function along with depth-selective optical properties in tissue ex-vivo using LEBS. Here we report the design and implementation of a lens-free fiber optic LEBS probe capable of providing depth-limited measurements of the reduced scattering coefficient in-vivo. Experimental measurements combined with Monte Carlo simulation of scattering phantoms consisting of polystyrene microspheres in water are used to validate the performance of the probe. Additionally, depth-limited capabilities are demonstrated using Monte Carlo modeling and experimental measurements from a two-layered phantom.

Spectral Imaging with Scattered Light: From Early Cancer Detection to Cell Biology.

This article reports the evolution of scanning spectral imaging techniques using scattered light for minimally invasive detection of early cancerous changes in tissue and cell biology applications. Optical spectroscopic techniques have shown promising results in the diagnosis of disease on a cellular scale. They do not require tissue removal, can be performed in vivo, and allow for real time diagnoses. Fluorescence and Raman spectroscopy are most effective in revealing molecular properties of tissue. Light scattering spectroscopy (LSS) relates the spectroscopic properties of light elastically scattered by small particles, such as epithelial cell nuclei and organelles, to their size, shape and refractive index. It is capable of characterizing the structural properties of tissue on cellular and sub-cellular scales. However, in order to be useful in the detection of early cancerous changes which are otherwise not visible to the naked eye, it must rapidly survey a comparatively large area while simultaneously detecting these cellular changes. Both goals are achieved by combining LSS with spatial scanning imaging. Two examples are described in this article. The first reviews a clinical system for screening patients with Barrett's esophagus. The second presents a novel advancement in confocal light absorption and scattering spectroscopic (CLASS) microscopy.

Polarized Enhanced Backscattering Spectroscopy for Characterization of Biological Tissues at Subdiffusion Length-scales.

Since the early 1980's, the enhanced backscattering (EBS) phenomenon has been well-studied in a large variety of non-biological materials. Yet, until recently the use of conventional EBS for the characterization of biological tissue has been fairly limited. In this work we detail the unique ability of EBS to provide spectroscopic, polarimetric, and depth-resolved characterization of biological tissue using a simple backscattering instrument. We first explain the experimental and numerical procedures used to accurately measure and model the full azimuthal EBS peak shape in biological tissue. Next we explore the peak shape and height dependencies for different polarization channels and spatial coherence of illumination. We then illustrate the extraordinary sensitivity of EBS to the shape of the scattering phase function using suspensions of latex microspheres. Finally, we apply EBS to biological tissue samples in order to measure optical properties and observe the spatial length-scales at which backscattering is altered in early colon carcinogenesis.

Monte Carlo model of the penetration depth for polarization gating spectroscopy: influence of illumination-collection geometry and sample optical properties.

Polarization-gating has been widely used to probe superficial tissue structures, but the penetration depth properties of this method have not been completely elucidated. This study employs a polarization-sensitive Monte Carlo method to characterize the penetration depth statistics of polarization-gating. The analysis demonstrates that the penetration depth depends on both the illumination-collection geometry [illumination-collection area (R) and collection angle (θ(c))] and on the optical properties of the sample, which include the scattering coefficient (µ(s)), absorption coefficient (µ(a)), anisotropy factor (g), and the type of the phase function. We develop a mathematical expression relating the average penetration depth to the illumination-collection beam properties and optical properties of the medium. Finally, we quantify the sensitivity of the average penetration depth to changes in optical properties for different geometries of illumination and collection. The penetration depth model derived in this study can be applied to optimizing application-specific fiber-optic probes to target a sampling depth of interest with minimal sensitivity to the optical properties of the sample.

Quantification of nanoscale density fluctuations by electron microscopy: probing cellular alterations in early carcinogenesis.

Most cancers are curable if they are diagnosed and treated at an early stage. Recent studies suggest that nanoarchitectural changes occur within cells during early carcinogenesis and that such changes precede microscopically evident tissue alterations. It follows that the ability to comprehensively interrogate cell nanoarchitecture (e.g., macromolecular complexes, DNA, RNA, proteins and lipid membranes) could be critical to the diagnosis of early carcinogenesis. We present a study of the nanoscale mass-density fluctuations of biological tissues by quantifying their degree of disorder at the nanoscale. Transmission electron microscopy images of human tissues are used to construct corresponding effective disordered optical lattices. The properties of nanoscale disorder are then studied by statistical analysis of the inverse participation ratio (IPR) of the spatially localized eigenfunctions of these optical lattices at the nanoscale. Our results show an increase in the disorder of human colonic epithelial cells in subjects harboring early stages of colon neoplasia. Furthermore, our findings strongly suggest that increased nanoscale disorder correlates with the degree of tumorigenicity. Therefore, the IPR technique provides a practicable tool for the detection of nanoarchitectural alterations in the earliest stages of carcinogenesis. Potential applications of the technique for early cancer screening and detection are also discussed.

Alternate formulation of enhanced backscattering as phase conjugation and diffraction: derivation and experimental observation.

Enhanced backscattering (EBS), also known as weak localization of light, is derived using the Huygens-Fresnel principle and backscattering is generally shown to be the sum of an incoherent baseline and a phase conjugated portion of the incident wave that forms EBS. The phase conjugated portion is truncated by an effective aperture described by the probability function P(s) of coherent path-pair separations. P(s) is determined by the scattering properties of the medium and so characterization of EBS can be used for metrology of scattering materials. A three dimensional intensity peak is predicted in free space at a point conjugate to the source and is experimentally observed.