RESUMEN

Severe joint infections, such as septic arthritis, require rapid diagnostic testing of the synovial fluid aspirated from joints level so that a surgical team can be assembled quickly. We present a diffuse reflectance spectroscopy (DRS) system for noncontact determination of infection. Using a light-tight syringe holder and fiber optic probe, diffusely reflected light from 475 to 655 nm was acquired from 18 patient samples through the wall of a syringe in a noncontact and sterile manner. We determined the reflectance ratios at two different wavelengths-R490/R600 and R580/R600 and found statistically significant differences (p < 0.05) in both ratios between the infected and noninfected groups. Critically, the R490/R600 and R580/R600 ratios were significantly correlated with clinical biomarkers-the white blood cell (WBC) and red blood cell (RBC) counts, respectively. This study demonstrates the potential of DRS as a rapid diagnostic tool for joint infections.

RESUMEN

Background and objective: A positive surgical margin (PSM) occurs in up to 32% of patients undergoing robot-assisted radical prostatectomy (RARP). Diffuse reflectance spectroscopy (DRS), which measures tissue composition according to its optical properties, can potentially be used for real-time PSM detection during RARP. Our objective was to assess the feasibility of DRS in distinguishing prostate cancer from benign tissue in RARP specimens. Methods: In a single-center prospective study, DRS measurements were taken ex vivo for RARP specimens from 59 patients with biopsy-proven prostate carcinoma. Discriminating features from the DRS spectra were used to create a machine learning-based classification algorithm. The data were split patient-wise into training (70%) and testing (30%) sets, with ten iterations to ensure algorithm robustness. The average sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) from ten classification iterations were calculated. Key findings and limitations: We collected 542 DRS measurements, of which 53% were tumor and 47% were healthy-tissue measurements. Twenty discriminating features from the DRS spectra were used as the input for a support vector machine model. This model achieved average sensitivity of 89%, specificity of 82%, accuracy of 85%, and AUC of 0.91 for the test set. Limitations include the binary label input for classification. Conclusions and clinical implications: DRS can potentially discriminate prostate cancer from benign tissue. Before implementing the technique in clinical practice, further research is needed to assess its performance on heterogeneous tissue volumes and measurements from the prostate surface. Patient summary: We looked at the ability of a technique called diffuse reflectance spectroscopy to guide surgeons in discriminating prostate cancer tissue from benign prostate tissue in real time during prostate cancer surgery. Our study showed promising results in an experimental setting. Future research will focus on bringing this technique to clinical practice.

RESUMEN

A new, versatile, and straightforward vapor phase deposition (VPD) approach was used to prepare continuous stationary phase gradients (cSPGs) on silica thin-layer chromatography (TLC) plates using phenyldimethylchlorosilane (PDCS) as a precursor. A mixture of paraffin oil and PDCS was placed at the bottom of an open-ended rectangular chamber, allowing the reactive silanes to evaporate and freely diffuse under a controlled atmosphere. As the volatile silane diffused across the length of the TLC plate, it reacted with the surface silanol groups thus functionalizing the surface in a gradient fashion. Characterization of the gradient TLC plates was done through UV visualization and diffuse reflectance spectroscopy (DRS). Visualizing the fluorescent gradient plates under UV radiation shows the clear presence of a gradient with the side closest to the vapor source undergoing the most modification. More quantitative characterization of the shape of the gradient was provided by DRS. The DRS showed that the degree of modification and shape of the gradient was dependent on the concentration of silane, VPD time, and relative humidity. To evaluate the chromatographic performance, a mixture of three aromatic compounds (acetaminophen (A), aspirin (As), and 3-hydroxy-2-naphthoic acid (3H)) was spotted on the high (GHP) and low phenyl (GLP) ends of the gradient TLC plates and the results compared to the separations carried out on unmodified and uniformly modified plates. The GHP TLC plates showed retention factors (Rf) of 0.060 ± 0.006, 0.391 ± 0.006, and 0.544 ± 0.006, whereas the unmodified plate displayed Rf values of 0.059 ± 0.006, 0.092 ± 0.003, and 0.037 ± 0.002 for the analytes A, As, and 3H, respectively. From the Rf values, it was observed that each modified plate exhibited different selectivity for the analytes. The GHP TLC plates exhibited better separation performance, and improved resolution compared to the GLP, unmodified, and uniformly modified plates. Overall, VPD is a new, cost-effective method for creating a gradient on the stationary phase which has the potential to advance chromatographic separation capabilities.

Asunto(s)

RESUMEN

Significance: Despite the widespread use of photodynamic therapy in clinical practice, there is a lack of personalized methods for assessing the sufficiency of photodynamic exposure on tumors, depending on tissue parameters that change during light irradiation. This can lead to different treatment results. Aim: The objective of this article was to conduct a comprehensive review of devices and methods employed for the implicit dosimetric monitoring of personalized photodynamic therapy for tumors. Methods: The review included 88 peer-reviewed research articles published between January 2010 and April 2024 that employed implicit monitoring methods, such as fluorescence imaging and diffuse reflectance spectroscopy. Additionally, it encompassed computer modeling methods that are most often and successfully used in preclinical and clinical practice to predict treatment outcomes. The Internet search engine Google Scholar and the Scopus database were used to search the literature for relevant articles. Results: The review analyzed and compared the results of 88 peer-reviewed research articles presenting various methods of implicit dosimetry during photodynamic therapy. The most prominent wavelengths for PDT are in the visible and near-infrared spectral range such as 405, 630, 660, and 690 nm. Conclusions: The problem of developing an accurate, reliable, and easily implemented dosimetry method for photodynamic therapy remains a current problem, since determining the effective light dose for a specific tumor is a decisive factor in achieving a positive treatment outcome.

RESUMEN

Significance: We assess the feasibility of using diffuse reflectance spectroscopy (DRS) and coherent anti-Stokes Raman scattering spectroscopy (CARS) as optical tools for human brain tissue identification during deep brain stimulation (DBS) lead insertion, thereby providing a promising avenue for additional real-time neurosurgical guidance. Aim: We developed a system that can acquire CARS and DRS spectra during the DBS surgery procedure to identify the tissue composition along the lead trajectory. Approach: DRS and CARS spectra were acquired using a custom-built optical probe integrated in a commercial DBS lead. The lead was inserted to target three specific regions in each of the brain hemispheres of a human cadaver. Spectra were acquired during the lead insertion at constant position increments. Spectra were analyzed to classify each spectrum as being from white matter (WM) or gray matter (GM). The results were compared with tissue classification performed on histological brain sections. Results: DRS and CARS spectra obtained using the optical probe can identify WM and GM during DBS lead insertion. The tissue composition along the trajectory toward a specific target is unique and can be differentiated by the optical probe. Moreover, the results obtained with principal component analysis suggest that DRS might be able to detect the presence of blood due to the strong optical absorption of hemoglobin. Conclusions: It is possible to use optical measurements from the DBS lead during surgery to identify WM and GM and possibly the presence of blood in human brain tissue. The proposed optical tool could inform the surgeon during the lead placement if the lead has reached the target as planned. Our tool could eventually replace microelectrode recordings, which would streamline the process and reduce surgery time. Further developments are required to fully integrate these tools into standard clinical procedures.

RESUMEN

Background: In brain tumor surgery, maximal tumor resection is typically desired. This is complicated by infiltrative tumor cells which cannot be visually distinguished from healthy brain tissue. Optical methods are an emerging field that can potentially revolutionize brain tumor surgery through intraoperative differentiation between healthy and tumor tissues. Methods: This study aimed to systematically explore and summarize the existing literature on the use of Raman Spectroscopy (RS), Hyperspectral Imaging (HSI), Optical Coherence Tomography (OCT), and Diffuse Reflectance Spectroscopy (DRS) for brain tumor detection. MEDLINE, Embase, and Web of Science were searched for studies evaluating the accuracy of these systems for brain tumor detection. Outcome measures included accuracy, sensitivity, and specificity. Results: In total, 44 studies were included, covering a range of tumor types and technologies. Accuracy metrics in the studies ranged between 54 and 100% for RS, 69 and 99% for HSI, 82 and 99% for OCT, and 42 and 100% for DRS. Conclusions: This review provides insightful evidence on the use of optical methods in distinguishing tumor from healthy brain tissue.

RESUMEN

OBJECTIVES: The aim of this work is to assess the performance of multimodal spectroscopic approach combined with single core optical fiber for detection of bladder cancer during surgery in vivo. METHODS: Multimodal approach combines diffuse reflectance spectroscopy (DRS), fluorescence spectroscopy in the visible (405 nm excitation) and near-infrared (NIR) (690 nm excitation) ranges, and high-wavenumber Raman spectroscopy. All four spectroscopic methods were combined in a single setup. For 21 patients with suspected bladder cancer or during control cystoscopy optical spectra of bladder cancer, healthy bladder wall tissue and/or scars were measured. Classification of cancerous and healthy bladder tissue was performed using machine learning methods. RESULTS: Statistically significant differences in relative total haemoglobin content, oxygenation, scattering, and visible fluorescence intensity were found between tumor and normal tissues. The combination of DRS and visible fluorescence spectroscopy allowed detecting cancerous tissue with sensitivity and specificity of 78% and 91%, respectively. The addition of features extracted from NIR fluorescence and Raman spectra did not improve the quality of classification. CONCLUSIONS: This study demonstrates that multimodal spectroscopic approach allows increasing sensitivity and specificity of bladder cancer detection in vivo. The developed approach does not require special probes and can be used with single-core optical fibers applied for laser surgery.

Asunto(s)

RESUMEN

BACKGROUND: Quantification of macrosteatosis (MS) in the liver is important given that it has shown to directly correlate with adverse post-liver transplant (LT) outcomes. With advances in medical technology and an implicit understanding of pathology, noninvasive methods of quantitatively assessing MS are in various stages of development. Each of these methods is based on the physical principles of differences between a fat-laden hepatocyte and a normal one. METHODS: In this regard, after a proof-of-concept study on a prototype for a simple, real-time, handheld device using the principle of diffuse reflectance spectroscopy, this study presents an upgraded point-of-care (POC) device for the noninvasive assessment of hepatic MS in liver donors. RESULTS: The device was validated on cohort of donor livers and showed a sensitivity (0.0021 V/% fat) and highly correlated (r = 0.9868, P < .0001) with gold-standard liver biopsy. Results showed that this upgraded POC device provides a reliable method for the noninvasive assessment of hepatic MS, which is crucial for selecting suitable donor livers for LT. CONCLUSION: The device has the potential to be an invaluable apparatus at the hands of the organ-retrieving surgeon. It is noninvasive, portable (handheld), and economic; provides real-time readings of the percentage of MS; and can be efficaciously handled by any member of the organ-retrieving team.

Asunto(s)

RESUMEN

Significance: During breast-conserving surgeries, it is essential to evaluate the resection margins (edges of breast specimen) to determine whether the tumor has been removed completely. In current surgical practice, there are no methods available to aid in accurate real-time margin evaluation. Aim: In this study, we investigated the diagnostic accuracy of diffuse reflectance spectroscopy (DRS) combined with tissue classification models in discriminating tumorous tissue from healthy tissue up to 2 mm in depth on the actual resection margin of in vivo breast tissue. Approach: We collected an extensive dataset of DRS measurements on ex vivo breast tissue and in vivo breast tissue, which we used to develop different classification models for tissue classification. Next, these models were used in vivo to evaluate the performance of DRS for tissue discrimination during breast conserving surgery. We investigated which training strategy yielded optimum results for the classification model with the highest performance. Results: We achieved a Matthews correlation coefficient of 0.76, a sensitivity of 96.7% (95% CI 95.6% to 98.2%), a specificity of 90.6% (95% CI 86.3% to 97.9%) and an area under the curve of 0.98 by training the optimum model on a combination of ex vivo and in vivo DRS data. Conclusions: DRS allows real-time margin assessment with a high sensitivity and specificity during breast-conserving surgeries.

Asunto(s)

RESUMEN

Significance: Treatment planning for light-based therapies including photodynamic therapy requires tissue optical property knowledge. This is recoverable with spatially resolved diffuse reflectance spectroscopy (DRS) but requires precise source-detector separation (SDS) determination and time-consuming simulations. Aim: An artificial neural network (ANN) to map from DRS at multiple SDS to optical properties was created. This trained ANN was adapted to fiber-optic probes with varying SDS using transfer learning (TL). Approach: An ANN mapping from measurements to Monte Carlo simulation to optical properties was created with one fiber-optic probe. A second probe with different SDS was used for TL algorithm creation. Data from a third were used to test this algorithm. Results: The initial ANN recovered absorber concentration with RMSE=0.29 µM (7.5% mean error) and µs' at 665 nm (µs,665') with RMSE=0.77 cm-1 (2.5% mean error). For probe 2, TL significantly improved absorber concentration (0.38 versus 1.67 µM RMSE, p=0.0005) and µ's,665 (0.71 versus 1.8 cm-1 RMSE, p=0.0005) recovery. A third probe also showed improved absorber (0.7 versus 4.1 µM RMSE, p<0.0001) and µs,665' (1.68 versus 2.08 cm-1 RMSE, p=0.2) recovery. Conclusions: TL-based probe-to-probe calibration can rapidly adapt an ANN created for one probe to similar target probes, enabling accurate optical property recovery with the target probe.

Asunto(s)

RESUMEN

Significance: Efficacious photodynamic therapy (PDT) of abscess cavities requires personalized treatment planning. This relies on knowledge of abscess wall optical properties, which we report for the first time in human subjects. Aim: The objective was to extract optical properties and photosensitizer concentration from spatially resolved diffuse reflectance measurements of abscess cavities prior to methylene blue (MB) PDT, as part of a phase 1 clinical trial. Approach: Diffuse reflectance spectra were collected at the abscess wall of 13 human subjects using a custom fiber-optic probe and optical spectroscopy system, before and after MB administration. A Monte Carlo lookup table was used to extract optical properties. Results: Pre-MB abscess wall absorption coefficients at 665 nm were 0.15±0.1 cm-1 (0.03 to 0.36 cm-1) and 10.74±15.81 cm-1 (0.08 to 49.3 cm-1) post-MB. Reduced scattering coefficients at 665 nm were 8.45±2.37 cm-1 (4.8 to 13.2 cm-1) and 5.6±2.26 cm-1 (1.6 to 9.9 cm-1) for pre-MB and post-MB, respectively. Oxygen saturations were found to be 58.83%±35.78% (5.6% to 100%) pre-MB and 36.29%±25.1% (0.0001% to 76.4%) post-MB. Determined MB concentrations were 71.83±108.22 µM (0 to 311 µM). Conclusions: We observed substantial inter-subject variation in both native wall optical properties and MB uptake. This underscores the importance of making these measurements for patient-specific treatment planning.

Asunto(s)

RESUMEN

Significance: Accurately distinguishing tumor tissue from normal tissue is crucial to achieve complete resections during soft tissue sarcoma (STS) surgery while preserving critical structures. Incomplete tumor resections are associated with an increased risk of local recurrence and worse patient prognosis. Aim: We evaluate the performance of diffuse reflectance spectroscopy (DRS) to distinguish tumor tissue from healthy tissue in STSs. Approach: DRS spectra were acquired from different tissue types on multiple locations in 20 freshly excised sarcoma specimens. A k-nearest neighbors classification model was trained to predict the tissue types of the measured locations, using binary and multiclass approaches. Results: Tumor tissue could be distinguished from healthy tissue with a classification accuracy of 0.90, sensitivity of 0.88, and specificity of 0.93 when well-differentiated liposarcomas were included. Excluding this subtype, the classification performance increased to an accuracy of 0.93, sensitivity of 0.94, and specificity of 0.93. The developed model showed a consistent performance over different histological subtypes and tumor locations. Conclusions: Automatic tissue discrimination using DRS enables real-time intra-operative guidance, contributing to more accurate STS resections.

Asunto(s)

RESUMEN

Diffuse Reflectance Spectroscopy (DRS) can provide tissue feedback for pedicle screw placement in spine surgery, yet the integration of fiber optics into the tip of the pedicle probe, a device used to pierce through bone, is challenging, since the optical probing depth and signal-to-noise ratio (SNR) are affected negatively compared to those of a blunt DRS probe. Through Monte Carlo simulations and optical phantom experiments, we show how differences in the shape of the instrument tip influence the acquired spectrum. Our findings demonstrate that a single bevel with an angle of 30∘ offers a solution to anticipate cortical breaches during pedicle screw placement. Compared to a blunt probe, the optical probing depth and SNR of a cone tip are reduced by 50%. The single bevel tip excels with 75% of the optical probing depth and a SNR remaining at approximately ⅔, facilitating the construction of a surgical instrument with integrated DRS.

RESUMEN

Correct classification of skin lesions is a key step in skin cancer screening, which requires high accuracy and interpretability. This paper proposes a multimodal method for differentiating various clinical forms of basal cell carcinoma and benign neoplasms that includes machine learning. This study was conducted on 37 neoplasms, including benign neoplasms and five different clinical forms of basal cell carcinoma. The proposed multimodal screening method combines diffuse reflectance spectroscopy, optical coherence tomography and high-frequency ultrasound. Using diffuse reflectance spectroscopy, the coefficients of melanin pigmentation, erythema, hemoglobin content, and the slope coefficient of diffuse reflectance spectroscopy in the wavelength range 650-800 nm were determined. Statistical texture analysis of optical coherence tomography images was used to calculate first- and second-order statistical parameters. The analysis of ultrasound images assessed the shape of the tumor according to parameters such as area, perimeter, roundness and other characteristics. Based on the calculated parameters, a machine learning algorithm was developed to differentiate the various clinical forms of basal cell carcinoma. The proposed algorithm for classifying various forms of basal cell carcinoma and benign neoplasms provided a sensitivity of 70.6 ± 17.3%, specificity of 95.9 ± 2.5%, precision of 72.6 ± 14.2%, F1 score of 71.5 ± 15.6% and mean intersection over union of 57.6 ± 20.1%. Moreover, for differentiating basal cell carcinoma and benign neoplasms without taking into account the clinical form, the method achieved a sensitivity of 89.1 ± 8.0%, specificity of 95.1 ± 0.7%, F1 score of 89.3 ± 3.4% and mean intersection over union of 82.6 ± 10.8%.

RESUMEN

Significance: Machine learning (ML)-enabled diffuse reflectance spectroscopy (DRS) is increasingly used as an alternative to the computation-intensive inverse Monte Carlo (MCI) simulation to predict tissue's optical properties, including the absorption coefficient, µa and reduced scattering coefficient, µs'. Aim: We aim to develop a use-error-robust ML algorithm for optical property prediction from DRS spectra. Approach: We developed a wavelength-independent regressor (WIR) to predict optical properties from DRS data. For validation, we generated 1520 simulated DRS spectra with the forward Monte Carlo model, where µa=0.44 to 2.45 cm-1, and µs'=6.53 to 9.58 cm-1. We introduced common use-errors, such as wavelength miscalibrations and intensity fluctuations. Finally, we collected 882 experimental DRS images from 170 tissue-mimicking phantoms and compared performances of the WIR model, a dense neural network, and the MCI model. Results: When compounding all use-errors on simulated data, the WIR model best balanced accuracy and speed, yielding errors of 1.75% for µa and 1.53% for µs', compared to the MCI's 50.9% for µa and 24.6% for µs'. Regarding experimental data, WIR model had mean errors of 13.2% and 6.1% for µa and µs', respectively. The errors for MCI were about eight times higher. Conclusions: The WIR model presents reliable use-error-robust optical property predictions from DRS data.

Asunto(s)

RESUMEN

This study investigates the relationship between body hydration levels and skin hydration using spatially resolved diffuse reflectance spectroscopy. The research involved monitoring skin dehydration and rehydration under various conditions, including thermal and physical loads on healthy volunteers, and diuretic therapy in patients with edema syndrome. Findings indicate a correlation between body mass reduction and skin hydration: a 1% loss in body mass corresponds to a 10% decrease in skin hydration. During thermal stress, water absorption at 970 nm decreased monotonically without recovery. Physical activity resulted in approximately 10% changes in skin water content within 20 min, followed by rehydration. Patients with edema syndrome exhibited the most substantial decrease in water absorption amplitude, at nearly 30%, during diuretic treatment. These results support optical spectroscopy as a non-invasive tool for assessing body hydration, with implications for developing portable hydration monitoring devices for clinical and sports applications.

RESUMEN

Brown adipose tissue (BAT) is related to lipid and glucose metabolism, and BAT evaluation is expected to contribute to disease prevention and treatment. We aimed to establish a BAT evaluation method using simple and non-invasive diffuse reflectance spectroscopy (DRS). We acquired diffuse reflectance spectra of BAT using DRS from rats with cold stimulation and analyzed the second-derivative spectra. To predict the amount of triglyceride in BAT from the second-derivative spectra, partial least-squares regression analysis was performed, and we examined whether BAT weight can be predicted from the amount of triglyceride by single regression analysis. By focusing on changes in the amount of triglyceride in BAT with cold stimulation, it was suggested that this amount could be predicted spectroscopically, and the predicted amount of triglyceride could be used to estimate the BAT weight with cold stimulation. If these results can be translated into humans, they may contribute to preventing metabolic disorders.

Asunto(s)

RESUMEN

Understanding the role of non-structural carbohydrates (NSC) in tree-level carbon cycling crucially depends on the availability of NSC data in a sufficient temporal resolution covering extreme conditions and seasonal peaks or declines. Chemical analytical methods should therefore get complemented by less extensive retrieval methods. To this end, we explored the potential of diffuse reflectance spectroscopy for estimating NSC contents at a set of 180 samples taken from leaves, roots, stems and branches of different tree species in different biogeographic regions. Multiple randomized partitioning in calibration and validation data were performed with near-infrared (NIR) and mid-infrared (MIR) as well as combined data. With derivative spectra, NIR markedly outperformed MIR data for NSC estimation; mean RMSE for outer validation samples equalled 2.58 (in % of dry matter) compared to 2.90, r2 was 0.64 compared to 0.52. We found complementary information related to NSC in both spectral domains, so that a combination with high-level data fusion (model averaging) increased accuracy (RMSE decreased to 2.19, r2 equalled 0.72). Spectral variable selection with the CARS algorithm further improved results slightly (RMSE = 1.97, r2 = 0.78). On the level of tissue types, we found a marked differentiation concerning the appropriateness of datasets and approaches. High-level data fusion was successful for leaves, NIR data (together with CARS) provided the best results for wooden tissues. This suggests further studies with a greater number of samples per tissue type but only for selected (main) tree species to finally judge the sensitivities of diffuse reflectance spectroscopy (NIR, MIR) for NSC retrieval.

Asunto(s)

RESUMEN

Diffuse optical measurement is an evolving optical modality providing a fast and portable solution for microcirculation assessment. Diffuse optics in static and dynamic modalities are combined here in a system to assess hemodynamics in skin tissues of control and diabetic subjects. The in-house developed system consists of a laser source, fiber optic probe, a low-cost avalanche photodiode, a finite element model (FEM) derived static optical property estimator, and a software correlator for continuous flow monitoring through microvasculature. The studies demonstrated that the system quantifies the changes in blood flow rate in the immediate skin subsurface. The system is calibrated with in vitro flow models and a proof-of-concept was demonstrated on a limited number of subjects in a clinical environment. The flow changes in response to vasoconstrictive and vasodilative stimuli were analyzed and used to classify different stages of diabetes, including diabetic neuropathy.

Asunto(s)

RESUMEN

Significance: Knowledge of optical properties is important to accurately model light propagation in tissue, but in vivo reference data are sparse. Aim: The aim of our study was to present in vivo skin optical properties from a large Swedish cohort including 3809 subjects using a three-layered skin model and spatially resolved diffuse reflectance spectroscopy (Periflux PF6000 EPOS). Approach: Diffuse reflectance spectra (475 to 850 nm) at 0.4 and 1.2 mm source-detector separations were analyzed using an inverse Monte Carlo method. The model had one epidermis layer with variable thicknesses and melanin-related absorptions and two dermis layers with varying hemoglobin concentrations and equal oxygen saturations. The reduced scattering coefficient was equal across all layers. Results: Median absorption coefficients (mm-1) in the upper dermis ranged from 0.094 at 475 nm to 0.0048 at 850 nm and similarly in the lower dermis from 0.059 to 0.0035. The reduced scattering coefficient (mm-1) ranged from 3.22 to 1.20, and the sampling depth (mm) ranged from 0.23 to 0.38 (0.4 mm separation) and from 0.49 to 0.68 (1.2 mm separation). There were differences in optical properties across sex, age groups, and BMI categories. Conclusions: Reference material for skin optical properties is presented.

Asunto(s)