Retrieval of chromophore concentration changes in a digital human head model using analytical mean partial pathlengths of photons.

Significance: Continuous-wave functional near-infrared spectroscopy has proved to be a valuable tool for assessing hemodynamic activity in the human brain in a non-invasively and inexpensive way. However, most of the current processing/analysis methods assume the head is a homogeneous medium, and hence do not appropriately correct for the signal coming from the scalp. This effect can be reduced by considering light propagation in a layered model of the human head, being the Monte Carlo (MC) simulations the gold standard to this end. However, this implies large computation times and demanding hardware capabilities. Aim: In this work, we study the feasibility of replacing the homogeneous model and the MC simulations by means of analytical multilayered models, combining in this way, the speed and simplicity of implementation of the former with the robustness and accuracy of the latter. Approach: Oxy- and deoxyhemoglobin (HbO and HbR, respectively) concentration changes were proposed in two different layers of a magnetic resonance imaging (MRI)-based meshed model of the human head, and then these changes were retrieved by means of (i) a typical homogeneous reconstruction and (ii) a theoretical layered reconstruction. Results: Results suggest that the use of analytical models of light propagation in layered models outperforms the results obtained using traditional homogeneous reconstruction algorithms, providing much more accurate results for both, the extra- and the cerebral tissues. We also compare the analytical layered reconstruction with MC-based reconstructions, achieving similar degrees of accuracy, especially in the gray matter layer, but much faster (between 4 and 5 orders of magnitude). Conclusions: We have successfully developed, implemented, and validated a method for retrieving chromophore concentration changes in the human brain, combining the simplicity and speed of the traditional homogeneous reconstruction algorithms with robustness and accuracy much more similar to those provided by MC simulations.

Assessment of Donor Site Scar Outcomes, Healing Time, and Postoperative Complications Associated With Split Thickness Skin Grafts Harvested From the Hair Bearing Scalp.

BACKGROUND: The hair-bearing scalp is an underused donor site for split-thickness skin grafts (STSG). OBJECTIVE: Evaluating the donor site scar outcomes, healing times, and complications associated with STSG harvested from the hair-bearing scalp. MATERIALS AND METHODS: During this prospective observational study, donor site healing was assessed on postoperative Days 8 and 30. Donor site scar outcomes were quantified at 1 month using the Vancouver Scar Scale. All postoperative complications were collected during the 30-day follow-up window. RESULTS: 80% of donor sites was fully healed at 1-week follow-up. Vancouver Scar Scale score at the donor site was 0.26 at 1-month follow-up. All patients experienced full hair regrowth. Maximum pain scores were reported on the night of surgery (Vancouver Scar Scale 1.8), with quick resolution in days to follow. No major complications were reported. All STSG obtained from the scalp had full take and good texture and color match with the recipient site. CONCLUSION: The hair-bearing scalp is an excellent donor site for split-thickness skin graft harvesting.

Invention of automated numerical algorithm adopting binarization for the evaluation of scalp hair coverage: An image analysis providing a substitute for phototrichogram and global photography assessment for hair diseases.

BACKGROUND: The efficacy of therapeutic modalities for hair disease can be evaluated globally by photo assessment and more precisely by phototrichogram (PTG). However, the latter procedure is laborious, time consuming, subject to inter-observer variation, and requires hair clipping. OBJECTIVE: To establish an automated and patient/investigator friendly methodology enabling quantitative hair amount evaluation for daily clinical practice. METHODS: A novel automated numerical algorithm (aNA) adopting digital image binarization (i.e., black and white color conversion) was invented to evaluate hair coverage and measure PTG parameters in scalp images. Step-by-step improvement of aNA was attempted through comparative analyses of the data obtained respectively by the novel approach and conventional PTG/global photography assessment (GPA). RESULTS: For measuring scalp hair coverage, the initial version of aNA generally agreed with the cumulative hair diameter as assessed using PTG, showing a coefficient of 0.60. However, these outcomes were influenced by the angle of hair near the parting line. By integrating an angle compensation formula, the standard deviation of aNA data decreased from 5.7% to 1.2%. Consequently, the coefficient of determination for hair coverage calculated using the modified aNA and cumulative hair diameter assessed by PTG increased to 0.90. Furthermore, the change in hair coverage as determined by the modified aNA protocol correlated well with changes in the GPA score of images obtained using clinical trials. CONCLUSION: The novel aNA method provides a valuable tool for enabling simple and accurate evaluation of hair growth and volume for clinical trials and for treatment of hair disease.

Imaging Tools for Noninvasive Hair Assessment.

Trichology tools historically have been limited in their ability to provide noninvasive detailed assessments of the hair and scalp. Recent advances in diagnostic and treatment monitoring technologies have begun to fill this gap. Global photography previously relied on a film camera and stereotactic imaging equipment but has been simplified by the advent of cameras that use software analysis and provide adjustable outlines to match facial features for the capture of standardized views. Reflectance confocal microscopy (RCM) and optical coherence tomography (OCT) both enable in vivo visualization of subcutaneous structures and provide new insight into the dynamic subclinical changes of alopecia. Recent efforts focus on training convolutional neural networks to quantify various hair parameters on OCT scans. When scalp biopsy is necessary, trichoscopy, RCM, and OCT can guide in selecting biopsy sites. Because of the growing clinical applications of these technologies, clinicians should be aware of the advantages and limitations of noninvasive hair-imaging tools.

Minimizing Bias in Alopecia Diagnosis in Skin of Color Patients.

Alopecia is one of the most common dermatologic conditions affecting black patients, with a significantly negative impact on quality of life.1,2 Timely and accurate diagnosis is therefore critical in order to reverse or halt progression of disease.3 Unfortunately, lack of representation of skin of color (SOC) patients in the current literature may contribute to misdiagnosis as providers may be unfamiliar with the clinical spectrum of alopecia presenting in darker scalps.4 Some scarring alopecia subtypes such as Central Centrifugal Cicatricial Alopecia (CCCA) are more prevalent in certain racial groups. However, focusing solely on patient demographics and gross clinical findings may obscure accurate diagnoses. To distinguish alopecia findings in Black patients, a dedicated approach using a combination of clinical exam findings and patient history, along with trichoscopy and biopsy, is essential to prevent misdiagnosis and improve clinical and diagnostic outcomes. We present three cases of alopecia in patients of color which the initial suspected clinical diagnosis did not correspond with trichoscopic and biopsy results. We challenge clinicians to reexamine their biases and fully evaluate patients of color with alopecia. An examination should include a thorough history, clinical examination, trichoscopy, and potentially a biopsy, particularly when findings do not correlate. Our cases highlight the challenges and disparities that exist in diagnosis of alopecia in Black patients. We emphasize the need for continued research regarding alopecia in skin of color and the importance of a complete workup for alopecia to improve diagnostic outcomes.Balazic E, Axler E, Nwankwo C, et al. Minimizing bias in alopecia diagnosis in skin of color patients. J Drugs Dermatol. 2023;22(7):703-705. doi:10.36849/JDD.7117.  .

Feasibility of size-specific organ-dose estimates based on water equivalent diameter for common head CT examinations: a Monte Carlo study.

Computed tomography dose index (CTDI) is an unreliable dose estimate outside of the standard CTDI phantom diameters (16 and 32 cm). Size-specific dose estimate (SSDE) for head computed tomography (CT) examination was studied in the American Association of Physicists in Medicine Report 293 to provide SSDE coefficient factors based on water equivalent diameter as size metrics. However, it is limited to one protocol and for a fully irradiated organ. This study aimed to evaluate the dependency of normalized organ dose (ND) on water equivalent diameter as a size metric in three common protocols: routine head, paranasal sinus, and temporal bone. CTDIwmeasurements were performed for outlined protocols in the Siemens Emotion 16-slice-configuration scanner. Geant4 Application for Tomographic Emission Monte Carlo simulation platform, coupled with ten GSF patient models, was used to estimate organ doses. CT scanner system was modeled. Helical CT scans were simulated using constructor scan parameters and calculated scan lengths of each patient model. Organ doses provided by simulations were normalized to CTDIvol. The water equivalent diameters (Dw) of patient models were obtained via relationships betweenDwand both effective diameter for a sample of patients' data.NDs received by fully, partially, and non-directly irradiated organs were then reported as a function ofDw. For fully irradiated organs, brain (R2> 0.92), eyes (R2> 0.88), and eye lens (R2> 0.89) correlate well withDw. For the rest of the results, a poor correlation was observed. For partially irradiated organs, the exception was scalp (R2= 0.93) in temporal bone CT. For non-directly irradiated organs, the exception was thyroid (R2> 0.90) and lungs (R2> 0.91) in routine head CT. ND correlates well in routine head CT than other protocols. For the most part, no relationship seems to exist betweenR2and scan percentage coverage. The results have revealed additional factors that may influence the ND andDwrelationship, which explains the need for more studies in the future to investigate the effect of scan conditions and organ anatomy variation.

Scalp ripple rates for rapid epilepsy differentiation and seizure activity assessment: Applicability and influential factors.

OBJECTIVE: We aim to determine whether automatically detected ripple rate (ADRR) of 10-min scalp electroencephalography (EEG) during slow-wave sleep can be a useful tool for rapid epilepsy differentiation and seizure activity assessment, and we analyze the clinical factors that may affect the scalp ripple rates. METHODS: We retrospectively included 336 patients who underwent long-term video-EEG with a sampling rate ≥1000 Hz, and three groups were established based on their final clinical diagnosis (non-epilepsy; non-active epilepsy [epilepsy being seizure-free for at least 1 year]; and active epilepsy [epilepsy with one or more seizures in the past year]). ADRRs between groups were compared and diagnostic thresholds set according to the maximum of Youden index with the receiver-operating characteristic curve. RESULTS: The 336 patients comprised 49 non-epilepsy and 287 epilepsy patients (95 non-active epilepsy and 192 active epilepsy). The median ADRR of the epilepsy group was significantly greater than in the non-epilepsy group, with a diagnostic threshold of 4.25 /min (specificity 89.8%, sensitivity 47.74%, p<.001). Following stratification by age, the area under the curve was greatest in the 0-20 year subgroup, threshold 4.10 /min (specificity 100%, sensitivity 52.47%, p<.001). Regarding distinguishing active epilepsy from non-active epilepsy patients, the area under the curve was also greatest in patients 0-20 years of age, threshold 13.05/min (specificity 98.36%, sensitivity 35.64%, p<.001). Following stratification by epilepsy type, the diagnostic efficiency was best in children with developmental and epileptic encephalopathies/epileptic encephalopathies (DEEs/EEs) (threshold 5.20/min, specificity 100%, sensitivity 100%) and self-limited focal epilepsies (SeLFEs) (threshold 5.45/min, specificity 80%, sensitivity 100%). Multivariate analysis revealed that the influential factors of ADRRs were age, depth of epileptogenic lesion, and seizure frequency. SIGNIFICANCE: ADRR of scalp EEG can be a rapid and specific method to differentiate epilepsy and evaluate seizure activity. This method is especially suitable for young patients.

Ethical, legal, organizational and social issues related to the use of scalp cooling for the prevention of chemotherapy-induced alopecia: A systematic review.

INTRODUCTION: Scalp cooling (SC) aims to prevent chemotherapy-induced alopecia. The goal of this systematic review is to tackle ethical, legal, organizational and social issues related to SC. METHODS: A critical appraisal of the literature was carried out using a systematic review design. MEDLINE, Embase and Web of Science databases were searched up until 2 June 2021. Studies addressing these aspects in English or Spanish were considered. Representatives of both patient associations and professional scientific societies related to the topic participated in the design of the protocol and the review of the findings. RESULTS: A total of 17 studies were included. Articles were critically appraised using the MMAT and SANRA. Findings were organized into four categories: (1) ethical aspects focused on equal access, gender equity and doctor-patient communication supported by Patient Decision Aids (PtDAs); (2) patient perspective and acceptability; (3) professional perspective and acceptability; (4) organizational aspects focused on accessibility and feasibility. CONCLUSION: Cancer patients' expectations when using SC need to be adjusted to reduce the potential distress associated with hair loss. PtDAs could help patients clarify their values and preferences regarding SC. Equal access to technology should be guaranteed. PATIENT OR PUBLIC CONTRIBUTION: In this systematic review, the representatives of the patient associations (Ms. María Luz Amador Muñoz of the Spanish Association Against Cancer [AECC] and Ms. Catiana Martinez Cánovas of the Spanish Breast Cancer Federation [FECMA]) participated in the review of the study protocol, as well as in the results, discussion and conclusions, making their contributions. In the type of design of these studies (systematic reviews), it is not usual to have the direct participation of patients, but in this one, we have done so, as it is a systematic review that is part of a report of the Spanish Network of Health Technology Assessment Agencies (ETS).

Quantitative signal quality assessment for large-scale continuous scalp electroencephalography from a big data perspective.

Objective. Despite electroencephalography (EEG) being a widely used neuroimaging technique with an excellent temporal resolution, in practice, the signals are heavily contaminated by artifacts masking responses of interest in an experiment. It is thus essential to guarantee a prompt and effective detection of artifacts that provides quantitative quality assessment (QA) on raw EEG data. This type of pipeline is crucial for large-scale EEG studies. However, current EEG QA studies are still limited.Approach. In this study, combined from a big data perspective, we therefore describe a quantitative signal quality assessment pipeline, a stable and general threshold-based QA pipeline that automatically integrates artifact detection and new QA measures to assess continuous resting-state raw EEG data. One simulation dataset and two resting-state EEG datasets from 42 healthy subjects and 983 clinical patients were utilized to calibrate the QA pipeline.Main Results. The results demonstrate that (1) the QA indices selected are sensitive: they almost strictly and linearly decrease as the noise level increases; (2) stable, replicable QA thresholds are valid for other experimental and clinical EEG datasets; and (3) use of the QA pipeline on these datasets reveals that high-frequency noises are the most common noises in EEG practice. The QA pipeline is also deployed in the WeBrain cloud platform (https://webrain.uestc.edu.cn/, the Chinese EEG Brain Consortium portal).Significance. These findings suggest that the proposed QA pipeline may be a stable and promising approach for quantitative EEG signal quality assessment in large-scale EEG studies.

Effects of Different Optical Properties of Head Tissues on Near-Infrared Spectroscopy Using Monte Carlo Simulations.

In near-infrared spectroscopy (NIRS), it is crucial to have an accurate and realistic model of photon transport in the adult head for obtaining accurate brain oxygenation values. There are several studies on the influence of thickness, the morphology of extracerebral layers, and source-detector distance on the sensitivity of NIRS to the brain. However, the optical properties of the different layers vary between different publications. How is the performance of NIRS affected when the real optical properties differ from the assumed ones?We aim to investigate the influence of variation in scattering and absorption in a five-layered head model (scalp, skull, CSF, grey and white matter). We performed Monte Carlo simulations focusing on a five-layered slab mesh. The range of optical properties is based on a review of the published literature. We assessed the effect on light propagation by measuring the difference in the mean partial path lengths, attenuation, and the number of the detected photons between the different optical properties performing Monte Carlo simulations. For changes in the reduced scattering, we found that the upper layers tend to have a negative impact. In contrast, changes in lower layers tend to impact the brain's influence metrics positively. Furthermore, for small source-detector distances, the relative percentage difference between lower and higher values is greater than larger distances. Conclusions: We conclude that the assumption of different optical properties has a substantial effect on the sensitivity to the brain. This means that it is important to determine the correct optical properties for NIRS measurements in vitro and in vivo.

Current status and development potential of scalp healthcare in the COVID-19 blue era: A critical review focused on Republic of Korea.

AIMS: The purpose of this paper was to review the literature focusing on the scalp health of the Korean people in the COVID-19 blue era and the possibility of significant development as an academic. METHODS: This review paper is a literature review, and the method is a narrative review. RESULTS: It was found that the higher the awareness of hair loss, the better the scalp and hair management behavior. South Korea needs to develop systematic customized management methods, scalp programs, and products due to the development of the COVID-19 era and the development of the 4th industry. CONCLUSION: South Korea still needs to improve the expertise of tricolologists and national social security insurance and research along with the growth of the beauty and healthcare service industry in the COVID-19 blue era.

Quantifying tissue optical properties of human heads in vivo using continuous-wave near-infrared spectroscopy and subject-specific three-dimensional Monte Carlo models.

SIGNIFICANCE: Quantifying subject-specific optical properties (OPs) including absorption and transport scattering coefficients of tissues in the human head could improve the modeling of photon propagation for the analysis of functional near-infrared spectroscopy (fNIRS) data and dosage quantification in therapeutic applications. Current methods employ diffuse approximation, which excludes a low-scattering cerebrospinal fluid compartment and causes errors. AIM: This work aims to quantify OPs of the scalp, skull, and gray matter in vivo based on accurate Monte Carlo (MC) modeling. APPROACH: Iterative curve fitting was applied to quantify tissue OPs from multidistance continuous-wave NIR reflectance spectra. An artificial neural network (ANN) was trained using MC-simulated reflectance values based on subject-specific voxel-based tissue models to replace MC simulations as the forward model in curve fitting. To efficiently generate sufficient data for training the ANN, the efficiency of MC simulations was greatly improved by white MC simulations, increasing the detectors' acceptance angle, and building a lookup table for interpolation. RESULTS: The trained ANN was six orders of magnitude faster than the original MC simulations. OPs of the three tissue compartments were quantified from NIR reflectance spectra measured at the forehead of five healthy subjects and their uncertainties were estimated. CONCLUSIONS: This work demonstrated an MC-based iterative curve fitting method to quantify subject-specific tissue OPs in-vivo, with all OPs except for scattering coefficients of scalp within the ranges reported in the literature, which could aid the modeling of photon propagation in human heads.

Data-Driven EEG Band Discovery with Decision Trees.

Electroencephalography (EEG) is a brain imaging technique in which electrodes are placed on the scalp. EEG signals are commonly decomposed into frequency bands called delta, theta, alpha, and beta. While these bands have been shown to be useful for characterizing various brain states, their utility as a one-size-fits-all analysis tool remains unclear. The goal of this work is to outline an objective strategy for discovering optimal EEG bands based on signal power spectra. A two-step data-driven methodology is presented for objectively determining the best EEG bands for a given dataset. First, a decision tree is used to estimate the optimal frequency band boundaries for reproducing the signal's power spectrum for a predetermined number of bands. The optimal number of bands is then determined using an Akaike Information Criterion (AIC)-inspired quality score that balances goodness-of-fit with a small band count. This data-driven approach led to better characterization of the underlying power spectrum by identifying bands that outperformed the more commonly used band boundaries by a factor of two. Additionally, key spectral components were isolated in dedicated frequency bands. The proposed method provides a fully automated and flexible approach to capturing key signal components and possibly discovering new indices of brain activity.

Efficacy assessment for low-level laser therapy in the treatment of androgenetic alopecia: a real-world study on 1383 patients.

Low-level laser therapy (LLLT) has been a treatment modality by many androgenetic alopecia (AGA) patients in recent years. It remained unclear as to how long the treatment regime should be maintained, and which characteristics of patients should this be recommended. A real-world study was carried out with an FDA-cleared low-level laser helmet for 1383 patients. Ordinal logistic regression analysis with propensity score matching (PSM) was used to investigate the factors related to efficacy assessment. More than 80% of users were between 18 and 40 years old. The median use times were 133 for mild AGA patients and 142 for moderate-to-severe AGA patients, which equated to 38 weeks and 40 weeks, respectively. The overall clinical effectiveness was nearly 80%. PSM analysis revealed that gender (P = 0.002), use period (P = 0.068), scalp conditions with dandruff, rash, and itchy symptoms were associated with the grading of efficacy assessment. Male users (ordinal OR: 1.35, CI: (1.01, 1.79)); use for more than 180 times or use period for 1 year (ordinal OR: 1.40, CI: (1.11, 1.96)); and those with scalp dandruff (ordinal OR: 1.34, CI: (1.01, 1.87)), rash (ordinal OR: 1.47, CI: (1.04, 2.07)), and itchy symptoms (ordinal OR: 1.51, CI: (1.12, 2.03)) had better efficacy assessments. The recommended treatment regime with low-level laser helmet was more than 1 year or 180 use times. Male patients with dandruff, rash, and itchy symptoms in scalps tended to have a better efficacy assessment.