Prediction model for knee osteoarthritis using magnetic resonance-based radiomic features from the infrapatellar fat pad: data from the osteoarthritis initiative.

Background: The infrapatellar fat pad (IPFP) plays an important role in the incidence of knee osteoarthritis (OA). Magnetic resonance (MR) signal heterogeneity of the IPFP is related to pathologic changes. In this study, we aimed to investigate whether the IPFP radiomic features have predictive value for incident radiographic knee OA (iROA) 1 year prior to iROA diagnosis. Methods: Data used in this work were obtained from the osteoarthritis initiative (OAI). In this study, iROA was defined as a knee with a baseline Kellgren-Lawrence grade (KLG) of 0 or 1 that further progressed to KLG ≥2 during the follow-up visit. Intermediate-weighted turbo spin-echo knee MR images at the time of iROA diagnosis and 1 year prior were obtained. Five clinical characteristics-age, sex, body mass index, knee injury history, and knee surgery history-were obtained. A total of 604 knees were selected and matched (302 cases and 302 controls). A U-Net segmentation model was independently trained to automatically segment the IPFP. The prediction models were established in the training set (60%). Three main models were generated using (I) clinical characteristics; (II) radiomic features; (III) combined (clinical plus radiomic) features. Model performance was evaluated in an independent testing set (remaining 40%) using the area under the curve (AUC). Two secondary models were also generated using Hoffa-synovitis scores and clinical characteristics. Results: The comparison between the automated and manual segmentations of the IPFP achieved a Dice coefficient of 0.900 (95% CI: 0.891-0.908), which was comparable to that of experienced radiologists. The radiomic features model and the combined model yielded superior AUCs of 0.700 (95% CI: 0.630-0.763) and 0.702 (95% CI: 0.635-0.763), respectively. The DeLong test found no statistically significant difference between the receiver operating curves of the radiomic and combined models (P=0.831); however, both models outperformed the clinical model (P=0.014 and 0.004, respectively). Conclusions: Our results demonstrated that radiomic features of the IPFP are predictive of iROA 1 year prior to the diagnosis, suggesting that IPFP radiomic features can serve as an early quantitative prediction biomarker of iROA.

Accurate and early prediction of the wound healing outcome of burn injuries using the wavelet Shannon entropy of terahertz time-domain waveforms.

Significance: Severe burn injuries cause significant hypermetabolic alterations that are highly dynamic, hard to predict, and require acute and critical care. The clinical assessments of the severity of burn injuries are highly subjective and have consistently been reported to be inaccurate. Therefore, the utilization of other imaging modalities is crucial to reaching an objective and accurate burn assessment modality. Aim: We describe a non-invasive technique using terahertz time-domain spectroscopy (THz-TDS) and the wavelet packet Shannon entropy to automatically estimate the burn depth and predict the wound healing outcome of thermal burn injuries. Approach: We created 40 burn injuries of different severity grades in two porcine models using scald and contact methods of infliction. We used our THz portable handheld spectral reflection (PHASR) scanner to obtain the in vivo THz-TDS images. We used the energy to Shannon entropy ratio of the wavelet packet coefficients of the THz-TDS waveforms on day 0 to create supervised support vector machine (SVM) classification models. Histological assessments of the burn biopsies serve as the ground truth. Results: We achieved an accuracy rate of 94.7% in predicting the wound healing outcome, as determined by histological measurement of the re-epithelialization rate on day 28 post-burn induction, using the THz-TDS measurements obtained on day 0. Furthermore, we report the accuracy rates of 89%, 87.1%, and 87.6% in automatic diagnosis of the superficial partial-thickness, deep partial-thickness, and full-thickness burns, respectively, using a multiclass SVM model. Conclusions: The THz PHASR scanner promises a robust, high-speed, and accurate diagnostic modality to improve the clinical triage of burns and their management.

Deep neural network classification of in vivo burn injuries with different etiologies using terahertz time-domain spectral imaging.

Thermal injuries can occur due to direct exposure to hot objects or liquids, flames, electricity, solar energy and several other sources. If the resulting injury is a deep partial thickness burn, the accuracy of a physician's clinical assessment is as low as 50-76% in determining the healing outcome. In this study, we show that the Terahertz Portable Handheld Spectral Reflection (THz-PHASR) Scanner combined with a deep neural network classification algorithm can accurately differentiate between partial-, deep partial-, and full-thickness burns 1-hour post injury, regardless of the etiology, scanner geometry, or THz spectroscopy sampling method (ROC-AUC = 91%, 88%, and 86%, respectively). The neural network diagnostic method simplifies the classification process by directly using the pre-processed THz spectra and removing the need for any hyperspectral feature extraction. Our results show that deep learning methods based on THz time-domain spectroscopy (THz-TDS) measurements can be used to guide clinical treatment plans based on objective and accurate classification of burn injuries.

Supervised machine learning for automatic classification of in vivo scald and contact burn injuries using the terahertz Portable Handheld Spectral Reflection (PHASR) Scanner.

We present an automatic classification strategy for early and accurate assessment of burn injuries using terahertz (THz) time-domain spectroscopic imaging. Burn injuries of different severity grades, representing superficial partial-thickness (SPT), deep partial-thickness (DPT), and full-thickness (FT) wounds, were created by a standardized porcine scald model. THz spectroscopic imaging was performed using our new fiber-coupled Portable HAndheld Spectral Reflection Scanner, incorporating a telecentric beam steering configuration and an f-[Formula: see text] scanning lens. ASynchronous Optical Sampling in a dual-fiber-laser THz spectrometer with 100 MHz repetition rate enabled high-speed spectroscopic measurements. Given twenty-four different samples composed of ten scald and ten contact burns and four healthy samples, supervised machine learning algorithms using THz-TDS spectra achieved areas under the receiver operating characteristic curves of 0.88, 0.93, and 0.93 when differentiating between SPT, DPT, and FT burns, respectively, as determined by independent histological assessments. These results show the potential utility of our new broadband THz PHASR Scanner for early and accurate triage of burn injuries.

In Vivo Assessment and Monitoring of Burn Wounds Using a Handheld Terahertz Hyperspectral Scanner.

The accuracy of clinical assessment techniques in diagnosing partial-thickness burn injuries has remained as low as 50-76%. Depending on the burn depth and environmental factors in the wound, such as reactive oxygen species, inflammation, and autophagy, partial-thickness burns can heal spontaneously or require surgical intervention. Herein, it is demonstrated that terahertz time-domain spectral imaging (THz-TDSI) is a promising tool for in vivo quantitative assessment and monitoring of partial-thickness burn injuries in large animals. We used a novel handheld THz-TDSI scanner to characterize burn injuries in a porcine scald model with histopathological controls. Statistical analysis (n= 40) indicates that the THz-TDSI modality can accurately differentiate between partial-thickness and full-thickness burn injuries (1-way ANOVA, p< 0.05). THz-TDSI has the potential to improve burn care outcomes by helping surgeons in making objective decisions for early excision of the wound.

Effective Debye relaxation models for binary solutions of polar liquids at terahertz frequencies.

There are many effective medium models that accurately describe the dielectric properties of mixtures. However, these models assume that the components are non-interacting. This assumption is not valid for solutions of polar liquids, resulting in significant deviations between the measured and theoretically predicted values of the complex index of refraction of the mixtures. We present three effective medium theories by expanding the well-known Debye relaxation model for solutions of polar liquids in the terahertz (THz) regime. The new effective medium models proposed in this paper predict the individual relaxation Debye parameters based on the cooperative motion dynamics and self-associative properties of each mixture, and therefore explain the deviation of the dielectric functions of the solutions from the traditional effective medium models. These models are verified through reflection measurements of four alcohol-water solutions acquired through THz time-domain spectroscopy (THz-TDS). Compared to the current mixed medium models, the new effective Debye theorem predicts the dielectric properties of polar solutions more accurately and has the potential to explain inter-species mixing schemes and interactions.

Comparison of comparable scald and contact burns in a porcine model: A preliminary report.

Whether the depth and healing of scalds and contact burns are similar is controversial. Due to water's greater heat capacity, we hypothesized that when exposed to similar temperatures and durations of exposure, burns caused by hot water would be deeper than those caused by contact with hot metal. Forty standardized burns were created in two anesthetized female domestic pigs using a brass bar or circulating heated water. In one pig, the temperature was kept constant (95°C) while the duration of exposure varied (5, 10, 15 seconds) In the second pig, the exposure time was kept constant (10 seconds) while the temperature of exposure varied (70°C, 80°C, 98°C). Periodic punch biopsies were taken to determine burn depth immediately after injury, percentage burns reepithelialized within 21 days, and depth of scar at 28 days. The analysis was performed using analysis of variance. When the temperature was held constant, duration of exposure (5, 10, and 15 seconds) was associated with scar depth (2.1 vs 3.8 vs 5.0 mm, respectively, P = 0.001) but not with burn depth (2.0 vs 2.2 vs 2.3 mm, respectively, P = 0.10). When exposure duration was held constant, temperature (70°C, 80°C, 98°C) was associated with scar depth (0.6 vs 1.7 vs 3.6, P < 0.001) but not with burn depth (1.2 vs 1.5 vs 1.7 mm, respectively, P = 0.21). Burn depths were greater for scald than contact burns although not significantly greater. After controlling for temperature, the difference in scar depth between scalds and contact burns was statistically significant (marginal means 3.0 for contact burns, 4.3 for scalds, P = 0.008). We conclude that burns created in swine with circulating hot water result in deeper scars than those created by contact with a brass bar when controlling for temperature and duration of exposure.

Cognitive resources are distributed among the entire auditory landscape in auditory scene analysis.

Although attention has been shown to enhance neural representations of selected inputs, the fate of unselected background sounds is still debated. The goal of the current study was to understand how processing resources are distributed among attended and unattended sounds during auditory scene analysis. We used a three-stream paradigm with four acoustic features uniquely defining each sound stream (frequency, envelope shape, spatial location, tone quality). We manipulated task load by having participants perform a difficult auditory task and an easy movie-viewing task with the same set of sounds in separate conditions. The mismatch negativity (MMN) component of event-related brain potentials (ERPs) was measured to evaluate sound processing in both conditions. We found no effect of task demands on unattended sound processing: MMNs were elicited by unattended deviants during both low- and high-load task conditions. A key factor of this result was the use of unique tone feature combinations to distinguish each of the three sound streams, strengthening the segregation of streams. In the auditory task, the P3b component demonstrates a two-stage process of target evaluation. Thus, these results, in conjunction with results of previous studies, suggest that stimulus-driven factors that strengthen stream segregation can free up processing capacity for higher-level analyses. The results illustrate the interactive nature of top-down and stimulus-driven processes in stream formation, supporting a distributive theory of attention that balances the strength of the bottom-up input with perceptual goals in analyzing the auditory scene.