CD28-CD57+ T cells from head and neck cancer patients produce high levels of cytotoxic granules and type II interferon but are not senescent.

T lymphocytes expressing CD57 and lacking costimulatory receptors CD27/CD28 have been reported to accumulate with aging, chronic infection, and cancer. These cells are described as senescent, with inability to proliferate but enhanced cytolytic and cytokine-producing capacity. However, robust functional studies on these cells taken directly from cancer patients are lacking. We isolated these T cells and their CD27/28+ counterparts from blood and tumor samples of 50 patients with previously untreated head and neck cancer. Functional studies confirmed that these cells have enhanced ability to degranulate and produce IFN-γ. They also retain the ability to proliferate, thus are not senescent. These data suggest that CD27/28-CD57+ CD8+ T cells are a subset of highly differentiated, CD45RA+ effector memory (TEMRA) cells with retained proliferative capacity. Patients with > 34% of these cells among CD8+ T cells in the blood had a higher rate of locoregional disease relapse, suggesting these cells may have prognostic significance.

An Ensemble Learning Method for Detection of Head and Neck Squamous Cell Carcinoma Using Polarized Hyperspectral Microscopic Imaging.

Head and neck squamous cell carcinoma (HNSCC) has a high mortality rate. In this study, we developed a Stokes-vector-derived polarized hyperspectral imaging (PHSI) system for H&E-stained pathological slides with HNSCC and built a dataset to develop a deep learning classification method based on convolutional neural networks (CNN). We use our polarized hyperspectral microscope to collect the four Stokes parameter hypercubes (S0, S1, S2, and S3) from 56 patients and synthesize pseudo-RGB images using a transformation function that approximates the human eye's spectral response to visual stimuli. Each image is divided into patches. Data augmentation is applied using rotations and flipping. We create a four-branch model architecture where each branch is trained on one Stokes parameter individually, then we freeze the branches and fine-tune the top layers of our model to generate final predictions. Our results show high accuracy, sensitivity, and specificity, indicating that our model performed well on our dataset. Future works can improve upon these results by training on more varied data, classifying tumors based on their grade, and introducing more recent architectural techniques.

Effects of socioeconomic status on enrollment in clinical trials for cancer: A systematic review.

BACKGROUND: To achieve equitable access to cancer clinical trials (CCTs), patients must overcome structural, clinical, and attitudinal barriers to trial enrollment. The goal of this systematic review was to study the relationship between socioeconomic status (SES), assessed either by direct or proxy measures, and CCT enrollment. METHODS: The review team and medical librarian developed search strategies for each database to identify studies for this systematic review, which was conducted according to PRISMA guidelines. Inclusion criteria were as follows: studies published in relevant scientific journals between January 2000 and July 2022, primary sources, English literature, and studies conducted in the US. Sixteen studies fulfilled the inclusion criteria and were reviewed. The risk of bias assessment was conducted independently by two reviewers using the Newcastle Ottawa scale. RESULTS: The initial search yielded 4070 citations, and 16 studies were included in our review. Four of the studies included used patient reported annual income as a measure of SES, while the remaining 12 studies used patient zip code as a proxy measurement of SES. Consistent with our hypothesis, 13 studies showed a positive association between high SES (patient-reported or proxy measurement) and CCT enrollment. Two studies showed a negative association, and one study showed no relationship. CONCLUSIONS: The existing literature suggests that low SES is associated with lower participation in CCT. The small number of studies identified on this topic highlights the need for additional research on SES and other barriers to CCT participation.

Polarized hyperspectral microscopic imaging system for enhancing the visualization of collagen fibers and head and neck squamous cell carcinoma.

Significance: Polarized hyperspectral microscopes with the capability of full Stokes vector imaging have potential for many biological and medical applications. Aim: The aim of this study is to investigate polarized hyperspectral imaging (PHSI) for improving the visualization of collagen fibers, which is an important biomarker related to tumor development, and improving the differentiation of normal and tumor cells on pathologic slides. Approach: We customized a polarized hyperspectral microscopic imaging system comprising an upright microscope with a motorized stage, two linear polarizers, two liquid crystal variable retarders (LCVRs), and a compact SnapScan hyperspectral camera. The polarizers and LCVRs worked in tandem with the hyperspectral camera to acquire polarized hyperspectral images, which were further used to calculate four Stokes vectors: S0, S1, S2, and S3. Synthetic RGB images of the Stokes vectors were generated for the visualization of cellular components in PHSI images. Regions of interest of collagen, normal cells, and tumor cells in the synthetic RGB images were selected, and spectral signatures of the selected components were extracted for comparison. Specifically, we qualitatively and quantitatively investigated the enhanced visualization and spectral characteristics of dense fibers and sparse fibers in normal stroma tissue, fibers accumulated within tumors, and fibers accumulated around tumors. Results: By employing our customized polarized hyperspectral microscope, we extract the spectral signatures of Stokes vector parameters of collagen as well as of tumor and normal cells. The measurement of Stokes vector parameters increased the image contrast of collagen fibers and cells in the slides. Conclusions: With the spatial and spectral information from the Stokes vector data cubes (S0, S1, S2, and S3), our PHSI microscope system enhances the visualization of tumor cells and tumor microenvironment components, thus being beneficial for pathology and oncology.

Independent Validation of the International Grading System for Medullary Thyroid Carcinoma: A Single Institution Experience.

Medullary thyroid carcinoma (MTC), an uncommon C cell thyroid malignancy, accounts for a disproportionate number of thyroid cancer deaths. To predict MTC clinical behavior, the recent international MTC grading system (IMTCGS) was published combining features from the Memorial Sloan Kettering Cancer Center and Royal North Shore Hospital grading systems that incorporates mitotic count, necrosis, and Ki67 proliferative index (Ki67PI). The IMTCGS appears promising, but independent validation data are limited. Here, we applied the IMTCGS to our institutional MTC cohort and assessed its ability to predict clinical outcomes. Our cohort comprised 87 MTCs (30 germline and 57 sporadic). Slides for each case were reviewed by 2 pathologists and histologic features recorded. Ki67 immunostaining was performed on all cases. Each MTC was graded with the IMTCGS based on tumor necrosis, Ki67PI, and mitotic count. Cox regression analysis was performed to assess the impact of various clinical and pathological data on disease outcomes, including overall survival (OS), disease-free survival, disease-specific survival (DSS), and distant metastasis-free survival. In our MTC cohort, 18.4% (n = 16/87) were IMTCGS high grade. IMTCGS grade was strongly prognostic for OS, disease-free survival, DSS, and distant metastasis-free survival on univariate analysis and multivariable analysis in both the entire MTC cohort and in the sporadic subset. Among the individual IMTCGS parameters, while all 3 were associated with poorer survival outcomes on univariate analysis, necrosis had the strongest association with all survival parameters on multivariable analysis, whereas Ki67PI or mitotic count was associated only with OS and DSS. This retrospective study independently demonstrates that the IMTCGS is valid for grading MTCs. Our findings support incorporating IMTCGS into routine pathology practice. IMTCGS grading may help clinicians to better predict the prognosis of MTC. Future studies may shed light on how MTC grading should impact treatment protocols.

Work-to-family effects of inclusive leadership: The roles of work-to-family positive spillover and complementary values.

Drawing on work-family enrichment theory, we explore whether inclusive leadership leads to employees' work-to-family positive spillover, which further improves their family performance. We also focus on the moderating role of complementary values. A time-lagged study was conducted and the sample included 292 employees from two hotels. The results indicate that inclusive leadership triggers employees' work-to-family positive spillover, and then their family performance is enhanced. Moreover, employees' complementary values may strengthen the positive effect of inclusive leadership. We also provide theoretical and practical implications of the results.

An Unexpected Magnet Response of a Biotronik Pacemaker in Automatic Mode: A Case Report.

In patients with cardiovascular implantable electronic devices, asynchronous pacing is necessary for surgeries with a risk of electromagnetic interference. Magnets are often used for asynchronous pacing. In this case report, magnet application to a Biotronik Evia DR-T pacemaker (Biotronik) programmed to a magnet response mode called automatic magnet mode (AUTO) led to a brief period of asynchronous pacing before reverting to prior settings, an unexpected response that was not revealed on the preoperative interrogation report. For Biotronik pacemakers programmed to the AUTO mode, changes in programming are needed for asynchronous pacing.

Automatic detection of head and neck squamous cell carcinoma on histologic slides using hyperspectral microscopic imaging (Erratum).

The erratum corrects the name of the first author listed in a reference cited.

A Multicenter Randomized Phase II Study of Single Agent Efficacy and Optimal Combination Sequence of Everolimus and Pasireotide LAR in Advanced Thyroid Cancer.

PURPOSE: Aberrant mTOR pathway and somatostatin receptor signaling are implicated in thyroid cancer and offer potential therapeutic targets. We assessed the clinical efficacy of everolimus and Pasireotide long-acting release (LAR) in radioiodine-refractory differentiated thyroid cancer (DTC) and medullary thyroid cancer (MTC). PATIENTS AND METHODS: Adults with progressive MTC and DTC untreated or treated with no more than one systemic agent were eligible. The trial was designed to establish the most promising regimen and the optimal combination sequence. Patients were randomized to start treatment with single agent everolimus (10 mg QD; Arm A), pasireotide-LAR (60 mg intramuscular injection, Q4 weeks; Arm B), or the combination (Arm C). At initial progression (PFS1), patients on Arm A or B switched to the combination and continued until progression (PFS2). Efficacy was measured by RECIST criteria. RESULTS: Study enrolled 42 patients: median age 65 years; female 17 (40.5%); White 31 (73.8%), African American 6 (14.3%), others 5 (11.9); DTC 32 (76.2%); MTC 10 (23.8%). There was no objective response by RECIST criteria across the three arms. Median and 1-year PFS1 rates were 8.3, 1.8, 8.1 months and 49.9%, 36.4%, 25.0% for Arms A, B, C, respectively. Median and 1-year PFS2 rates were 26.3, 17.5, 8.1 months and 78.4%, 70.0%, 25% for Arms A, B, C, respectively. The most frequent adverse events were anemia, stomatitis, fatigue, hyperglycemia, and hypercholesterolemia. CONCLUSIONS: The combination of everolimus and pasireotide-LAR showed promising efficacy over single agent. The delayed combination of everolimus and pasireotide-LAR following progression on single agent everolimus appeared intriguing as a combination strategy.

Automatic detection of head and neck squamous cell carcinoma on histologic slides using hyperspectral microscopic imaging.

SIGNIFICANCE: Automatic, fast, and accurate identification of cancer on histologic slides has many applications in oncologic pathology. AIM: The purpose of this study is to investigate hyperspectral imaging (HSI) for automatic detection of head and neck cancer nuclei in histologic slides, as well as cancer region identification based on nuclei detection. APPROACH: A customized hyperspectral microscopic imaging system was developed and used to scan histologic slides from 20 patients with squamous cell carcinoma (SCC). Hyperspectral images and red, green, and blue (RGB) images of the histologic slides with the same field of view were obtained and registered. A principal component analysis-based nuclei segmentation method was developed to extract nuclei patches from the hyperspectral images and the coregistered RGB images. Spectra-based support vector machine and patch-based convolutional neural networks (CNNs) were implemented for nuclei classification. The CNNs were trained with RGB patches (RGB-CNN) and hyperspectral patches (HSI-CNN) of the segmented nuclei and the utility of the extra spectral information provided by HSI was evaluated. Furthermore, cancer region identification was implemented by image-wise classification based on the percentage of cancerous nuclei detected in each image. RESULTS: RGB-CNN, which mainly used the spatial information of nuclei, resulted in a 0.81 validation accuracy and 0.74 testing accuracy. HSI-CNN, which utilized the spatial and spectral features of the nuclei, showed significant improvement in classification performance and achieved 0.89 validation accuracy as well as 0.82 testing accuracy. Furthermore, the image-wise cancer region identification based on nuclei detection could generally improve the cancer detection rate. CONCLUSIONS: We demonstrated that the morphological and spectral information contribute to SCC nuclei differentiation and that the spectral information within hyperspectral images could improve classification performance.

Pediatric intraoperative nerve monitoring during thyroid surgery: A review from the American Head and Neck Society Endocrine Surgery Section and the International Neural Monitoring Study Group.

Children are more likely to experience recurrent laryngeal nerve (RLN) injury during thyroid surgery. Intraoperative nerve monitoring (IONM) may assist in nerve identification and surgical decision making. A literature review of pediatric IONM was performed and used to inform a monitoring technique guide and expert opinion statements. Pediatric IONM is achieved using a variety of methods. When age-appropriate endotracheal tubes with integrated surface electrodes are not available, an alternative method should be used. Patient age and surgeon experience with laryngoscopy influence technique selection; four techniques are described in detail. Surgeons must be familiar with the nuances of monitoring technique and interpretation; opinion statements address optimizing this technology in children. Adult IONM guidelines may offer strategies for surgical decision making in children. In some cases, delay of second-sided surgery may reduce bilateral RLN injury risk.

Qualitative Study of Mentorship for Women and Minorities in Surgery.

BACKGROUND: Despite the growth of mentorship opportunities for women in surgery, women remain largely underrepresented in the surgical field. Mentorship is an effective strategy to increase female entry and retention within surgical careers. There is limited literature evaluating mentorship for women in surgery across different career levels and racial backgrounds. STUDY DESIGN: In-depth interviews were conducted with female fourth-year medical students applying for a surgical residency, female surgical residents, and female surgical faculty from a single academic institution. RESULTS: A total of 35 women in surgery, including 14 faculty, 11 residents, and 10 fourth-year medical students were interviewed. Twenty (57%) self-identified as White, 7 (20%) as Asian, 6 (17.1%) as Black, and 2 (5.7%) as Other. Key themes included: (1) access to mentorship, (2) characteristics valued in a mentor, (3) role of gender identity when choosing a mentor, (4) role of racial identity when choosing a mentor, and (5) importance of early mentorship for women and underrepresented minorities in medicine (URiM). Mentorship was important for early career development. Mentors who were approachable, invested in their mentees, and were available and honest were most valued. Shared gender and racial identity were appreciated most by younger and URiM mentees, respectively. Respondents from each career level acknowledged the importance of early mentorship for women and URiM in surgery to facilitate increased diversity in the surgical field. CONCLUSION: Mentorship plays a pivotal role in early career development for women in the surgical field. Access to mentors with shared gender and racial compositions can provide a unique level of support for female and URiM mentees. Expanded and earlier mentorship access for women and minority students can increase diversity in the surgical field.

Suturing the gender gap through sponsorship: The role of sponsorship in female entry and advancement through their surgical careers.

BACKGROUND: Sponsorship promotes female entry and advancement through the surgical field, and can mitigate gender inequities that persist in the surgical field. METHODS: 35 women in surgery, including 14 surgeons, 11 residents, and 10 fourth-year medical students, were interviewed from July 30, 2021 to August 18, 2021 at a single institution. RESULTS: All participants had provided or received sponsorship. Main themes included: (1) Evolving needs of sponsorship, (2) Decreased Access to Sponsorship as Career Level Advances, (3) Evolving importance of sponsorship, (4) Perceived limitations of receiving sponsorship, and (5) Perceived limitations of providing sponsorship. Faculty members most frequently reported barriers to both receiving and providing sponsorship. CONCLUSIONS: The lack of sponsorship for female faculty limits their ability to rise to organizational leadership, and consequently, their ability to sponsor others. Increasing access to sponsorship for female surgeons can help to bridge the gender gap in the surgical field.

Detecting Aggressive Papillary Thyroid Carcinoma Using Hyperspectral Imaging and Radiomic Features.

Hyperspectral imaging (HSI) and radiomics have the potential to improve the accuracy of tumor malignancy prediction and assessment. In this work, we extracted radiomic features of fresh surgical papillary thyroid carcinoma (PTC) specimen that were imaged with HSI. A total of 107 unique radiomic features were extracted. This study includes 72 ex-vivo tissue specimens from 44 patients with pathology-confirmed PTC. With the dilated hyperspectral images, the shape feature of least axis length was able to predict the tumor aggressiveness with a high accuracy. The HSI-based radiomic method may provide a useful tool to aid oncologists in determining tumors with intermediate to high risk and in clinical decision making.

Thyroid Carcinoma Detection on Whole Histologic Slides Using Hyperspectral Imaging and Deep Learning.

Hyperspectral imaging (HSI), a non-invasive imaging modality, has been successfully used in many different biological and medical applications. One such application is in the field of oncology, where hyperspectral imaging is being used on histologic samples. This study compares the performances of different image classifiers using different imaging modalities as training data. From a database of 33 fixed tissues from head and neck patients with follicular thyroid carcinoma, we produced three different datasets: an RGB image dataset that was acquired from a whole slide image scanner, a hyperspectral (HS) dataset that was acquired with a compact hyperspectral camera, and an HS-synthesized RGB image dataset. Three separate deep learning classifiers were trained using the three datasets. We show that the deep learning classifier trained on HSI data has an area under the receiver operator characteristic curve (AUC-ROC) of 0.966, higher than that of the classifiers trained on RGB and HSI-synthesized RGB data. This study demonstrates that hyperspectral images improve the performance of cancer classification on whole histologic slides. Hyperspectral imaging and deep learning provide an automatic tool for thyroid cancer detection on whole histologic slides.

Automatic detection of head and neck squamous cell carcinoma on pathologic slides using polarized hyperspectral imaging and deep learning.

The study is to incorporate polarized hyperspectral imaging (PHSI) with deep learning for automatic detection of head and neck squamous cell carcinoma (SCC) on hematoxylin and eosin (H&E) stained tissue slides. A polarized hyperspectral imaging microscope had been developed in our group. In this paper, we firstly collected the Stokes vector data cubes (S0, S1, S2, and S3) of histologic slides from 17 patients with SCC by the PHSI microscope, under the wavelength range from 467 nm to 750 nm. Secondly, we generated the synthetic RGB images from the original Stokes vector data cubes. Thirdly, we cropped the synthetic RGB images into image patches at the image size of 96×96 pixels, and then set up a ResNet50-based convolutional neural network (CNN) to classify the image patches of the four Stokes vector parameters (S0, S1, S2, and S3) by application of transfer learning. To test the performances of the model, each time we trained the model based on the image patches (S0, S1, S2, and S3) of 16 patients out of 17 patients, and used the trained model to calculate the testing accuracy based on the image patches of the rest 1 patient (S0, S1, S2, and S3). We repeated the process for 6 times and obtained 24 testing accuracies (S0, S1, S2, and S3) from 6 different patients out of the 17 patients. The preliminary results showed that the average testing accuracy (84.2%) on S3 outperformed the average testing accuracy (83.5%) on S0. Furthermore, 4 of 6 testing accuracies of S3 (96.0%, 87.3%, 82.8%, and 86.7%) outperformed the testing accuracies of S0 (93.3%, 85.2%, 80.2%, and 79.0%). The study demonstrated the potential of using polarized hyperspectral imaging and deep learning for automatic detection of head and neck SCC on pathologic slides.

Automatic detection of head and neck squamous cell carcinoma on pathologic slides using polarized hyperspectral imaging and machine learning.

The aim of this study is to incorporate polarized hyperspectral imaging (PHSI) with machine learning for automatic detection of head and neck squamous cell carcinoma (SCC) on hematoxylin and eosin (H&E) stained tissue slides. A polarized hyperspectral imaging microscope had been developed in our group. In this paper, we imaged 20 H&E stained tissue slides from 10 patients with SCC of the larynx by the PHSI microscope. Several machine learning algorithms, including support vector machine (SVM), random forest, Gaussian naive Bayes, and logistic regression, were applied to the collected image data for the automatic detection of SCC on the H&E stained tissue slides. The performance of these methods was compared among the collected PHSI data, the pseudo-RGB images generated from the PHSI data, and the PHSI data after applying the principal component analysis (PCA) transformation. The results suggest that SVM is a superior classifier for the classification task based on the PHSI data cubes compared to the other three classifiers. The incorporate of four Stokes vector parameters improved the classification accuracy. Finally, the PCA transformed image data did not improve the accuracy as it might lose some important information from the original PHSI data. The preliminary results show that polarized hyperspectral imaging can have many potential applications in digital pathology.

Perioperative pain management and opioid-reduction in head and neck endocrine surgery: An American Head and Neck Society Endocrine Surgery Section consensus statement.

BACKGROUND: This American Head and Neck Society (AHNS) consensus statement focuses on evidence-based comprehensive pain management practices for thyroid and parathyroid surgery. Overutilization of opioids for postoperative pain management is a major contributing factor to the opioid addiction epidemic however evidence-based guidelines for pain management after routine head and neck endocrine procedures are lacking. METHODS: An expert panel was convened from the membership of the AHNS, its Endocrine Surgical Section, and ThyCa. An extensive literature review was performed, and recommendations addressing several pain management subtopics were constructed based on best available evidence. A modified Delphi survey was then utilized to evaluate group consensus of these statements. CONCLUSIONS: This expert consensus provides evidence-based recommendations for effective postoperative pain management following head and neck endocrine procedures with a focus on limiting unnecessary use of opioid analgesics.

StayHome: A FHIR-Native Mobile COVID-19 Symptom Tracker and Public Health Reporting Tool.

As the COVID-19 pandemic continues to unfold and states experience the impacts of reopened economies, it is critical to efficiently manage new outbreaks through widespread testing and monitoring of both new and possible cases. Existing labor-intensive public health workflows may benefit from information collection directly from individuals through patient-reported outcomes (PROs) systems. Our objective was to develop a reusable, mobile-friendly application for collecting PROs and experiences to support COVID-19 symptom self-monitoring and data sharing with appropriate public health agencies, using Fast Healthcare Interoperability Resources (FHIR) for interoperability. We conducted a needs assessment and designed and developed StayHome, a mobile PRO administration tool. FHIR serves as the primary data model and driver of business logic. Keycloak, AWS, Docker, and other technologies were used for deployment. Several FHIR modules were used to create a novel "FHIR-native" application design. By leveraging FHIR to shape not only the interface strategy but also the information architecture of the application, StayHome enables the consistent standards-based representation of data and reduces the barrier to integration with public health information systems. FHIR supported rapid application development by providing a domain-appropriate data model and tooling. FHIR modules and implementation guides were referenced in design and implementation. However, there are gaps in the FHIR specification which must be recognized and addressed appropriately. StayHome is live and accessible to the public at https://stayhome.app. The code and resources required to build and deploy the application are available from https://github.com/uwcirg/stayhome-project.