Stony Brook Research Articles

Rogue AI: Cautionary Cases in Neuroradiology and What We Can Learn From Them.

Introduction In recent years, artificial intelligence (AI) in medical imaging has undergone unprecedented innovation and advancement, sparking a revolutionary transformation in healthcare. The field of radiology is particularly implicated, as clinical radiologists are expected to interpret an ever-increasing number of complex cases in record time. Machine learning software purchased by our institution is expected to help our radiologists come to a more prompt diagnosis by delivering point-of-care quantitative analysis of suspicious findings and streamlining clinical workflow. This paper explores AI's impact on neuroradiology, an area accounting for a substantial portion of recent radiology studies. We present a case series evaluating an AI software's performance in detecting neurovascular findings, highlighting five cases where AI interpretations differed from radiologists' assessments. Our study underscores common pitfalls of AI in the context of CT head angiograms, aiming to guide future AI algorithms. Methods We conducted a retrospective case series study at Stony Brook University Hospital, a large medical center in Stony Brook, New York, spanning from October 1, 2021 to December 31, 2021, analyzing 140 randomly sampled CT angiograms using AI software. This software assessed various neurovascular parameters, and AI findings were compared with neuroradiologists' interpretations. Five cases with divergent interpretations were selected for detailed analysis. Results Five representative cases in which AI findings were discordant with radiologists' interpretations are presented with diagnoses including diffuse anoxic ischemic injury, cortical laminar necrosis, colloid cyst, right superficial temporal artery-to-middle cerebral artery(STA-MCA) bypass, and subacute bilateral subdural hematomas. Discussion The errors identified in our case series expose AI's limitations in radiology. Our case series reveals that AI's incorrect interpretations can stem from complexities in pathology, challenges in distinguishing densities, inability to identify artifacts, identifying post-surgical changes in normal anatomy, sensitivity limitations, and insufficient pattern recognition. AI's potential for improvement lies in refining its algorithms to effectively recognize and differentiate pathologies. Incorporating more diverse training datasets, multimodal data, deep-reinforcement learning, clinical context, and real-time learning capabilities are some ways to improve AI's performance in the field of radiology. Conclusion Overall, it is apparent that AI applications in radiology have much room for improvement before becoming more widely integrated into clinical workflows. While AI demonstrates remarkable potential to aid in diagnosis and streamline workflows, our case series highlights common pitfalls that underscore the need for continuous improvement. By refining algorithms, incorporating diverse datasets, embracing multimodal information, and leveraging innovative machine learning strategies, AI's diagnostic accuracy can be significantly improved.

Cultivating compassion in medicine: a toolkit for medical students to improve self-kindness and enhance clinical care

BackgroundCompassionate care lies at the foundation of good patient care and is a quality that patients and providers continue to value in the fast-paced setting of contemporary medicine. Compassion is often discussed superficially in medical school curricula, but the practical aspect of learning this skill is often not taught using a formal framework. In the present work, the authors present an 8-session curriculum with a mindfulness-based approach to compassion that addresses this need. It is hypothesized that students in this curriculum will improve in their levels of compassion based on validated scales.MethodsThe curriculum was delivered to fourth-year medical students at Renaissance School of Medicine at Stony Brook University who had just completed their clerkship year. It was developed as a customizable set of modules that could be delivered in various ways. The students were taught with evidence-based cognitive exercises followed by group discussions and written reflections based on compassion-focused thematic questions. All students completed a pre- and post-Self-Compassion Scale, Compassion Scale, and Toronto Mindfulness Scale. Students in this course were compared with students in different courses about non-clinical topics delivered at the same time. Wilcoxon Signed Rank tests and Mann Whitney U tests were used to assess potential associations between pre- and post-survey responses for the validated scales and subscales.Results17 fourth-year medical students completed pre- and post-course tests, 11 participated in the compassion curriculum while 6 participated from the other courses. Before any of the courses began, all students performed similarly on the pre-test across all scales. The students in the compassion curriculum demonstrated a significant increase in their total Self-Compassion score by 8.7 [95% CI 4.3 to 13.2] points (p = 0.008), total Compassion score by 6.0 [95% CI 1.4 to 10.6] points (p = 0.012), and the curiosity component of the Toronto Mindfulness Scale by 4.4 [95% CI 1.0 to 7.7] points (p = 0.012). There was no statistically significant difference between pre- and post-tests among the non-compassion curriculum students in the aforementioned scales (p = 0.461, p = 0.144, p = 0.785, respectively).ConclusionsOur results indicate that the students in our course developed an enhanced ability to engage in self-compassion, to understand the shared human experience, and to be motivated to act to alleviate suffering. Regardless of a program’s existing compassion education, this customizable model allows for easy integration into a medical student’s crowded curriculum. Furthermore, although teaching compassion early and often in a clinician’s training is desirable, our study that targeted fourth-year medical students suggests an additional benefit of rekindling the loss of compassion well described in a medical student’s clinical years.

Demographic and Diagnostic Factors in Physical Therapy Attendance.

Introduction Physical therapy (PT) is an effective nonoperative treatment for various orthopedic diagnoses. However, patients may have many reasons to dismiss PT, including favoringanother intervention for their injury, time constraints, transportation, and cost. This dismissal of PT may contribute to inadequate patient compliance. This study aimed to elucidate patient compliance with a basic PT prescription and whether PT led to subjective injury improvement. Methods This is a retrospective study of patients observed in Stony Brook Orthopedic clinics from 08/01/2022 to 12/23/2022. Patients prescribed PT received a phone call six weeks after the PT prescription. The primary outcome was patient attendance at PT. Secondary outcomes were subjective; symptomatic improvement was listed asbetter, worse, or the same. Chi-square testing was used to compare outcomes. Results A total of 100 patients were enrolled in the study. Patients prescribed PT following surgery were more likely to attend compared to patients prescribed PT as a primary treatment (P value=0.027). The association between attendance at PT and a change in subjective symptoms (better, worse, same) was not significant. Patients' age, sex, and chronicity of injury were not significant factors in PT attendance. Of the 40 patients who did not attend PT, 14 cited time constraints, 11 utilized self-directed treatment, three cited insurance, two cited transportation, and 10 cited other reasons. Conclusions Overall, postoperative patients were more likely to attend PT compared to patients prescribed PT as a primary treatment. Factors such as age, sex, and chronicity of injury did not affect whether a patient attended PT. Of the patients enrolled, 71% stated subjective improvement in symptoms, but there was no association between symptoms and PT attendance. This study highlights the characteristics of those patient factors that may influence PT compliance and underscores the importance of further research into the population most likely to attend and benefit from PT.

Microscale Updrafts within Northeast U.S. Coastal Snowstorms Using High-Resolution Cloud Radar Measurements

Abstract Limited knowledge exists about ∼100-m-scale precipitation processes within U.S. northeast coastal snowstorms because of a lack of high-resolution observations. We investigate characteristics of microscale updraft regions within the cyclone comma head and their relationships with snowbands, wind shear, frontogenesis, and vertical mass flux using high-spatiotemporal-resolution vertically pointing Ka-band radar measurements, soundings, and reanalysis data for four snowstorms observed at Stony Brook, New York. Updraft regions are defined as contiguous time–height plotted areas with upward Doppler velocity without hydrometeor sedimentation that is equal to or greater than 0.4 m s−1. Most updraft regions in the time–height data occur on a time scale of seconds (<20 s), which is equivalent to spatial scales < 500 m. These small updraft regions within cloud echo occur more than 30% of the time for three of the four cases and 18% for the other case. They are found at all altitudes and can occur with or without frontogenesis and with or without snowbands. The updraft regions with relatively large Doppler spectrum width (>0.4 m s−1) occur more frequently within midlevels of the storms, where there are strong wind shear layers and moist shear instability layers. This suggests that the dominant forcing for the updrafts appears to be turbulence associated with the vertical shear instability. The updraft regions can be responsible for upward mass flux when they are closer together in space and time. The higher values of column mean upward mass flux often occur during snowband periods. Significance Statement Small-scale (<500 m) upward motions within four snowstorms along the U.S. northeast coast are analyzed for the first time using high-spatiotemporal-resolution millimeter-wavelength cloud radar pointed vertically. The analysis reveals that updrafts appear in the storms regardless of whether snowbands are present or whether there is larger-scale forcing for ascent. The more turbulent and stronger updrafts frequently occur in midlevels of storms associated with instability from vertical shear and contribute to upward mass flux during snowband periods when they are closer together in space and time.

The high-performance DIRC for the ePIC detector at the EIC

The next-generation nuclear physics facility in the United States will be the Electron-Ion Collider (EIC), scheduled to be built at Brookhaven National Laboratory (BNL). Excellent particle identification (PID) is one of the key requirements for the EIC central detector called ePIC. Identification of the hadrons in the final state is critical to study how different quark flavors contribute to nucleon properties. A detector using the Detection of Internally Reflected Cherenkov light (DIRC) principle, with a radial size of only 7-8 cm, was chosen as the PID system for the ePIC barrel region. Within the framework of the EIC R&D programs, the development of a high-performance DIRC (hpDIRC) detector was undertaken with the aim of significantly advancing state-of-the-art performance. Key components of the hpDIRC detector are a 3-layer compound lens and small pixel-size photo sensors. Currently, the hpDIRC R&D program is focused on developing and validating the radiation hard 3-layer lens, quality assurance of the BaBar DIRC radiation bars, and the early stage of the hpDIRC prototype program with Cosmic Ray Telescope at Stony Brook University, in preparation for beam tests at Fermilab in 2024.

Synthesis of Hybrid Data Consisting of Chest Radiographs and Tabular Clinical Records Using Dual Generative Models for COVID-19 Positive Cases.

To generate synthetic medical data incorporating image-tabular hybrid data by merging an image encoding/decoding model with a table-compatible generative model and assess their utility. We used 1342 cases from the Stony Brook University Covid-19-positive cases, comprising chest X-ray radiographs (CXRs) and tabular clinical data as a private dataset (pDS). We generated a synthetic dataset (sDS) through the following steps: (I) dimensionally reducing CXRs in the pDS using a pretrained encoder of the auto-encoding generative adversarial networks (αGAN) and integrating them with the correspondent tabular clinical data; (II) training the conditional tabular GAN (CTGAN) on this combined data to generate synthetic records, encompassing encoded image features and clinical data; and (III) reconstructing synthetic images from these encoded image features in the sDS using a pretrained decoder of the αGAN. The utility of sDS was assessed by the performance of the prediction models for patient outcomes (deceased or discharged). For the pDS test set, the area under the receiver operating characteristic (AUC) curve was calculated to compare the performance of prediction models trained separately with pDS, sDS, or a combination of both. We created an sDS comprising CXRs with a resolution of 256 × 256 pixels and tabular data containing 13 variables. The AUC for the outcome was 0.83 when the model was trained with the pDS, 0.74 with the sDS, and 0.87 when combining pDS and sDS for training. Our method is effective for generating synthetic records consisting of both images and tabular clinical data.

Implementation and mixed-methods evaluation of "Walk with a Doc" program at Stony Brook.

Walking groups run by trained individuals, lasting under an hour in a natural environment, may be a cost-effective way by which to encourage sustainable changes in physical activity as well as foster companionship and a shared experience of wellness among participants. Walk with a Doc (WWaD) is a national program that provides a platform for medical professionals, including physicians and medical students, to deliver a short talk on a health topic prior to walking side by side with patients and community members. To evaluate the WWaD Chapter at Stony Brook following implementation, a questionnaire was designed utilizing a mixed-methods approach (i.e.,containing qualitative and quantitative items) and administered to all attendees monthly prior to the health discussion. The aim of the questionnaire was fourfold: first, to obtain participant demographics; second, to obtain information on attendees' own perceptions of their health status and the role exercise plays in their health; third, to gain data on physical activity levels, including lengths of exercise sessions and types of activities performed; and fourth, to learn more about attendees' motivations and goals for participating in the walks. We received an IRB exemption. Physician and medical student volunteers were recruited from Stony Brook University Hospital, a suburban tertiary care center, to oversee program logistics. WWaD was scheduled to take place on the third Sunday of every month for 1 h at Heritage Park in Mount Sinai, New York. The event was advertised by volunteers to colleagues, peers, patients, and community members utilizing word of mouth, printed flyers, emails to listservs, and social media outlets. Each month, a physician volunteer oversaw a brief discussion (approximately 10 min in length). Over the course of the 5 month evaluation period, 91individuals participated in the walks, including repeat attendees. After excluding duplicate or incomplete entries, data from 30 participants were included in this analysis. The majority of participants were female (n=24) with a mean age of 50 years (range, 23-98 years). Feedback on WWaD program elements was largely positive. Participants commended the monthly speakers for "informative talks" (n=6) on "interesting topics" (n=4), with plans to review the supplemental information in educational pamphlets following the walk (n=4). The brochures were also deemed "helpful." Overwhelmingly, patients referred to the community gathering and team building aspects of WWaD as the "most enjoyable" aspect of the program (n=8) and a key driver for participation. This mixed-methods study of the WWaD chapter at Stony Brook contributes to a growing body of evidence highlighting the value of walking groups as effective avenues for collaboration in producing accessible healthy behavior.

Life Is About Change: A Professional Memoir.

Receiving my doctorate in 1961 just as John F. Kennedy was inaugurated president of the United States, I was inspired by his sentiment that any person can make a difference, and every person should try. In this memoir I review my professional journey of trying to make a difference in researching, teaching, supervising, and practicing clinical psychology and psychotherapy. I began my career by working on an evidence base for projective techniques. Upon joining the Stony Brook faculty, I shifted my efforts to research on and practice of behavior therapy, and then to the incorporation of cognition in developing cognitive behavioral therapy. Further work on integration consisted of closing the gap between research and practice, lowering the barriers that existed across schools of therapy, and incorporating lesbian, gay, bisexual, and transgender issues into mainstream psychology.

Abstract TP164: Predisposing Factors and Outcomes of Primary Intracerebral Hemorrhage in Patients Presenting With Hyponatremia

Background: Hyponatremia is the most common electrolyte abnormality seen in intracerebral hemorrhage (ICH) and is associated with a nearly doubled mortality rate and more severe presentations. However, the current literature has not addressed what factors might predispose ICH patients to presenting with hyponatremia or developing it during their hospital stay. The aim of this study was to evaluate the characteristics, comorbidities, and inpatient outcomes prevalent amongst ICH patients with hyponatremia. Methods: A retrospective study was performed for 814 adult patients admitted from January 2011-December 2022 with primary ICH at Stony Brook University Hospital. We recorded sodium and serum chemistry levels throughout admission, medical history, radiographic hematoma volumes, and Modified Rankin Scale (MRS) and Glasgow Coma Scale (GCS) up to 1-year follow-up. Results: Hyponatremia on admission was seen in 79 (9.8%) patients. Another 311 patients (38.3%) developed hyponatremia during their hospital stay. Pre-existing hyponatremia was correlated with a history of diabetes while hyponatremia during stay was correlated with diabetes, liver disease, heavy drinking, and prior valve replacement. Complications such as pneumonia, UTI, or a bloodstream infection were more prevalent in patients with hyponatremia. They also had a longer hospital stay and higher inpatient mortality (χ2(1)=5.176, p=0.023). Patients with hyponatremia had significantly lower GCS values on discharge. A multivariate regression analysis of age, admission MRS, diabetes, liver disease, ICH score, volume, and minimum Na was statistically significant ( R 2=0.255, F(7,704)=34.46, p<0.001). Minimum Na reliably predicted death in this model (β=0.007, p=0.023). Conclusions: Several factors can predispose ICH patients to hyponatremia on presentation or be associated with developing hyponatremia during their hospital stay. This study showed that developing hyponatremia during the hospital stay was associated with worse outcomes at discharge. In addition, hyponatremia can significantly predict inpatient mortality when controlling for ICH severity and common aggravating factors.

Abstract C067: Correlation of keratin17 expression with tumor cell proliferation and invasion in PDAC

Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) shows variable degrees of differentiation, with both intratumoral, regional, and case to case heterogeneity, including glandular elements, sheet-like aggregates, cell clusters, and single diffusely infiltrative tumor cells. Prior research from our lab and others have established keratin 17 (K17) to be a defining hallmark of the basal molecular subtype of PDAC. In addition to its role as a component of the cytoskeleton, soluble forms of K17 undergo nuclear translocation to drive cell cycle progression and chemoresistance to first line chemotherapy. While K17 is heterogeneously expressed in the gland-forming elements of PDACs, it is most consistently expressed in tumor cells which are either in small groups or are single diffusely infiltrative. The aims of the current study are to define the correlation between K17 expression and tumor cell differentiation, with the focus on glandular versus single diffusely infiltrative components of PDAC, and to relate these findings to established biomarkers of cell proliferation and invasion. Methods: Archival human PDACs were provided by the Stony Brook Cancer Center Biobank and K17 immunohistochemistry was performed by indirect immunoperoxidase method, as previously described, to select cases with both glandular and diffusely infiltrative cell components and heterogeneous K17 expression. Multiplex immunofluorescence with a panel of antibodies to K17 (Cell Signaling Technology), pan-cytokeratin, Ki-67 and vimentin [KS1] (Miltenyi Biotec) was performed on 5-micron FFPE sections using the MACSima system (Miltenyi Biotec). Distribution patterns of K17 were evaluated in glandular and diffusely invasive components and were related to the Ki-67 status. Results: Cytoplasmic staining for K17 was found in the minority of tumor cells in glands and displayed intraglandular heterogeneity but was found in most diffusely infiltrative tumor cells. Also, nuclear K17 was rarely detected in the glandular components but was found in a high proportion of the diffusely infiltrative cells. Ki-67 was detected mainly in glandular cells, unrelated to K17 status, and rarely in single diffusely infiltrative cells, never co-localizing with nuclear K17. Of note, only a small fraction of tumor cells co-expressed K17 and vimentin, suggesting that majority of diffusely infiltrative tumor cells were not engaged in epithelial to mesenchymal transition. Conclusion: While cytoplasmic K17 is heterogeneously expressed in the glandular components of PDAC, strong staining for K17 in both the cytoplasm and the nucleus is a hallmark of diffusely infiltrative, Ki-67-negative tumor cells. These observations support the paradigm that tumor cells are committed to either cell division in the glandular components, or to diffuse single cell invasion, highlighted by increased cytoplasmic and nuclear K17 expression. Therefore, the results emphasize the importance of understanding the expression of PDAC biomarkers in both gland-forming elements and diffusely infiltrative tumor cells. Citation Format: Shayan Sarkar, Lyanne Oblein, Michael Horowitz, Luisa Escobar-Hoyos, Natalia Marchenko, Kenneth Shroyer. Correlation of keratin17 expression with tumor cell proliferation and invasion in PDAC [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C067.

Abstract B065: Biomarker approach to define tumor subtype in pancreatic ductal adenocarcinoma

Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal tumors with a predicted five-year survival rate in 2023 of 12%. Building on prior observations that molecular subtypes correlate with survival and response to treatment, our goal has been to understand the patterns of expression and prognostic correlations of three reciprocally expressed proteins previously identified as surrogate biomarkers of PDAC subtypes. Keratin 17 (K17) and Keratin 5 (K5) have both been identified as biomarkers of the basal subtype whereas GATA6, a transcription factor necessary for normal pancreatic development, is a surrogate marker of the classical subtype associated with longer-term survival. Here, we explore the expression of these three diagnostic biomarkers in PDAC and their specificity to tumor cells. Methods: Immunohistochemical analyses of K17 (KDx Diagnostics), GATA6 (R&D Systems), and KT5 (Leica) were performed on archival primary PDAC specimens from Stony Brook University Hospital (n= 30), by routine immunoperoxidase methods on serial sections. IHC stained slides were scanned using an Olympus VS200 slide scanner and images were imported into QuPath for digital analysis. Regions of interest (ROIs) were defined by the presence of tumor cells and were identified by histological assessment of representative sections. Digital scoring was performed on identified ROIs using the integrated "positive cell detection" function in QuPath and classified into three different stain intensities (1+, 2+, 3+). The threshold for each intensity is as follows: 1+, 0.2; 2+, 0.4; 3+, 1.0. According to the number of detections of each intensity, tumor cells were categorized into negative (0 and 1+) or positive (2+ and 3+). The percentage positive of analyzed biomarker expression within the tumor ROI was calculated by dividing the total number of positive cells by the total number of detected cells. Results: K17 was detected in both well and poorly differentiated PDAC components and in a few benign proliferative ducts of chronic pancreatitis but no staining was detected in stromal cells, benign ductal epithelium, or acinar cells. K5 was detected in a smaller proportion of cells from glandular components of the tumor as well as in most diffusely infiltrative single cells, benign ductal, and acinar cells but not in stromal cells. By contrast, GATA6 was detected in the nuclei of most cancer epithelial cells and was also detected in benign ductal cells, acinar cells, and stromal cells. The proportion of K17 expressing cells exceeded that of K5 positive cells in the great majority of ROIs and across cases. Conclusions: Keratin 17 detects a higher proportion of tumor cells than K5 and shows the lowest level of expression in benign cell types. By contrast, GATA6 IHC shows variable patterns of expression related to K17 or K5 expression and is expressed in the highest proportion of tumor cells, including both well-differentiated, diffusely infiltrative components, and benign tissue components. Citation Format: Carson Ho, Michael Horowitz, Lyanne Oblein, Shayan Sarkar, Soma Kobayashi, Karen Bai, Natalia Marchenko, Luisa Escobar-Hoyos, Kenneth Shroyer. Biomarker approach to define tumor subtype in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr B065.

Abstract A068: Proteomic analysis of keratin 17 positive cells from laser-capture microdissected pancreatic ductal adenocarcinoma

Abstract Introduction. Although patients with pancreatic ductal adenocarcinoma (PDAC) have one of the lowest survival of all carcinomas, there is considerable variation in survival and disease progression, even when accounting for factors such as age and pathologic stage. Our group identified keratin 17 (K17) as a negative prognostic and predictive biomarker in PDAC. Patients with high K17 expression in their tumors have shorter overall survival as well as decreased response to chemotherapeutic agents, including gemcitabine. K17 has also emerged as an established biomarker of the basal molecular subtype of PDAC. In this study, we aim to identify proteins which correlate, directly or indirectly, with K17 expression via a combined approach using immunohistochemistry (IHC) followed by laser capture microdissection (LCM) and mass spectrometry. Methods. We selected 5 PDAC cases of low K17 expression and 5 PDAC cases of high K17 expression from the archival collections from the Stony Brook Cancer Center Biobank. A modified indirect immunoperoxidase approach was performed on sections mounted on LCM-compatible membrane slides. Carcinoma cells that were either K17 positive or negative by IHC were precisely dissected using LMD7 microscope (Leica) from 10-µM thick sections, followed by a modified tissue digestion and protein extraction protocol. Collision-induced fragment mass information and peptide abundance values were obtained by a liquid chromatography-electrospray ionization tandem mass spectrometry (LC-MS/MS). Spectral cutoffs were analyzed at both <5% and 1% false discovery rates. The human UniProt dataset was used for data alignment. Results. Mass spectrometry yielded over 1600 detected proteins with approximately 50 of which correlated strongly with K17 expression. Our preliminary results show that keratin 5, a known marker of basal-like PDAC, is positively correlated with keratin 17. Genes whose increased expression contribute to the Moffitt classification of basal molecular subtype of PDAC, such as S100A2, keratin 6A and keratin 7, also showed positive correlation with K17 in our study. The remainder of proteins associated with K17 expression include those involved with cell adhesion, cell-extracellular matrix interaction and smooth muscle contraction pathways, with specific types and classes being identified, pending in-depth analysis. Proteins with inverse relationship to K17 expression included those involved in intracellular organelle trafficking and apoptosis pathways. Conclusion. Our findings demonstrate the utility of mass spectrometry-based spatial proteomic analysis of microdissected cell populations from formalin-fixed, paraffin embedded samples. These methods have the potential to uncover complementary biomarkers to K17 that could enhance prognostic accuracy or serve as therapeutic targets and provide mechanistic insight into the mechanisms through which K17 drives tumor aggression. Citation Format: Ji Dong K. Bai, John D. Haley, Natalia Marchenko, Luisa F. Escobar-Hoyos, Kenneth R. Shroyer. Proteomic analysis of keratin 17 positive cells from laser-capture microdissected pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr A068.

Abstract B041: Keratin 17 excludes CD8-positive T cells and recruits CD163-positive macrophages in pancreatic ductal adenocarcinoma

Abstract Background. Keratin 17 (K17) is a negative prognostic and predictive biomarker, overexpressed in the biologically most aggressive forms of pancreatic ductal adenocarcinoma (PDAC). In other anatomic sites and disease processes, K17 expression impacts the inflammatory microenvironment, correlating with changes in the expression of inflammatory cytokines and the infiltration of CD8+ T cells. Thus, we hypothesized that K17 expression also impacts the immune response in PDAC. Methods. We aimed to determine the relationship between intratumoral and peritumoral immune cell infiltrates versus K17 expression in tumor cells, using brightfield multiplexed immunohistochemistry (mIHC) and our suite of deep learning tools to quantitatively evaluate the expression of four biomarkers of T-cells and macrophages. The study included a multi-institutional cohort of 235 PDAC cases from Stony Brook University Hospital (n=54), Thomas Jefferson University (n=67), Cedars Sinai Medical Center (n=7) and Know Your Tumor PanCAN-Perthera (n=107). Peritumoral immune cells were scored in zones defined as stromal tissue within ≤25 µm of the closest tumor cell. Intratumor immune cells were defined as those that physically touched or overlapped with tumor cells. Immune cell counts in peritumoral and intratumoral K17-negatvie areas of the tumor were normalized to immune cell counts in K17-positive areas. Results. The density of CD8+ T cells in K17-negative peritumoral zones was greater than in K17-positive peritumoral zones in 82.6% of PDACs. Similarly, the density of intratumoral CD8+ T cells in K17-negative areas was greater than in K17-positive areas in 93.2% of cases. Less striking inverse correlations for immune cell density relative to K17 expression were found for CD4+ peritumor lymphocytes and both intratumoral and peritumor CD16+ macrophages. By contrast, CD163+ (tumor-promoting) macrophages were more numerous in K17+ peritumoral and intratumoral zones. All differences were statistically significant and independent of tumor grade, stage, histologic subtype, and neoadjuvant treatment history (p< 0.0001). Conclusions. Correlations between K17 and inflammatory cells suggests K17 expression negatively influences the number and infiltration of T-cells and contributes to the marked immunosuppressive effect of PDAC. These findings suggest that the biologic impact of K17 goes beyond its role as a negative prognostic biomarker that impacts tumor growth, metastasis, and chemoresistance, to suppress the immune response to PDAC. Understanding how K17 influences immune cell function may inform future immunotherapeutic opportunities for PDAC treatment. Citation Format: Lyanne Oblein, Sruthi Babu, Mariana Torrente-Goncalves, Lucia Roa, Michael Horowitz, Mahmudul Hasan, Danielle Fassler, Jaymie Oentoro, Emanuel Petricoin, Lynn M. Matrisian, Natalia Marchenko, Edik Blais, Felicia Allard, Ali Alkalin, Wei Jiang, Brent Larson, Andrew Hendifar, Chao Chen, Shahira Abousamra, Dimitris Samaras, Tahsin Kurc, Joel Saltz, Luisa Escobar-Hoyos, Kenneth Shroyer. Keratin 17 excludes CD8-positive T cells and recruits CD163-positive macrophages in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr B041.

Cosmetic outcomes of simple facial laceration suturing in the pediatric emergency department

Purpose: The long-term cosmetic outcomes of simple facial lacerations have not been well addressed, specifically regarding those of suturing by pediatric emergency physicians (PEPs) and plastic surgery (PS) residents. Methods: A retrospective study was performed at the pediatric emergency department of Shaare Zedek Medical Center in Jerusalem, Israel. Cosmetic outcomes of simple facial lacerations sutured within 1 year of the study were reviewed using digital photographs taken by legal guardians of children sutured in the department. The photographs were reviewed and rated blindly using the Stony Brook scar score as measures of cosmetic outcomes by 2 plastic surgeons and 1 PEP, as well as the general numeric score (GNS) rated by the guardians and the 3 doctors. The scores were compared between children sutured by PEPs (PEP group) and those sutured by PS residents (PS group). A sample size of 50 children in each study group was calculated to have enough power to show a difference. Results: Among a total of 108 children who participated in the study (median age, 4.0 years [interquartile range, 3.0-7.0]), 57 and 51 were sutured by PEPs and PS residents, respectively. Guardian-rated median GNS showed no difference between the 2 groups (PEP, 90.0 [70.0-95.0] vs. PS, 90.0 [60.0-90.0]; P = 0.310). In contrast, doctor-rated median GNS was higher in the PEP group (PEP, 75.0 [63.3-86.7] vs. PS, 70.0 [53.3-83.3]); P = 0.046). A Stony Brook scar score of 3 or higher was similarly frequent in both groups (PEP, 87.7% vs. PS, 74.5%; P = 0.173) with a low interrater agreement (Kappa = 0.36). Conclusion: Cosmetic outcomes of simple facial lacerations in the pediatric emergency department were favorable regardless of the specialty or expertise of doctors. The guardians were more satisfied with the outcomes, compared to the doctors.

Lonely but not alone: Loneliness and social positive valence sensitivity in emerging adults' everyday lives

Loneliness predicts a range of highly negative outcomes and is a rising problem among young adults. The current study examines the basic processes associated with young adult loneliness. In the Stony Brook Temperament Study, 320 18 year-olds completed an ecological momentary assessment (2 weeks; 5 assessments/day) of whether they had recently socialized, and the extent to which the social experience was positive or negative. They also completed trait measures of general positive valence sensitivity (PVS), social PVS, depression, and loneliness. The amount of socializing was not associated with loneliness, while subjectively positive social experiences (but not negative), social PVS, and depression were. The current study highlights the role of social PVS hyposensitivity in young adult loneliness.

Study on the management of granulation during surgery for congenital preauricular fistula infection stage

Objective:To investigate the management of granulation tissue during surgery for infected congenital preauricular fistula and to assess the surgical outcomes. Methods:To summarize the surgical methods and the treatment of granulation methods in 140 cases of congenital preauricular fistula during the period of infection treated in our department from January 2018 to September 2022. The study divided patients into an observation group （79 patients） undergoing fistulectomy without granulation treatment, and a control group （61 patients） where fistulectomy and granulation resection were performed concurrently.. After six months of follow-up, the wound healing, recurrence rates, and the aesthetic assessment of granulation healing were evaluated using the Stony Brook Scar Evaluation Scale（SBSES）. Results:The two surgical approaches were applied to a total of 140 patients with infected congenital preauricular fistula. There was no statistical difference in wound healing and recurrence rates between the observation group and the control group. However, the observation group exhibited smaller scars. Conclusion:In cases of infected congenital preauricular fistula, surgical removal without excising granulation tissue is feasible, leading to effective healing and lesser scar formation.

Printing Solidarity: An Experiment in Pedagogical Curating

Abstract: This article is a co-written reflection on the process of curating and programming Printing Solidarity: Tricontinental Graphics from Cuba (2021–2022). Held at Stony Brook University's Paul W. Zuccaire Gallery, the exhibition featured over sixty posters and printed matter produced mostly in the 1960s–1970s by the Organization of Solidarity with the People of Asia, Africa, and Latin America (OSPAAAL) in Havana. As an experiment in pedagogical curating, the yearlong project spanned the isolation from, return to, and re-envisioning of inperson learning during the COVID-19 pandemic. Reflecting on our inspirations, intentions, and challenges, we argue for the role of art objects in activating material-based, in-person learning on campus and consider the value of academic collaboration, cross-regional research, and experimental pedagogies. The project offered an opportunity to revisit the Cold War-period politics of global solidarity in today's pandemic era while exploring what it would mean to study art today from the question of solidarity rather than division.

Psychometric Performance of the Stony Brook Scar Evaluation Scale and SCAR-Q Questionnaire in Dutch Children after Pediatric Surgery.

Introduction: The growing population of survivors following pediatric surgery emphasizes the importance of long-term follow-up. The impact of surgical scars on daily life can be evaluated through patient-reported outcome measurements. The Stony Brook Scar Evaluation Scale (SBSES) and SCAR-Q questionnaire are two interesting instruments for this purpose. We evaluated their psychometric performance in Dutch children after pediatric surgery. Methods: After English-Dutch translation, we evaluated-following the COSMIN guidelines-the feasibility, reliability (internal and external), and validity (construct, criterion, and convergent) of the SBSES and SCAR-Q in Dutch patients < 18 years old with surgical scars. Results: Three independent observers completed the SB for 100 children (58% boys, median age 7.3 (IQR 2.5-12.1) years) in whom surgery had been performed a median of 2.8 (0.5-7.9) years ago. Forty-six of these children (61% boys, median age 12.1 (9.3-16.2) years) completed the SCAR-Q. Feasibility and internal reliability (Cronbach's alpha > 0.7) was good for both instruments. For the SB, external reliability was poor to moderate (interobserver variability: ICC 0.46-0.56; intraobserver variability: ICC 0.74). For the SCAR-Q, external reliability was good (test-retest agreement: ICC 0.79-0.93). Validity tests (construct, criterion, and convergent) showed poor to moderate results for both instruments. Conclusions: The Dutch-translated SBSES and SCAR-Q showed good feasibility and internal reliability. External reliability and validity were likely affected by differences in conceptual content between the questionnaires. Combining them would provide insight in the impact of scars on patients. Implementation of these instruments in longitudinal follow-up programs could provide new insights into the long-term psychological outcome after pediatric surgery.

Abstract C134: Efficacy of mobile mammography and state-funded cancer services in reducing disparities in follow-up adherence: A retrospective analysis

Abstract Objective: Mobile mammography programs, such as the one at Stony Brook Cancer Center (SBCC), play an important role in providing breast cancer screening services to underserved communities. Follow-up to abnormal mammogram screenings is critical for early cancer detection, but patients often encounter barriers that prevent timely diagnostic procedures. We aim to evaluate the role of New York State’s Cancer Services Program (CSP) in facilitating follow-up care among underserved patients who participated in SBCC’s mobile mammography initiative. Methods: We conducted a retrospective analysis of 817 mobile mammography patients who required additional testing following an abnormal mammogram over a five-year period. Of these, 68% were beneficiaries of the CSP, while 32% were insured. Results: Our findings revealed that among CSP beneficiaries, only 3.5% were lost to follow-up, compared to a significant 16.5% of insured patients who did not adhere to recommended follow-up care. This suggests that the CSP’s supportive role is critical in ensuring follow-up care among underserved communities. Conclusions: The CSP’s substantial impact on follow-up care adherence highlights the program's effectiveness in reducing healthcare disparities. However, more work is needed to enhance follow-up care adherence among insured patients. Solutions may include identifying and addressing barriers to care and implementing targeted interventions to improve patient outcomes. Implications for Policy or Practice: Mobile mammography programs, such as SBCC’s initiative, demonstrate a potential strategy for reducing health disparities in breast cancer screening and detection. Securing access to follow-up care is crucial for improving patient outcomes. Addressing barriers to care, strengthening patient education, and enhancing outreach efforts can increase participation in screening initiatives, thus advancing health equity and reducing disparities in breast cancer outcomes. Citation Format: Patrick J. Dineen, Mollie M. Williams. Efficacy of mobile mammography and state-funded cancer services in reducing disparities in follow-up adherence: A retrospective analysis [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr C134.

A Deep Learning-Based Pathomics Methodology for Quantifying and Characterizing Nucleated Cells in the Bone Marrow Microenvironment

Introduction: The overall cellularity of the bone marrow (BM) microenvironment is a WHO criterion for differentiating BCRABL- myeloproliferative neoplasms (MPNs) like polycythemia vera (PV) and myelofibrosis (MF) [1]. However, manual assessment by hematopathologists is subjective, not scalable, and only records a single global measure, disregarding BM regional differences. Leveraging pathology slide scanners and deep learning (DL) can address these limitations and reveal valuable insights into MPN subtypes and treatment effects. Despite its potential, computational pathology (Pathomics) in this area remains understudied [2-3]. Methods: After institutional review from Stony Brook University and Weill Cornell Medicine (WCM), we identified 54 patients (pts) with a manually confirmed PV diagnosis (dx) at WCM (17% newly dx'ed, 61% treated, 17% disease progression). The dataset includes hematoxylin &amp; eosin (H&amp;E) stained whole slide images (WSIs), labs, molecular studies, and pathology report elements (reference standard for biopsy core size and cellularity). Numeric cellularity measures the ratio of hematopoietic cells to fat cells and excludes inevaluable trabecular bone. Normal cellularity ranges from (100-pt age [y])±20% and PV is characterized by hypercellularity. We evaluated three DL algorithms for nuclear segmentation: 1) Our U-Net model trained on 5B nuclei from 10 cancer types [4], 2) HistoCartography (HC): a graph neural network trained on 235K nuclei (PanNuke/MoNuSac datasets) [5], and 3) CellPose (CP): a gradient-driven U-Net model trained on 1K nuclei of varied modalities [6]. A color/morphology-based segmenter identified fat cells and evaluable BM regions, excluding vessels/tissue tears. Cellular characteristics (shape, texture, color) were computed and clustered by k-nearest neighbors (kNN) and k-means to explore differences between PV stages. A tissue-based approach for cellularity estimation derived the proportion of non-fat tissue to evaluable regions. A cell-based approach derived the proportions of nucleated cell and fat cell areas. The study calculated mean differences between biopsy core size estimates, assessed correlation (r) and intra-class correlation (ICC) for numeric cellularity estimates, and Cohen's kappa (κ) for categorical cellularity estimates. Results: Measured and estimated biopsy core sizes differed by an acceptable margin (3±4 mm). Tissue-based cellularity estimator results: r=0.2, ICC=0.0, κ=0.2. Cell-based cellularity estimator result: our approach (r=0.7, ICC=0.6, κ=0.7), HC (r=0.7, ICC=0.5, κ=0.6), and CP (r=0.2, ICC=0.2, κ=0.7). Cell size clusters aligned with known distributions in PV, with the prominent Int1 class (5.1-9μm) likely containing erythrocytes and myeloid progenitors. Overall and cell-sized cellularity heatmaps visualize regional differences (Figure 1). K-means clustering separated new and progressing PV (Figure 2). Discussion: DL and classical image analysis were employed to segment nucleated cells, fat cells, and other evaluable regions of hematopoietic tissue. Extracting shape, texture, and color features from segmented nuclei enhances BM microenvironment characterization. This pilot study resulted in a practical and interpretable Pathomics pipeline and downstream analytics as a proof of concept for hypothesis-driven research. Future directions involve applying these insights to a large cohort of diagnosis WSIs from other MPN subtypes and correlating findings with other tools, like immune cell detection models.