Faculty Bibliography

Precision-targeted ultrasonic neuromodulation offers immense potential for studying brain function and treating neurological diseases. Yet, its application has been limited by challenges in achieving precise spatio-temporal control and monitoring of ultrasound effects on brain circuits. Here we show that transcranial ultrasound elicits direct and highly focal responses, which can be dynamically steered at spatio-temporal scales relevant for neural function. Furthermore, holographic transcranial ultrasound stimulation allows direct control of the stimulated volume and actively modulates local and mid-range network projections, effectively lowering the activation threshold by an order of magnitude. To better understand this previously unexplored excitability regime not fully explained by the conventional pressure-frequency dyad, we developed a dual modelling framework, where both an empirical and a mechanistic model were constructed to capture the intricacies of holographic transcranial ultrasound stimulation. These models achieve qualitative agreement with our experimental results, suggesting that these findings are predominantly driven by putative network interactions. Our results bring insight on the complex interaction mechanisms of ultrasound with neural tissue and highlight its potential for the noninvasive interfacing of distributed brain networks.

OBJECTIVES/OBJECTIVE:Multicenter research of geriatric emergency department (GED) care remains limited. Our objectives were to: 1. Prospectively collect data prioritized by the Geriatric Emergency care Applied Research (GEAR) network, a transdisciplinary taskforce for GED care, and create a multicenter GED research repository of prospective and electronic health record (EHR) data, 2. Assess concordance between prospective and EHR data. METHODS:The GEAR Standardization Study (GEARSS) is a multicenter, prospective study of older emergency department (ED) patients (65+) focusing on the 4Ms of age-friendly care (mobility, medication safety, mentation, what matters) and elder mistreatment. Demographic and clinical data were collected via interviews by trained research assistants (RA) on Days 0, 4, 30, and 90 and linked to EHR. Prevalence of chronic comorbidities and incident delirium were measured and reported using descriptive statistics. Prospective and EHR data concordance was assessed with Cohen's Kappa. RESULTS:999 participants were recruited from 5 EDs (3/25/2021-6/30/2022) across 3 institutions: Grady Health System, Northwestern Memorial Hospital, and Yale New Haven Health. The cohort was 57.0% female, 55.2% White, 39.1% Black, and 3.4% Hispanic, and the mean age was 75.1 years. For rheumatologic disease, peptic ulcer disease, diabetes, renal disease, and cancer, prevalence differed between prospective and EHR data by > 10%. About two-thirds of participants were at risk for falls. Concordance between prospective and EHR data was good for ethnicity (K = 0.73); excellent for sex (K = 1.00), age (K = 1.00), and race (K = 0.98); fair for disposition (K = 0.53); slight for ED observation status (K = 0.33) and dementia diagnosis (K = 0.24); poor for delirium presence (K = 0.07). CONCLUSION/CONCLUSIONS:In GEARSS, demographic variables aligned strongly between prospective and EHR data, while diagnosis, disposition, and mentation factors did not. This multicenter data source provides preliminary findings for common geriatric syndromes and conditions. Choice of measures using these data should be driven by GED research questions.

OBJECTIVE:Childhood inhibited temperament (cIT) is associated with an increased risk for developing internalizing psychopathology. Neurobiological characteristics identified by structural magnetic resonance imaging (MRI) may elucidate the neural substrates for cIT, but studies are scarce and often focus on particular regions of interest. Moreover, current findings lack replication. This pre-registered analysis from the ENIGMA-Anxiety Working Group examined structural brain characteristics associated with cIT using a comprehensive whole-brain approach. METHOD/METHODS:Temperament assessments (behavioral observations, parental/teacher reports or self-reports on cIT before age 13) and MRI-data (age at scan: 6-25 years) from international research sites (Europe, North America, South America) were pooled for mega-analysis. Following image processing and quality control, associations between cIT and brain structure were examined in 3,803 participants. Subcortical volumes, cortical thickness and surface area (main analyses) and detailed subcortical characteristics (e.g. subnuclei, subfields, partial volume effects; exploratory analyses) were considered. RESULTS:= 0.029) in youth with parental/teacher reports on cIT-levels. Exploratory analyses revealed findings in hippocampus, putamen and caudate, but most did not survive statistical correction for multiple testing. CONCLUSION/CONCLUSIONS:This mega-analysis found no consistent associations between cIT and regional brain structure, although the role of parietal regions warrants further investigation. Future studies should consider brain function in cIT, preferably using longitudinal designs.

BACKGROUND:As the digital age progresses, individuals are increasingly seeking online websites for the dissemination of information. YouTube, the most popular free video streaming platform worldwide, garners over 2 billion users. Plastic surgery information is widely available on YouTube and acts as a common interface for the distribution of plastic surgery-related information. This investigation aimed to identify trends in YouTube videos describing common plastic surgery search terms based on narrator gender, channel type, and language patterns. METHODS:Top-ranking videos for six common plastic surgery search terms were queried. Video characteristics and transcripts for each video were extracted. Transcripts were subsequently analyzed using the Linguistic Inquiry and Word Count software. Comparisons were performed using various statistical analysis methods. RESULTS:Significant differences in audience engagement were noted by search topic (p < 0.05). Speakers in plastic surgery videos were predominantly male only (108 [60%]), with notable variation observed across channel type and search topic. Significant differences were found for videos on medical professional channels (p = 0.004) and videos regarding gynecomastia (p < 0.05). Linguistic pattern analysis revealed that female speakers used more authentic (p = 0.01) and emotional (p = 0.012) language than male speakers. CONCLUSION/CONCLUSIONS:With YouTube being the most visited online video platform website worldwide, plastic surgeons must understand trends to appropriately tailor their content and maximize their social media reach. Also, while plastic surgery is making strides in the right direction, continued work should be done in promoting adequate representation among online material. NO LEVEL ASSIGNED/METHODS:This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

OBJECTIVES/OBJECTIVE:Post-colonoscopy colorectal cancer (PCCRC) represents an important real-world colonoscopy quality indicator. Using a national database, we evaluated predictors of PCCRC in fecal immunochemical test (FIT)-positive individuals, determined the PCCRC 3-year rate (PCCRC-3y), and performed a root cause analysis (RCA). METHODS:This retrospective cohort study evaluated FIT-positive patients who underwent colonoscopy from January 2015 to July 2022. Data was collected from the Veterans Affairs (VA) national database. PCCRC was defined as CRC detected ≥6 months after colonoscopy. CRC was identified using SNOMED codes and the VA Cancer Registry. The World Endoscopy Organization methodology was used to perform the RCA and calculate the PCCRC-3y rate. RESULTS:We identified 132 PCCRCs among 52,167 FIT-positive individuals. The PCCRC-3y rate was 6.4% (95% CI, 5.0-7.7%). PCCRC locations were proximal colon (43.2%), distal colon (34.8%), and rectum (22%). Root causes were likely new CRC (17.4%), missed lesions with adequate (31.2%) or inadequate (9.8%) examination, incomplete polyp resection (22%), and detected but unresected lesions (19.7%). 16.7% of patients with PCCRC had poor bowel preparation on index colonoscopy. The cecal intubation rate was 88.6% and rectal retroflexion rate was 84.5%. In 14.4% of cases, recommended surveillance intervals did not adhere to established guidelines. Independent predictors of PCCRC were ages 70-79 (HR 7.86; 95% CI, 1.08-57.39), age ≥80 (HR 10.18; 95% CI, 1.06-97.98), tubulovillous adenoma (HR 3.98; 95% CI, 2.52-6.29), and adenoma with high-grade dysplasia (HR 10.15; 95% CI, 5.91-17.42). CONCLUSIONS:Among FIT-positive individuals, the PCCRC-3y rate was 6.4%, with missed lesions and incomplete resection as key contributors. These findings provide useful information on quality metrics in FIT-based CRC screening programs.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Gynecological cancers represent 10% to 15% of cancers in women, but brain metastases (BM) are uncommon, with limited evidence regarding their management. This study investigates the role of stereotactic radiosurgery (SRS) for BM from primary gynecological cancers. METHODS:Institutions of the International Radiosurgery Research Foundation participated in this study. Inclusion criteria required histological diagnosis of epithelial ovarian, cervical, or endometrial cancer, SRS between 2000 and 2020, and at least 1 imaging or clinical follow-up. RESULTS:A total of 276 patients having SRS for 977 BM were included. Median age at SRS was 62 years (IQR, 55-70). Primary cancer origin was ovarian in 128 (46%), cervical in 43 (16%), and endometrial in 105 patients (38%). Median Karnofsky Performance Scale was 80%, and systemic disease was active in 124 (45%) of patients. A median of 1 metastasis was treated (IQR, 1-3) per patient. Median individual metastasis volume was 0.27 cc (IQR, 0.05-1.59 cc). The majority (91%) received single-fraction SRS, using a median margin dose of 18 Gy (IQR, 16-20 Gy). Actuarial overall survival was 77%, 65%, and 44% at 6, 12, and 24 months, respectively. Predictors of worsened survival included older age, cervical and endometrial primary, previous whole-brain radiation therapy (WBRT), active systemic disease, worsened Karnofsky Performance Scale, absence of subsequent surgery, and increasing number of BM. Actuarial local control was 94% at 6 months, 89% at 12 months, and 78% at 24 months. Previous SRS or WBRT, tumor bed treatment, and cervical histology increased the risk of local failure. New remote BM and leptomeningeal dissemination occurred in 44% and 11% of patients, respectively. Adverse radiation effects (ARE) occurred in 13% of cases but were symptomatic in only 3%. Previous WBRT or SRS and increased tumor diameter increased the risk of ARE. CONCLUSION/CONCLUSIONS:SRS is an effective management for BM from gynecological cancers with low risks of symptomatic ARE.

BACKGROUND:High-risk infant follow-up (HRIF) lacks universal definition. The aim of this study was to report current practice and factors used to identify eligibility for HRIF, yielding information which may provide a basis for future consensus. METHODS:A survey was prepared for a workshop at the 15th International Newborn Brain Conference on prediction of outcome, which was subsequently distributed to all attendees (n = 426). RESULTS:Follow-up was offered by 97% of respondents (n = 113/116). HRIF was offered to infants born <28 weeks by 47%, to those <32 weeks by two-thirds (66%) and to preterms based on neuroimaging by 54%. For infants born full-term, HRIF was offered by 88% in neonatal encephalopathy (NE) and 86% in neonatal stroke. HRIF continued most frequently until 24 months corrected (33.6%). For guiding prognosis in preterm infants, 22% (n = 25) selected neuroimaging as the most important factor. For NE, 54% (n = 63) selected neuroimaging findings as the most important factor in guiding prognosis and 14% (n = 16) selected EEG/aEEG. Social factors are not considered by 46% in determining HRIF eligibility. CONCLUSION/CONCLUSIONS:Significant variability in HRIF exists, without consensus. Awareness of factors predicting prognosis and the importance of social risk-factors must improve to allow accurate identification of those at highest risk. This information may act as a basis for future consensus on HRIF. IMPACT/CONCLUSIONS:There is no clear consensus on eligibility or duration of high-risk infant follow-up. We report current practice in, and factors used to identify eligibility for same, amongst attendees of the International Newborn Brain Conference. This information on international practice may provide a basis for future consensus. Given the importance of accurate prognostication in risk-stratification, we report participants' awareness of the most important factors guiding prognosis. A disconnect between the impact of social factors on outcome and their consideration for eligibility of high-risk infant follow-up is noted. We propose the need for guidelines on follow-up of socially disadvantaged, medically high-risk infants.

Dental enamel protects against the invasion of bacterial pathogens deep into the innervated layers of the tooth. Hereditary enamel disorders referred to as amelogenesis imperfecta (AI) can severely affect the development and mineralization of dental enamel compromising these functions. This rare disorder is often visible, carries a significant psychological and financial burden, and cosegregates with disease in other organs. Pathological variants in over 100 genes affect the enamel formation. Here, we describe the biology of enamel formation focusing on pathogenic variants underlying AI. We provide a computational model encapsulating new advances in calcium regulation during enamel formation. We also describe the psychological and financial burden of AI, its impact in systemic health, and discuss recent developments in diagnostic panels to detect AI.

BACKGROUND AND AIMS/OBJECTIVE:Endoscopic full-thickness resection (EFTR) is an established, safe technique for the resection of appendiceal orifice (AO) neoplasms. Post-EFTR appendicitis is a recognised adverse event. There are no systematic reviews and a paucity of literature which has assessed outcomes especially with respect to delayed appendicitis, mucocele, or fistula formation. We aimed to evaluate efficacy of EFTR for AO lesions. PATIENTS AND METHODS/METHODS:Consecutive AO lesions referred for consideration of EFTR were prospectively studied. Multiple data points were recorded including technical success, EFTR histopathological data, adverse events, and follow-up surveillance data by colonoscopy. Surveillance CT was performed due to concern of potential mucocele from the obstructed remnant appendix. RESULTS:Over a 4 year period to July 2023, 37 AO lesions were referred to a tertiary center for consideration of EFTR. EFTR was attempted in 35 (95%) lesions. Most lesions were small [median size 10mm, interquartile range (IQR) 10-15mm], Paris 0-IIa morphology (n=32, 91%) with serrated histopathology (n=17, 49%). R0 resection was achieved in most EFTR cases (n=30/35, 86%). Adverse events included appendicitis (n=4, 11%) and delayed bleeding (n=2, 6%). At 6-month (IQR 4-6 months) surveillance colonoscopy, there was 1 (3%) case of residual lesion. This was successfully treated endoscopically, confirmed on a second surveillance colonoscopy. There was one case of appendicitis of the remnant at 7 months. At surveillance CT abdomen/pelvis (median 15 months, IQR 7-37 months), 2/17 (12%) fistulas were identified. Both of these patients had presumed adhesions due to abdominal surgery prior to EFTR. CONCLUSIONS:In conclusion, EFTR is an effective technique for the curative resection of select, small (<15mm) Paris 0-IIa AO lesions. Appendicitis is a relatively common adverse event but often managed conservatively. The long-term significance post-EFTR fistulas remains unclear. Caution should be exercised when considering EFTR in a patient with prior regional surgery.

OBJECTIVES/OBJECTIVE:Despite its high negative predictive value (NPV) for clinically significant prostate cancer (csPCa), MRI suffers from a substantial number of false positives, especially for intermediate-risk cases. In this work, we determine whether a deep learning model trained with PI-RADS-guided representation learning can disambiguate the PI-RADS 3 classification, detect csPCa from bi-parametric prostate MR images, and avoid unnecessary benign biopsies. MATERIALS AND METHODS/METHODS:This study included 28,263 MR examinations and radiology reports from 21,938 men imaged for known or suspected prostate cancer between 2015 and 2023 at our institution (21 imaging locations with 34 readers), with 6352 subsequent biopsies. We trained a deep learning model, a representation learner (RL), to learn how radiologists interpret conventionally acquired T2-weighted and diffusion-weighted MR images, using exams in which the radiologists are confident in their risk assessments (PI-RADS 1 and 2 for the absence of csPCa vs. PI-RADS 4 and 5 for the presence of csPCa, n=21,465). We then trained biopsy-decision models to detect csPCa (Gleason score ≥7) using these learned image representations, and compared them to the performance of radiologists, and of models trained on other clinical variables (age, prostate volume, PSA, and PSA density) for treatment-naïve test cohorts consisting of only PI-RADS 3 (n=253, csPCa=103) and all PI-RADS (n=531, csPCa=300) cases. RESULTS:On the 2 test cohorts (PI-RADS-3-only, all-PI-RADS), RL-based biopsy-decision models consistently yielded higher AUCs in detecting csPCa (AUC=0.73 [0.66, 0.79], 0.88 [0.85, 0.91]) compared with radiologists (equivocal, AUC=0.79 [0.75, 0.83]) and the clinical model (AUCs=0.69 [0.62, 0.75], 0.78 [0.74, 0.82]). In the PIRADS-3-only cohort, all of whom would be biopsied using our institution's standard of care, the RL decision model avoided 41% (62/150) of benign biopsies compared with the clinical model (26%, P<0.001), and improved biopsy yield by 10% compared with the PI-RADS ≥3 decision strategy (0.50 vs. 0.40). Furthermore, on the all-PI-RADS cohort, RL decision model avoided 27% of additional benign biopsies (138/231) compared to radiologists (33%, P<0.001) with comparable sensitivity (93% vs. 92%), higher NPV (0.87 vs. 0.77), and biopsy yield (0.75 vs. 0.64). The combination of clinical and RL decision models further avoided benign biopsies (46% in PI-RADS-3-only and 62% in all-PI-RADS) while improving NPV (0.82, 0.88) and biopsy yields (0.52, 0.76) across the 2 test cohorts. CONCLUSIONS:Our PI-RADS-guided deep learning RL model learns summary representations from bi-parametric prostate MR images that can provide additional information to disambiguate intermediate-risk PI-RADS 3 assessments. The resulting RL-based biopsy decision models also outperformed radiologists in avoiding benign biopsies while maintaining comparable sensitivity to csPCa for the all-PI-RADS cohort. Such AI models can easily be integrated into clinical practice to supplement radiologists' reads in general and improve biopsy yield for any equivocal decisions.