This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.

This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.

Facial emotion expressions play a central role in interpersonal interactions; these displays are used to predict and influence the behavior of others. Despite their importance, quantifying and analyzing the dynamics of brief facial emotion expressions remains an understudied methodological challenge. Here, we present a method that leverages machine learning and network modeling to assess the dynamics of facial expressions. Using video recordings of clinical interviews, we demonstrate the utility of this approach in a sample of 96 people diagnosed with psychotic disorders and 116 never-psychotic adults. Participants diagnosed with schizophrenia tended to move from neutral expressions to uncommon expressions (e.g., fear, surprise), whereas participants diagnosed with other psychoses (e.g., mood disorders with psychosis) moved toward expressions of sadness. This method has broad applications to the study of normal and altered expressions of emotion and can be integrated with telemedicine to improve psychiatric assessment and treatment.

Background

Sentinel lymph node (SLN) surgery is used worldwide for staging breast cancer patients and helps limit axillary lymph node dissection. [(99m)Tc]Tilmanocept is a novel receptor-targeted radiopharmaceutical evaluated in 2 open-label, nonrandomized, within-patient, phase 3 trials designed to assess the lymphatic mapping performance.

Methods

A total of 13 centers contributed 148 patients with breast cancer. Each patient received [(99m)Tc]tilmanocept and vital blue dye (VBD). Lymph nodes identified intraoperatively as radioactive and/or blue stained were excised and histologically examined. The primary endpoint, concordance (lower boundary set point at 90 %), was the proportion of nodes detected by VBD and [(99m)Tc]tilmanocept.

Results

A total of 13 centers contributed 148 patients who were injected with both agents. Intraoperatively, 207 of 209 nodes detected by VBD were also detected by [(99m)Tc]tilmanocept for a concordance rate of 99.04 % (p < 0.0001). [(99m)Tc]tilmanocept detected a total of 320 nodes, of which 207 (64.7 %) were detected by VBD. [(99m)Tc]Tilmanocept detected at least 1 SLN in more patients (146) than did VBD (131, p < 0.0001). In 129 of 131 patients with ≥1 blue node, all blue nodes were radioactive. Of 33 pathology-positive nodes (18.2 % patient pathology rate), [(99m)Tc]tilmanocept detected 31 of 33, whereas VBD detected only 25 of 33 (p = 0.0312). No pathology-positive SLNs were detected exclusively by VBD. No serious adverse events were attributed to [(99m)Tc]tilmanocept.

Conclusion

[(99m)Tc]Tilmanocept demonstrated success in detecting a SLN while meeting the primary endpoint. Interestingly, [(99m)Tc]tilmanocept was additionally noted to identify more SLNs in more patients. This localization represented a higher number of metastatic breast cancer lymph nodes than that of VBD.

As the immuno-oncology field continues the rapid growth witnessed over the past decade, optimising patient outcomes requires an evolution in the current response-assessment guidelines for phase 2 and 3 immunotherapy clinical trials and clinical care. Additionally, investigational tools-including image analysis of standard-of-care scans (such as CT, magnetic resonance, and PET) with analytics, such as radiomics, functional magnetic resonance agents, and novel molecular-imaging PET agents-offer promising advancements for assessment of immunotherapy. To document current challenges and opportunities and identify next steps in immunotherapy diagnostic imaging, the National Cancer Institute Clinical Imaging Steering Committee convened a meeting with diverse representation among imaging experts and oncologists to generate a comprehensive review of the state of the field.