br Table br ROC AUC values
ROC AUC values for human tissue staining with Quizartinib (AC220) 1.
Tissue type ROC AUC
a 60% exocrine epithelium, 20% endocrine epithelium, 20% ducts; bpancreatic intraepithelial neoplasia non-tumor struc-tures with 10% exocrine epithelium, 5% endocrine epithelium,
c tumor grade G2 (moderately diﬀerentiated); dtumor grade G3 (poorly diﬀerentiated).
Fig. 5. Signal quantification from PDAC KMC mouse model tissue represented as pixel intensity histograms. Unstained PDAC control tissue (left) and PDAC tissue stained with 1 (right) using the optimized protocol: 125 µM with 5 min incubation, rinse and 5 min PFA incubation (total 15 min). The separation of pixel values in stained tissue is evidence of its eﬃciency in selective PDAC targeting over surrounding stroma tissue.
antibody conjugates takes between 24 and 48 h to obtain an image, which is not practical for surgery. In the previous study, 1 was shown to achieve specificity to PDAC in a PDAC mouse model without the need for conjugation to an antibody or any complex targeting ligands. Herein, we have shown that it can be used for analyzing human PDAC frozen tissue sections following a short 15-min staining protocol. It exhibits enhanced accumulation in the ducts of the adenocarcinoma versus the surrounding stroma tissue. In addition, it stains PanIN pre-cancerous lesions which may be useful for investigating the progression of PDAC.
Unlike the current FSA stain (H&E), 1 aﬀords quantifiable images and PDAC specificity. The fluorescence in pancreas tissue was quanti-fied using ROC curves. The high contrast between the stroma and the adenocarcinoma in 1 stained tissue can serve as marker for PDAC. For example, it may enable margin assessment both qualitatively and quantitatively since stained healthy pancreas tissue does not show ap-preciable contrast under the same processing conditions (e.g., Figs. 3 and 5, Table 2). Moreover, ex vivo frozen section staining using 1 under the optimized conditions described herein takes place in nearly the same amount of time as H&E staining. It is also promising that high contrast was also observed in the tissue sample containing the PanIN pancreatic cancer precursor lesions. This may potentially enable early monitoring and the investigation of PDAC progression.
This work was supported by the National Institutes of Health (R15EB016870).
All authors contributed equally.
Declaration of Competing Interest
The authors declare no completing financial interests.
Appendix A. Supplementary data
European Annals of Otorhinolaryngology, Head and Neck diseases xxx (2019) xxx–xxx
Available online at
Assessment of impairment of intelligibility and of speech signal after oral cavity and oropharynx cancer
c Laboratoire Octogone-Lordat, URI Octogone-Lordat (EA4156), maison de la recherche, université de Toulouse II Jean-Jaurès, 5, allée Antonio-Machado, 31058 Toulouse cedex 9, France
Oral cavity cancer
Background: Perceptual evaluation is a means of assessing speech disorder severity in clinical practice.
Although limited in reliability and reproducibility, its ease of application makes it very widely used.
Choice of assessment criteria and type of speech sample are key points.
Objective: To compare a panel’s perceptual evaluations on two tasks with different criteria.
Material and method: The corpus comprised 87 samples from patients treated for oral cavity or orophar-ynx cancer, assessed by 6 experts on two criteria (impairment of intelligibility and of speech signal) and two kinds of speech sample (semi-spontaneous versus reading speech) Results: Although strong correlations were found between tasks (r > 0.8), the speech signal criterion gave a score distribution providing a better metric. Severity was greater in oral cavity (mean, 5.44 ± 2.47) than oropharyngeal cancer (6.46 ± 2.24). Semi-spontaneous speech tended to show less severity score ceiling effect than reading speech (mean, 6.06/10 for picture description and 6.51/10 for reading).
Conclusion: Speech signal impairment in semi-spontaneous speech seems to be the best clinical measure to assess speech disorder following treatment of oral cavity or oropharynx cancer.
© 2019 Elsevier Masson SAS. All rights reserved.
The difficulty of making a quantitative assessment of speech sequelae after head and neck cancer hinders the integration of func-tional risk in treatment protocols, while recent developments in telecommunication have made oral language essential in interper-sonal communication.
Head and neck is the fifth most frequent cancer region in France (HAS 2009), and often impacts oral communication capac-ity, impairing the vocal signal or articulation and thus quality of life .