Objective
To describe our modifications to the submental island flap (SMIF) in a case series that demonstrates improved reproducibility, shortened length of stay (LOS), and reduced utilization of hospital resources.
Study Design
This retrospective case series with chart review included adult patients who underwent resection of malignant or benign tumors resulting in lateral facial, parotid, or temporal bone defects, which were reconstructed with SMIF.
Setting
A tertiary‐care academic referral center.
Methods
Retrospective case series included all adult patients who underwent SMIF reconstruction between March 2020 and August 2021. Patient demographic and clinical data were collected. Primary outcomes were measures of hospital utilization including duration of surgery, LOS, and postoperative outcomes.
Results
Twenty‐eight patients were included with a mean age of 71.7 years. Eighty percent were male. All patients underwent parotidectomy, and the mean operative time was 347 minutes. The median LOS was 2.5 days (range 0‐16 days). Seventy‐five percent of the flaps drained into the internal jugular vein, and 25% drained into the external jugular vein. No patients required reoperation or readmission. All flaps survived.
Conclusion
SMIFs are a safe and effective option for reconstruction of lateral facial, parotid, and temporal bone defects. Compared to free flap reconstruction, SMIFs offer reduced length of surgery, decreased use of health care resources, and lower rate of reoperation. As health care resource allocation is increasingly important, the SMIF offers an excellent alternative to free flap reconstruction of lateral defects.
One of the largest factors affecting disease recurrence after surgical cancer resection is negative surgical margins. Hyperspectral imaging (HSI) is an optical imaging technique with potential to serve as a computer aided diagnostic tool for identifying cancer in gross ex-vivo specimens. We developed a tissue classifier using three distinct convolutional neural network (CNN) architectures on HSI data to investigate the ability to classify the cancer margins from ex-vivo human surgical specimens, collected from 20 patients undergoing surgical cancer resection as a preliminary validation group. A new approach for generating the HSI ground truth using a registered histological cancer margin is applied in order to create a validation dataset. The CNN-based method classifies the tumor-normal margin of squamous cell carcinoma (SCCa) versus normal oral tissue with an area under the curve (AUC) of 0.86 for inter-patient validation, performing with 81% accuracy, 84% sensitivity, and 77% specificity. Thyroid carcinoma cancer-normal margins are classified with an AUC of 0.94 for inter-patient validation, performing with 90% accuracy, 91% sensitivity, and 88% specificity. Our preliminary results on a limited patient dataset demonstrate the predictive ability of HSI-based cancer margin detection, which warrants further investigation with more patient data and additional processing techniques to optimize the proposed deep learning method.
Human papilloma virus (HPV) causes a subset of head and neck squamous cell carcinomas (HNSCC) of the oropharynx. We combined targeted DNA- and genome-wide RNA-sequencing to identify genetic variants and gene expression signatures respectively from patients with HNSCC including oropharyngeal squamous cell carcinomas (OPSCC). DNA and RNA were purified from 35- formalin fixed and paraffin embedded (FFPE) HNSCC tumor samples. Immuno-histochemical evaluation of tumors was performed to determine the expression levels of p16INK4A and classified tumor samples either p16+ or p16-. Using ClearSeq Comprehensive Cancer panel, we examined the distribution of somatic mutations. Somatic single-nucleotide variants (SNV) were called using GATK-Mutect2 (“tumor-only” mode) approach. Using RNA-seq, we identified a catalog of 1,044 and 8 genes as significantly expressed between p16+ and p16-, respectively at FDR 0.05 (5%) and 0.1 (10%). The clinicopathological characteristics of the patients including anatomical site, smoking and survival were analyzed when comparing p16+ and p16- tumors. The majority of tumors (65%) were p16+. Population sequence variant databases, including gnomAD, ExAC, COSMIC and dbSNP, were used to identify the mutational landscape of somatic sequence variants within sequenced genes. Hierarchical clustering of The Cancer Genome Atlas (TCGA) samples based on HPV-status was observed using differentially expressed genes. Using RNA-seq in parallel with targeted DNA-seq, we identified mutational and gene expression signatures characteristic of p16+ and p16- HNSCC. Our gene signatures are consistent with previously published data including TCGA and support the need to further explore the biologic relevance of these alterations in HNSCC.
A label-free, hyperspectral imaging (HSI) approach has been proposed for tumor margin assessment. HSI data, i.e., hypercube (x,y,λ), consist of a series of high-resolution images of the same field of view that are acquired at different wavelengths. Every pixel on an HSI image has an optical spectrum. In this pilot clinical study, a pipeline of a machine-learning-based quantification method for HSI data was implemented and evaluated in patient specimens. Spectral features from HSI data were used for the classification of cancer and normal tissue. Surgical tissue specimens were collected from 16 human patients who underwent head and neck (H&N) cancer surgery. HSI, autofluorescence images, and fluorescence images with 2-deoxy-2-[(7-nitro-2,1,3-benzoxadiazol-4-yl)amino]-D-glucose (2-NBDG) and proflavine were acquired from each specimen. Digitized histologic slides were examined by an H&N pathologist. The HSI and classification method were able to distinguish between cancer and normal tissue from the oral cavity with an average accuracy of 90%±8%, sensitivity of 89%±9%, and specificity of 91%±6%. For tissue specimens from the thyroid, the method achieved an average accuracy of 94%±6%, sensitivity of 94%±6%, and specificity of 95%±6%. HSI outperformed autofluorescence imaging or fluorescence imaging with vital dye (2-NBDG or proflavine). This study demonstrated the feasibility of label-free, HSI for tumor margin assessment in surgical tissue specimens of H&N cancer patients. Further development of the HSI technology is warranted for its application in image-guided surgery.
Purpose: Previous studies revealed diverging results regarding the role of survivin in squamous cell carcinoma of the head and neck (SCCHN). This study aimed to evaluate the clinical significance of survivin expression in SCCHN; the function of survivin in DNA-damage repair following ionizing radiation therapy (RT) in SCCHN cells; and the potential of honokiol to enhance RT through downregulation of survivin. Experimental Design: Expression of survivin in SCCHN patient primary tumor tissues (n ¼ 100) was analyzed and correlated with clinical parameters. SCCHN cell lines were used to evaluate the function of survivin and the effects of honokiol on survivin expression in vitro and in vivo. Results: Overexpression of survivin was significantly associated with lymph nodes' metastatic status (P ¼ 0.025), worse overall survival (OS), and disease-free survival (DFS) in patients receiving RT (n ¼ 65, OS: P ¼ 0.024, DFS: P ¼ 0.006) and in all patients with SCCHN (n ¼ 100, OS: P ¼ 0.002, DFS: P ¼ 0.003). In SCCHN cells, depletion of survivin led to increased DNA damage and cell death following RT, whereas overexpression of survivin increased clonogenic survival. RT induced nuclear accumulation of survivin and its molecular interaction with g-H2AX and DNA-PKCs. Survivin specifically bound to DNA DSB sites induced by I-SceI endonuclease. Honokiol (which downregulates survivin expression) in combination with RT significantly augmented cytotoxicity in SCCHN cells with acquired radioresistance and inhibited growth in SCCHN xenograft tumors. Conclusions: Survivin is a negative prognostic factor and is involved in DNA-damage repair induced by RT. Targeting survivin using honokiol in combination with RT May provide novel therapeutic opportunities.
Background
Pathologic extranodal extension (ENE) has traditionally guided the management of head and neck cancers. The prognostic value of radiographic ENE (rENE) in HPV-associated oropharyngeal squamous cell carcinoma (HPV+OPX) is uncertain.
Methods
HPV+OPX patient with adequate pre-treatment radiographic nodal evaluation, from a single institution were analyzed. rENE status was determined by neuroradiologists’ at time of diagnosis. Distant metastasis-free survival (DMFS), overall survival (OS), locoregional recurrence-free survival (LRFS) and were estimated using Kaplan-Meier methods. Cox proportional hazards models were fit to assess the impact of rENE on survival endpoints.
Results
168 patients with OPX+SCC diagnosed between April 2008 and December 2014 were included for analysis with median follow-up of 3.3 years. Eighty-eight percent of patients received concurrent chemoradiotherapy. rENE was not prognostic; its presence in HPV+OPX patients did not significantly impact OS, LRFS, or DMFS.
Conclusions
In patients with HPV+OPX, rENE was not significantly associated with OS, LRFS, or DMFS.
Background:
The prognostic relevance of human papillomavirus (HPV) status in non-oropharyngeal (OPX) squamous cell cancer (SCC) of the head and neck is controversial. We evaluated the impact of high-risk HPV status on overall survival (OS) in patients with non-OPX SCC using a large database approach.
Methods:
The National Cancer Data Base was queried to identify patients diagnosed from 2004–2014 with SCC of the OPX, hypopharynx (HPX), larynx, and oral cavity (OC) with known HPV status. Survival was estimated using Kaplan-Meier methods; distributions were compared with log-rank tests. Propensity score matching (PSM) and inverse probability of treatment weighing (IPTW) methods were utilized; cohorts were matched on age, sex, Charlson-Deyo score, clinical group stage, treatments received, and anatomic subsite. Propensity analyses were stratified by group stage.
Results:
24,740 patients diagnosed from 2010–2013 were analyzed; 1,085 patients with HPX, 4804 with larynx, 4,018 with OC, and 14,833 with OPX SCC. The proportions of HPV positive cases by site were: 17.7% in HPX, 11% in larynx, 10.6% in OC, and 62.9% in OPX. HPV status was prognostic in multiple un-adjusted and propensity-adjusted non-OPX populations. HPV positivity was associated with superior OS in HPX SCC with hazard ratio (HR) of 0.61 (p<0.001, IPTW), in stage III-IVB laryngeal SCC (HR 0.79, p=0.019, IPTW), and in stage III-IVB OC SCC (HR 0.78, p=0.03, IPTW).
Conclusions:
Positive high-risk HPV status is associated with longer OS in multiple non-oropharynx head and neck populations – hypopharynx, locally-advanced larynx and oral cavity. If prospectively validated, these findings have implications for risk-stratification.
Purpose: This study intends to investigate the feasibility of using hyperspectral imaging (HSI) to detect and delineate cancers in fresh, surgical specimens of patients with head and neck cancers. Experimental Design: A clinical study was conducted in order to collect and image fresh, surgical specimens from patients (N = 36) with head and neck cancers undergoing surgical resection. A set of machine-learning tools were developed to quantify hyperspectral images of the resected tissue in order to detect and delineate cancerous regions which were validated by histopathologic diagnosis. More than two million reflectance spectral signatures were obtained by HSI and analyzed using machine-learning methods. The detection results of HSI were compared with autofluorescence imaging and fluorescence imaging of two vital-dyes of the same specimens. Results: Quantitative HSI differentiated cancerous tissue from normal tissue in ex vivo surgical specimens with a sensitivity and specificity of 91% and 91%, respectively, and which was more accurate than autofluorescence imaging (P < 0.05) or fluorescence imaging of 2-NBDG (P < 0.05) and proflavine (P < 0.05). The proposed quantification tools also generated cancer probability maps with the tumor border demarcated and which could provide real-time guidance for surgeons regarding optimal tumor resection. Conclusions: This study highlights the feasibility of using quantitative HSI as a diagnostic tool to delineate the cancer boundaries in surgical specimens, and which could be translated into the clinic application with the hope of improving clinical outcomes in the future.
We explored potential associations of the PD-1/PD-L1/PD-L2 pathway with clinical characteristics, outcome, and expression of EGFR, HER2, HER3 in oropharyngeal squamous cell carcinoma (OPSCC) using an institutional database. Protein expression was assessed by IHC on tissue microarray sections (EGFR, HER2, HER3) or whole tissue sections (PD-1/PD-L1/PD-L2). Expression of EGFR, HER2, HER3, PD-L1, and PD-L2 was quantified on tumor cells. Maximum density of PD-1 positive lymphocytes was measured on a scale of 0 to 4 within the tumor mass and peritumoral stroma. Associations between biomarkers and patient outcomes were tested using descriptive and inferential statistics, logistic regression, and Cox proportional hazards models. We analyzed tissue samples from 97 OPSCC cases: median age 59 years, p16þ (71%), male (83.5%), never smokers (18%), stage 3 to 4 disease (77%). Twenty-five percent of cases were PD-L1 positive. The proportion of PD-L1þ tumors was higher in p16þ (29%) than p16 OPSCC (11%, P ¼ 0.047). There was no correlation between PD-L1, PD-L2, PD-1, EGFR, HER2, or HER3 expression. Positive PD-L1 status correlated with advanced nodal disease on multivariate analysis (OR 5.53; 95% CI, 1.06–28.77; P ¼ 0.042). Negative PD-L2 expression was associated with worse survival (HR 3.99; 95% CI, 1.37–11.58; P ¼ 0.011) in p16 OPSCC. Lower density of PD-1 positive lymphocytes in peritumoral stroma was associated with significantly increased risk of death on multivariate analysis (HR 3.17; 95% CI, 1.03–9.78; P ¼ 0.045) after controlling for prognostic factors such as stage and p16 status. PD-L1 expression on tumor cells correlates with p16 status and advanced nodal status in OPSCC. PD-1 positive lymphocytes in peritumoral stroma serve as an independent prognostic factor for overall survival.
Surgical cancer resection requires an accurate and timely diagnosis of the cancer margins in order to achieve successful patient remission. Hyperspectral imaging (HSI) has emerged as a useful, noncontact technique for acquiring spectral and optical properties of tissue. A convolutional neural network (CNN) classifier is developed to classify excised, squamous-cell carcinoma, thyroid cancer, and normal head and neck tissue samples using HSI. The CNN classification was validated by the manual annotation of a pathologist specialized in head and neck cancer. The preliminary results of 50 patients indicate the potential of HSI and deep learning for automatic tissue-labeling of surgical specimens of head and neck patients.