Intra-operative point-of-procedure delineation of oral cancer margins using optical coherence tomography.

ObjectivesSurgical margin status is a significant determinant of treatment outcome in oral cancer. Negative surgical margins can decrease the loco-regional recurrence by five-fold. The current standard of care of intraoperative clinical examination supplemented by histological frozen section, can result in a risk of positive margins from 5 to 17 percent. In this study, we attempted to assess the utility of intraoperative optical coherence tomography (OCT) imaging with automated diagnostic algorithm to improve on the current method of clinical evaluation of surgical margin in oral cancer.Materials and methodsWe have used a modified handheld OCT device with automated algorithm based diagnostic platform for imaging. Intraoperatively, images of 125 sites were captured from multiple zones around the tumor of oral cancer patients (n = 14) and compared with the clinical and pathologic diagnosis.ResultsOCT showed sensitivity and specificity of 100%, equivalent to histological diagnosis (kappa, ĸ = 0.922), in detection of malignancy within tumor and tumor margin areas. In comparison, for dysplastic lesions, OCT-based detection showed a sensitivity of 92.5% and specificity of 68.8% and a moderate concordance with histopathology diagnosis (ĸ = 0.59). Additionally, the OCT scores could significantly differentiate squamous cell carcinoma (SCC) from dysplastic lesions (mild/moderate/severe; p ≤ 0.005) as well as the latter from the non-dysplastic lesions (p ≤ 0.05).ConclusionThe current challenges associated with clinical examination-based margin assessment could be improved with intra-operative OCT imaging. OCT is capable of identifying microscopic tumor at the surgical margins and demonstrated the feasibility of mapping of field cancerization around the tumor

Estimation of thyroglobulin in lymph node aspirates: Pilot experience from a tertiary referral cancer center

Background: Assessment of cervical lymph node involvement in patients with thyroid cancer either during preoperative surgical mapping or detection of recurrences during follow-up is a crucial step in the management of differentiated thyroid cancers (DTCs). In most patients, fine needle aspiration cytology (FNAC) confirms the presence of metastasis in lymph node. However, in cases of paucicellular lymph node aspirate or discordant sonogram and cytology results, thyroglobulin (Tg) measurement in the lymph node aspirate (FNA-Tg) is useful and a value >1 ng/ml is considered consistent with metastatic disease. Context: The addition of FNAC to the US improves the specificity, but 5–10% are nondiagnostic and 6–8% rate of false-negative results. Several studies have reported that the detection of Tg in FNA-needle washes improves the evaluation of suspicious lymph nodes in patients with DTC.Data from Indian centers on FNA-Tg are limited. Aims: We piloted the utility of FNA-Tg in patients with sonographically suspicious cervical lymph node enlargement in the setting of suspicious thyroid nodule or in the follow-up of thyroid cancer. Settings and Design: Prospective data collection. Results: We measured Tg in 13 lymph node aspirates (12 patients, 10 females) among whom 4 patients had a total thyroidectomy and 1 had a hemithyroidectomy. Eight of the 13 lymph node aspirates had FNA-Tg values >150 ng/ml, all of them had unequivocal malignant cytology and four among them had proven metastatic DTC on surgical pathology. The median FNA-Tg of the patients with malignant cytology was 7550 ng/ml with a range of 162–30,000 ng/ml. Among the remaining 5 lymph node aspirate, 2 lymph nodes showed cytological features suggestive of reactive lymphadenitis (FNA-Tg <0.2 ng/ml) and were not operated, 1 had a high-grade malignancy consistent with anaplastic thyroid cancer (FNA-Tg <0.2 ng/ml), and 2 had nondiagnostic cytology (one had non-caseating granuloma on surgical pathology [FNA-Tg 1.3 ng/ml] and in the other patient [FNA-Tg <0.2 ng/ml] surgical intervention was deferred). Conclusions: FNA-Tg was concordant with positive cytology in all patients with DTC and may serve as a useful tool in patients with negative and nondiagnostic cytology to guide surgical management

Improving bethesda reporting in thyroid cytology: A team effort goes a long way and still miles to go…

Context: Fine-needle aspiration cytology is the first step in evaluation of thyroid nodules. Although the Bethesda classification for reporting thyroid cytology has been purported that this uniformity in reporting cytology thereby facilitating clinical decision-making, there are also studies indicating that the reporting percentage and the rates of malignancy in each category vary considerably from center to center making the clinical decision more difficult. Aim and Materials and Methods: We looked at our retrospective cytology and histopathology data of thyroid nodules operated between 2012 and 2014 and then prospectively collected data during 2015–2016. In the prospective arm, for every thyroid nodule that was sampled, there was a discussion between the endocrinologist and the cytopathologist on the risk of thyroid cancer (based on the patient's history, examination findings, sonographic pattern, and the cytological appearance). Results: We noted that there was considerable improvement in reporting standards with the rates of nondiagnostic cytology dropping from 11% to 5%, an increased reporting of Bethesda Category 2 and 6 which are the definitive strata of benign and malignant nodules (38% to 41% in Category 2 and 7% to 11% in Category 6) with a high specificity (100%). There was a decline in numbers of Category 4 and 5 (13% to 9% in Category 4 and 12% to 3% in Category 5). The reporting prevalence of Category 3 increased from 19% to 27%. Conclusions: We conclude that a team approach between the clinician who performs the ultrasound and the reporting cytopathologist improves Bethesda reporting, its predictive value, and thus potentially avoiding unnecessary thyroidectomies in benign thyroid nodules and hemithyroidectomies in thyroid cancers

Intra-operative point-of-procedure delineation of oral cancer margins using optical coherence tomography.

ObjectivesSurgical margin status is a significant determinant of treatment outcome in oral cancer. Negative surgical margins can decrease the loco-regional recurrence by five-fold. The current standard of care of intraoperative clinical examination supplemented by histological frozen section, can result in a risk of positive margins from 5 to 17 percent. In this study, we attempted to assess the utility of intraoperative optical coherence tomography (OCT) imaging with automated diagnostic algorithm to improve on the current method of clinical evaluation of surgical margin in oral cancer.Materials and methodsWe have used a modified handheld OCT device with automated algorithm based diagnostic platform for imaging. Intraoperatively, images of 125 sites were captured from multiple zones around the tumor of oral cancer patients (n = 14) and compared with the clinical and pathologic diagnosis.ResultsOCT showed sensitivity and specificity of 100%, equivalent to histological diagnosis (kappa, ĸ = 0.922), in detection of malignancy within tumor and tumor margin areas. In comparison, for dysplastic lesions, OCT-based detection showed a sensitivity of 92.5% and specificity of 68.8% and a moderate concordance with histopathology diagnosis (ĸ = 0.59). Additionally, the OCT scores could significantly differentiate squamous cell carcinoma (SCC) from dysplastic lesions (mild/moderate/severe; p ≤ 0.005) as well as the latter from the non-dysplastic lesions (p ≤ 0.05).ConclusionThe current challenges associated with clinical examination-based margin assessment could be improved with intra-operative OCT imaging. OCT is capable of identifying microscopic tumor at the surgical margins and demonstrated the feasibility of mapping of field cancerization around the tumor

Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer.

The head and neck squamous cell carcinoma (HNSCC) transcriptome has been profiled extensively, nevertheless, identifying biomarkers that are clinically relevant and thereby with translational benefit, has been a major challenge. The objective of this study was to use a meta-analysis based approach to catalog candidate biomarkers with high potential for clinical application in HNSCC. Data from publically available microarray series (N = 20) profiled using Agilent (4X44K G4112F) and Affymetrix (HGU133A, U133A_2, U133Plus 2) platforms was downloaded and analyzed in a platform/chip-specific manner (GeneSpring software v12.5, Agilent, USA). Principal Component Analysis (PCA) and clustering analysis was carried out iteratively for segregating outliers; 140 normal and 277 tumor samples from 15 series were included in the final analysis. The analyses identified 181 differentially expressed, concordant and statistically significant genes; STRING analysis revealed interactions between 122 of them, with two major gene clusters connected by multiple nodes (MYC, FOS and HSPA4). Validation in the HNSCC-specific database (N = 528) in The Cancer Genome Atlas (TCGA) identified a panel (ECT2, ANO1, TP63, FADD, EXT1, NCBP2) that was altered in 30% of the samples. Validation in treatment naïve (Group I; N = 12) and post treatment (Group II; N = 12) patients identified 8 genes significantly associated with the disease (Area under curve>0.6). Correlation with recurrence/re-recurrence showed ANO1 had highest efficacy (sensitivity: 0.8, specificity: 0.6) to predict failure in Group I. UBE2V2, PLAC8, FADD and TTK showed high sensitivity (1.00) in Group I while UBE2V2 and CRYM were highly sensitive (>0.8) in predicting re-recurrence in Group II. Further, TCGA analysis showed that ANO1 and FADD, located at 11q13, were co-expressed at transcript level and significantly associated with overall and disease-free survival (p<0.05). The meta-analysis approach adopted in this study has identified candidate markers correlated with disease outcome in HNSCC; further validation in a larger cohort of patients will establish their clinical relevance

A smart tele-cytology point-of-care platform for oral cancer screening.

Early detection of oral cancer necessitates a minimally invasive, tissue-specific diagnostic tool that facilitates screening/surveillance. Brush biopsy, though minimally invasive, demands skilled cyto-pathologist expertise. In this study, we explored the clinical utility/efficacy of a tele-cytology system in combination with Artificial Neural Network (ANN) based risk-stratification model for early detection of oral potentially malignant (OPML)/malignant lesion. A portable, automated tablet-based tele-cytology platform capable of digitization of cytology slides was evaluated for its efficacy in the detection of OPML/malignant lesions (n = 82) in comparison with conventional cytology and histology. Then, an image pre-processing algorithm was established to segregate cells, ANN was trained with images (n = 11,981) and a risk-stratification model developed. The specificity, sensitivity and accuracy of platform/ stratification model were computed, and agreement was examined using Kappa statistics. The tele-cytology platform, Cellscope, showed an overall accuracy of 84-86% with no difference between tele-cytology and conventional cytology in detection of oral lesions (kappa, 0.67-0.72). However, OPML could be detected with low sensitivity (18%) in accordance with the limitations of conventional cytology. The integration of image processing and development of an ANN-based risk stratification model improved the detection sensitivity of malignant lesions (93%) and high grade OPML (73%), thereby increasing the overall accuracy by 30%. Tele-cytology integrated with the risk stratification model, a novel strategy established in this study, can be an invaluable Point-of-Care (PoC) tool for early detection/screening in oral cancer. This study hence establishes the applicability of tele-cytology for accurate, remote diagnosis and use of automated ANN-based analysis in improving its efficacy

Identification of Protein-Protein Interaction.

<p>Analysis for protein-protein interaction by STRING network identified two major interconnecting clusters with high degree interactions between the genes (N = 122). These 2 major clusters were interconnected by the nodes MYC, FN1, FOS and HSPA4. The number of lines represent the levels of evidence as indicated in the color legend. The different sizes of the node are based on the extent of protein structural information available for each gene while the colors of the node are a visual aid used for better representation. The markers from this analysis selected for patient validation are encircled.</p