From Fine Needle Aspiration Research Articles

Trichorhinophalangeal syndrome 1 expression in breast and nonbreast metastases from Müllerian, lung, gastrointestinal tract, and pancreatic primary tumors by immunohistochemistry with cytology cell block specimens.

Trichorhinophalangeal syndrome 1 (TRPS1) expression in primary breast and other solid tumors has been investigated but its role as a marker in metastatic tumors is unclear. The objective of this study was to evaluate the sensitivity and specificity of TRPS1 as a breast cancer immunomarker in metastatic tumors that originated from breast, Müllerian, lung, gastrointestinal (GI), and pancreatic primary tumors with cell blocks from fine-needle aspiration (FNA) and effusion specimens. Cell blocks were immunostained with anti-TRPS1 monoclonal antibody (clone EPR16171). Histochemical scores (H scores) (proportion × intensity; range, 0-300) were assigned; H scores of ≥10 were considered positive. Overall, 160 specimens were examined, including 127 FNAs (35 breast, 25 Müllerian, 36 lung, and 31 GI and pancreatic carcinomas) and 33 effusion specimens (18 breast, 12 Müllerian, one lung, and two GI carcinomas). TRPS1 was positive in 51 of 53 (96%) metastatic breast carcinomas and in 28 of 107 (26.2%) nonbreast metastatic tumors. Metastatic breast carcinoma showed the highest mean H score of 247.35, compared to 45.36 in Müllerian, 8.4 in lung, and 5.88 in GI tumors. The sensitivity and specificity of TRPS1 for identifying a breast origin in metastatic tumors was 96.22% and 72.89%, respectively. Despite high overall sensitivity, TRPS1 showed lower specificity as a breast immunomarker because of its expression in nonbreast tumors. The mean H score in nonbreast tumors was significantly lower than in metastatic breast tumors. It is important to recognize the broad range of expression of TRPS1 in metastatic breast and nonbreast tumors to avoid an incorrect determination of a metastatic tumor's organ of origin.

Residual U-Net approach for thyroid nodule detection and classification from thyroid ultrasound images

With so many thyroid knobs (nodules) discovered by accident, it is critical to recognize as many aberrant knobs (nodules) as possible from fine-needle aspiration (FNA) biopsies or other medical procedures while excluding those that are virtually certainly benign. Thyroid ultrasonography, on the other hand, is prone to interobserver variability and subjective translations. An effective deep learning model for segmenting and categorizing thyroid nodules in this study follows the stages below: data collection from a well-known archive, The Thyroid Digital Image Database (TDID), which comprises ultrasound pictures from 298 patients, preprocessing using anisotropic diffusion filter (ADF) for removing noise and enhancing the images, segmentation using a bilateral filter for segmenting images, feature extraction using grey level occurrence matrix (GLCM), feature selection using Multi-objective Particle Swarm with Random Forest Optimization (MbPSRA) and finally classification happens were Residual U-Net will be used. Experiment evaluation states the proposed model outperforms well than other state-of-art models.

In Silico Analysis Uncovers FOXA1 as a Potential Biomarker for Predicting Neoadjuvant Chemotherapy Response in Fine-Needle Aspiration Biopsies.

Background: The preoperative identification of neoadjuvant chemotherapy (NAC) treatment responsiveness in breast cancer (BC) patients is advantageous for tailoring treatment regimens. There is a relative scarcity in the current research exploring NAC treatment responsive biomarkers using bulk sequencing data obtained from fine-needle aspiration (FNA). Materials and Methods: Limma was employed for the selection of differentially expressed genes. Additionally, WGCNA, machine learning, and Genetic Perturbation Similarity Analysis (GPSA) were utilized to identify key genes associated with NAC treatment response. ConsensusClusterPlus was employed for unsupervised clustering. Rt-qPCR and WB were conducted to assess gene expression and protein levels in clinical tissues and cell lines. The Seahorse XF96 Extracellular Flux Analyzer was utilized to evaluate Extracellular Acidification Rate (ECAR) and Oxygen Consumption Rate (OCR). The "pRRophetic" package was used for drug sensitivity prediction, while CB-Dock2 was applied for molecular docking and optimal pose presentation. Spatial transcriptomic analysis was based on the CROST database. Results: Eleven biomarkers were identified associated with NAC treatment response in BC patients, with FOXA1 identified as a pivotal hub gene among them. The expression levels of FOXA1 showed a significant positive correlation with genomic stability and a marked negative correlation with the homologous recombination deficiency (HRD) score. Downregulation of the FOXA1 gene resulted in reduced glycolysis in MCF-7 cells.Additionally, FOXA1 were found to serve as a biomarker for both NAC and PARP inhibitor treatment sensitivity in BC patients. Spatial transcriptomic analysis indicates significantly elevated infiltration of T follicular helper (T-FH) cells and mast cells surrounding tumors exhibiting high FOXA1 expression. Conclusion: In summary, our study involved the analysis of diverse sequencing datasets derived from various FNA samples to identify biomarkers sensitive to NAC, thereby offering novel insights into resources for future personalized clinical treatment strategies.

Enhancing Breast Cancer Diagnosis Through Clustering: A Study of KMeans, Agglomerative, and Gaussian Mixture Models

In the evolving landscape of medical data analysis, clustering techniques play a pivotal role, particularly in deciphering intricate patterns within datasets, such as those linked to cancer diagnostics. With the continuous expansion and increasing complexity of healthcare data, there is a growing demand for effective clustering algorithms capable of extracting significant insights. Current trends underscore the necessity of carefully selecting the most appropriate clustering method to improve both the accuracy and interpretability of analytical results. In this paper, we conduct a comprehensive comparison of three prominent clustering algorithms - KMeans, Agglomerative Clustering, and Gaussian Mixture Model (GMM) - applied to a breast cancer dataset comprising features from Fine Needle Aspirates (FNA) of breast masses. Following a thorough preprocessing and scaling of the features, we assess the performance of these clustering techniques using the Silhouette Score, Calinski-Harabasz Score, and Davies- Bouldin Score. The findings reveal that KMeans provides superior cluster separation and clarity relative to the other algorithms. This research emphasizes the critical role of algorithm selection based on specific dataset attributes and evaluation metrics, aiming to enhance the accuracy of clustering outcomes in breast cancer classification.

Molecular yield and cytomorphologic assessment of fine needle aspiration specimen supernatants.

Cytology samples are frequently relied upon for the diagnosis of advanced cancer such as lung cancer. As the recommendations for solid malignancies biomarker testing continue to expand, it becomes increasingly important to efficiently utilize limited specimens to minimize the need for additional sampling and its associated risks and costs. We performed molecular testing on fresh or CytoLyt-fixed supernatants derived from fine needle aspirates (FNAs) and compared its performance against the clinical specimen (including formalin-fixed paraffin-embedded cell blocks, residual PreservCyt and fresh samples). Supernatants were assessed for cellularity using Field-stained Cytospin (CS) preparations. There was overall almost perfect agreement (41/45 cases, K = 0.822) and substantial to almost perfect agreement in molecular testing results of clinically actionable variants between fresh (20/23 cases, Κ = 0.742) and CytoLyt-fixed (21/22 cases, Κ = 0.908) and its clinical specimen counterpart. Interestingly, CS examination of the supernatants revealed viable tumor cells. Centrifugation for 1 minute at 300 rpm is optimal for overall or tumor cellularity recovery. Delayed molecular testing after 3, 4 and 7 days at 4 degrees Celsius showed identical molecular results. We validated the use of supernatants derived from FNA cytology samples as a substrate for molecular testing using next-generation sequencing and other molecular techniques.

Diagnostic performance of the second-generation molecular tests in the assessment of indeterminate thyroid nodules: A systematic review and meta-analysis

ObjectiveThe objective of this systematic review and meta-analysis was to evaluate the diagnostic performance of the second-generation molecular tests in the diagnosis of thyroid nodules with indeterminate fine-needle aspiration biopsy results. MethodsWe searched PubMed, Google Scholar, Scopus, and Cochrane Library for studies published between January 2017 and March 2021. Inclusion criteria were indeterminate thyroid results from fine-needle aspiration (FNA) that included Bethesda categories III and IV, use of Afirma GSC, Thyroseq v3, and ThyGeNext as an index test, and conclusive histopathological results. Studies with no post-surgical diagnoses were excluded. For each included study, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were obtained. Sensitivity and specificity were pooled jointly using a bivariate binomial random-effects model. Statistical significance was indicated at p-value less than 0.05. ResultsOur search yielded 431 non-duplicate articles, of which 15 were included in the study (7 GSC, 6 Thyroseq v3, and 2 ThyGeNext). ThyGeNext studies were excluded from the meta-analysis due to the small sample size. Pooled data for GSC studies on 472 thyroid nodules showed a sensitivity of 96.6 (95% confidence interval: 89.7–98.9%), specificity of 52.9% (23.4–80.5%), PPV of 63% (51–74%), and NPV of 96% (94–98%). Pooled data for ThyroSeq studies on 530 thyroid nodules showed a sensitivity of 95.1% (91.1–97.4%), specificity of 49.6% (29.3–70.1%), PPV of 70% (55–83%), and NPV of 92% (86–97%). There was no statistically significant difference in diagnostic performances of the two tests (p-values for sensitivity = 0.89, specificity = 0.82, PPV = 0.43, NPV = 0.17). ConclusionHigh sensitivity and high NPV in GSC and Thyroseq v3 have potential to help rule out malignancy among thyroid nodules with indeterminate cytology results. There was no difference in diagnostic performances between the two molecular tests indicating that either test is appropriate to determine the malignancy of thyroid nodules. Further long-term outcome data are warranted to make a clear recommendation.

Ancillary studies on cell blocks from fine needle aspiration specimens of salivary gland lesions: A multi-institutional study.

BackgroundAncillary studies are commonly performed on cell blocks prepared from fine‐needle aspiration (FNA) specimens. There are limited studies in application of ancillary studies on cell blocks from salivary gland (SG) FNAs. This multi‐institutional study evaluates the role of ancillary studies performed on cell blocks in the diagnosis of SG lesions, and their impact on clinical management.MethodThe electronic pathology archives of three large academic institutions were searched for SG FNAs with ancillary studies performed on cell blocks. The patient demographics, FNA site, cytologic diagnosis, ancillary studies, and surgical follow‐up were recorded. If needed, the cytologic diagnoses were reclassified as per the Milan System for Reporting Salivary Gland Cytopathology (MSRSGC).Results117 SG FNA cases were identified including 3, 10, 11, 6, 23, 4, and 60 cases in MSRSGC categories I, II, III, IVa, IVb, V, VI, respectively with surgical follow‐up available ranging from 27% to 100% within each category. Ancillary studies including histochemistry, immunocytochemistry (IHC), and in situ hybridization (ISH) were beneficial in 60%–100% of cases in each category. Risk of malignancy was 100% in both the suspicious for malignancy (V) and malignant (VI) categories. Ancillary studies improved diagnosis in 60% of non‐neoplastic cases (II, 6/10), 100% of benign neoplasm cases (IVa, 6/6), and 98.3% of malignant cases (VI, 59/60).ConclusionJudicious and case‐based ancillary studies performed on SG FNA cell blocks with sufficient material can improve the diagnostic yield by further characterization of the atypical/neoplastic cells, particularly in MSRSGC categories IVa‐VI.

Evaluation of a Novel Technique of Frozen Sections of Cell Blocks and Immunocytochemistry Protocol for Fine Needle Aspirates and Fluid Cytology Specimens

Aim and objectives: Turnaround time is the main issue for formalin fixed-paraffin embedded-cell block diagnosis. The main objectives of this study were to develop fast and simple method of cell blocks preparation using frozen section technique, to develop a protocol of immunocytochemistry (ICC) on them and to evaluate its utility in clinical practice. Material and method: In this case series, we made frozen cell blocks (F-CB) from fine needle aspirates (FNA) and fluid samples using cryostat and performed ICC on them. Results were compared with histopathology diagnosis using Cohen’s Kappa agreement and Fisher Exact test. Results: Out of 25 cases, F-CB from FNA and fluid samples were made in 15 and 10 cases, respectively. ICC was performed on 20 cases. Only 40% of the cases had confirmed diagnosis on cytology smears. Addition of F-CB + ICC test could give a definitive diagnosis in 24/25 (96%) of cases. Conclusions: Newly developed method of frozen sectioning of cellblocks and ICC on them can give rapid and accurate cell block diagnosis.

Cellphone enabled point-of-care assessment of breast tumor cytology and molecular HER2 expression from fine-needle aspirates

Management of breast cancer in limited-resource settings is hindered by a lack of low-cost, logistically sustainable approaches toward molecular and cellular diagnostic pathology services that are needed to guide therapy. To address these limitations, we have developed a multimodal cellphone-based platform—the EpiView-D4—that can evaluate both cellular morphology and molecular expression of clinically relevant biomarkers directly from fine-needle aspiration (FNA) of breast tissue specimens within 1 h. The EpiView-D4 is comprised of two components: (1) an immunodiagnostic chip built upon a “non-fouling” polymer brush-coating (the “D4”) which quantifies expression of protein biomarkers directly from crude cell lysates, and (2) a custom cellphone-based optical microscope (“EpiView”) designed for imaging cytology preparations and D4 assay readout. As a proof-of-concept, we used the EpiView-D4 for assessment of human epidermal growth factor receptor-2 (HER2) expression and validated the performance using cancer cell lines, animal models, and human tissue specimens. We found that FNA cytology specimens (prepared in less than 5 min with rapid staining kits) imaged by the EpiView-D4 were adequate for assessment of lesional cellularity and tumor content. We also found our device could reliably distinguish between HER2 expression levels across multiple different cell lines and animal xenografts. In a pilot study with human tissue (n = 19), we were able to accurately categorize HER2-negative and HER2-positve tumors from FNA specimens. Taken together, the EpiView-D4 offers a promising alternative to invasive—and often unavailable—pathology services and may enable the democratization of effective breast cancer management in limited-resource settings.

Molecular testing approaches in thyroid cancer diagnosis

Thyroid cancer (TC) is the most common endocrine malignancy worldwide, with an annual incidence of around 300,000 cases. In recent decades, the incidence of TC in many countries, including Saudi Arabia, has increased significantly. Genomics has allowed multiple mutations to be examined simultaneously across multiple genes, providing a detailed genomic profile for a given tumor. It is understood from a molecular perspective that different signaling pathways may have genetic abnormalities as the primary factors in thyroid tumorigenesis. While there is still early progress in the usage and standardization of targeted next-generation sequencing (NGS) in TC, a major ongoing study to distinguish malignant from benign thyroid nodules from fine-needle aspiration (FNA) has shown promising results that can prevent unnecessary surgery, based on NGS analyses of mutations and gene fusions associated with most TC. The differential diagnosis and malignancy risk stratification of TC require multidisciplinary skills and experience of both ultrasound and the FNA and molecular analysis. The most common TC mutations are point mutations in the BRAF and the chromosome rearrangements of RET/papillary TCs. The transition mechanisms tend to be linked to specific etiological features, which are very crucial while deciding the treatment protocol. On the other hand, FNA cytology has an intrinsic drawback. The findings of infinite cytology cannot differentiate some types of TC, such as follicular adenomas, thyroid follicular carcinomas, or papillary thyroid follicular. Nevertheless, accumulating evidence indicates that molecular diagnostic approaches can overcome these limitations. In this review, we present an updated summary, which focuses primarily on molecular alterations in the tumorigenesis and biomarker investigations of TC.

Hyperspectral Raman microscopy can accurately differentiate single cells of different human thyroid nodules.

We report on the use of line-scan hyperspectral Raman microscopy in combination with multivariate statistical analyses for identifying and classifying single cells isolated from clinical samples of human thyroid nodules based on their intrinsic Raman spectral signatures. A total of 248 hyperspectral Raman images of single cells from benign thyroid (n = 127) and classic variant of papillary carcinoma (n = 121) nodules were collected. Spectral differences attributed to phenylalanine, tryptophan, proteins, lipids, and nucleic acids were identified for benign and papillary carcinoma cells. Using principal component analysis and linear discriminant analysis, cells were identified with 97% diagnostic accuracy. In addition, preliminary data of cells from follicular adenoma (n = 20), follicular carcinoma (n = 25), and follicular variant of papillary carcinoma (n = 18) nodules suggest the feasibility of further discrimination of subtypes. Our findings indicate that hyperspectral Raman microscopy can potentially be developed into an objective approach for analyzing single cells from fine needle aspiration (FNA) biopsies to enable the minimally invasive diagnosis of "indeterminate" thyroid nodules and other challenging cases.

Abstract 3355: Challenges in the implementation of molecular diagnostic testing for non-small cell lung cancer

Abstract Next generation sequencing (NGS) has been used to catalogue genetic mutations in cancer. Recent studies employing NGS have identified specific genetic mutations that reliably predict therapeutic success with targeted treatment in many forms of cancer, and particularly in non-small cell lung cancer (NSCLC). Importantly, patients with oncogenic driver mutations have better tumor control with targeted agents than with chemotherapy, while those lacking such a mutation derive more benefit from chemotherapy. To detect actionable mutations, all patients with metastatic disease must be tested. Mutation assays are generally developed using tissues derived from surgical samples. However, for many patients with metastatic NSCLC the only tissue available is from fine needle aspirates (FNAs). Given the limited number and heterogeneity of cells found in FNAs and the expanding number of clinically actionable mutations, the development and implementation of testing strategies that rapidly and accurately define driver mutations in NSCLC remains a challenge. Our project focuses on the identification of best methods (pre-analytical, analytical, and bioinformatic) to identify driver mutations in lung FNAs to standardize targeted NGS testing for NSCLC. The overarching goal of this project is to develop a strategy for Canada-wide implementation of the developed test. As a first step in this process, our team organized a stakeholder meeting to: A) Identify potential individual and/or system level challenges and barriers to implementation of standardized protocols for molecular oncology diagnostics; B) Outline guidelines and strategies to overcome identified challenges and barriers; and C) Initiate a research project to further study the barriers and facilitators of implementing Canada-wide diagnostic testing strategies for personalized cancer care. For this presentation, we will outline key challenges that impact implementation of the new test, including tumor characteristics (cellularity, heterogeneity); cost and reimbursement issues; required turn around times; bioinformatic requirements; testing strategy (technical limitations of test, panel size); technical staffing and infrastructure requirements; and barriers to implementation of the test into routine standard of care. Finally, we will present a preliminary workflow map, which builds upon the Lung Cancer Pathway Maps provided by Cancer Care Ontario (https://www.cancercareontario.ca/en/pathway-maps/lung-cancer) and addresses these barriers and explores various scenarios for implementation of new testing strategies. Citation Format: Pearl A. Campbell, Kednapa Thavorn, Bryan Lo, Ali Karimnezhad, Theodore J. Perkins, Robin Urquhart, Suzanne Kamel-Reid, Harmanjatinder Sekhon, David J. Stewart. Challenges in the implementation of molecular diagnostic testing for non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3355.

Multimodal optical imaging of renal cells

We present the results of the first quantitative multimodal confocal imaging study of methylene blue (MB)-stained cancer and normal human renal cells obtained from fine needle aspiration (FNA) biopsies. Fluorescence emission images provided morphological assessment, and fluorescence polarization (Fpol) images yielded quantitative characterization of each cell in the investigated samples. FNA specimens are obtained from discarded malignant and normal renal specimens following surgery. Prior to imaging, the cells are stained in aqueous MB solution. Our results demonstrate that all the specimens investigated are heterogeneous in terms of size and exhibited Fpol. Cancerous specimens predominantly contain cells of larger size that exhibit higher Fpol as compared to normal specimens. Imaging results correlated well with clinical assessment of the samples. Our results suggest that morphological assessment using fluorescence emission imaging and quantitative information provided by Fpol imaging may be valuable in determining the presence or absence of renal cancer cells in FNA specimens.

Hormone Receptors and Human Epidermal Growth Factor (HER2) Expression in Fine-Needle Aspirates from Metastatic Breast Carcinoma - Role in Patient Management.

Introduction:Estrogen receptors (ER), progesterone receptors (PR), and epidermal growth factor (HER2) are prognostic and predictive factors for breast carcinoma. We determined them by immunohistochemistry (IHC) on cell blocks from fine-needle aspirates (FNA) of metastatic breast carcinoma to axillary lymphnodes and compared them with that reported in the primary breast carcinoma (PBC) to document any change in their expression for future management.Materials and Methods:ER, PR, and HER2 by IHC and HER2 oncogene by fluorescent in-situ hybridization (FISH) were studied on cell blocks of FNA of axillary lymphnodes in 53 of 94 PBC cases from 2012 to 2016.Results:In 25 of 38 (65.8%) ER, PR negative PBC the metastasis on FNA was ER, PR+, whereas the 15 (28.3%) ER, PRPBC remained negative. In 10 of 11 (91%) of HER2-IHC+, PBC the metastatic tumor was HER2-IHC+. 7 of 32 (21.9%) HER2-IHC negative PBC were HER2-IHC+ in metastatic tumor. HER2-FISH was performed in 37 cases on FNA. Six of 37 were HER2 amplified/positive, whereas 9 and 19 remained equivocal and negative for HER2 copy number, and 3 were not interpretable. All the 6 HER2-FISH+ cases were positive by IHC. In our study, 34.2% of ER, PR+ cases of PBC became ER, PR– in the metastatic tumor and 21.9% of HER2-IHC negative PBC became HER2-IHC+ in the metastatic aspirate.Conclusion:ER, PR, and HER2 by IHC in cell blocks of metastatic lymphnodes are reliable. Change in receptor (34.2%) and HER2 status (21.9%) was documented, which is of clinical significance as these patients warrant a change of management.

Evaluation of Unexplained Lymphadenopathy and Suspected Lymphoma in a Lymphoma Rapid Diagnostic Clinic

Background: Lymphomas often present a diagnostic challenge, leading to delays in obtaining a definitive diagnosis. For some lymphomas, a delay in diagnosis can negatively influence outcomes of therapy and result in a shorter duration of remission. Patients are often referred for evaluation with lymphoma diagnosis based on cytology from fine needle aspiration (FNA), whereas excisional or core lymph node biopsy is required for definitive diagnosis. We established a nurse practitioner-led Lymphoma Rapid Diagnostic Clinic (LRDC) with the goal of reducing wait times to diagnosis and initiation of treatment. Program development included surgical and interventional radiology engagement, and dedicated operating room time for excisional lymph node biopsies. We conducted a retrospective chart review to describe the initial 30-month experience of the LRDC. Results were compared to time periods before implementation of the clinic to determine program impact, and identify areas for quality improvement.Methods: All patients referred to LRDC at Princess Margaret Cancer Centre (PM), part of University Health Network (UHN), with suspicion of lymphoma from June 1, 2015 to Nov 30, 2017 were evaluated. Patients were excluded if they arrived in clinic with confirmed diagnosis of lymphoma or declined further LRDC evaluation. Patient symptoms and relevant laboratory/imaging findings were collected to identify patterns of presentation and predictive factors for benign diagnoses. Time from initial consultation to diagnosis and treatment were compared to patients diagnosed with lymphoma by surgical, medical, or oncology services at UHN in 2008 and 2012. Statistical significance was investigated using Fisher Exact test for categorical variables, and non-parametric Wilcoxon rank sum test for continuous data. Statistical significance level was chosen at a 2-sided p-value of 0.05 or less.Results: Of 129 patients referred to LRDC with suspected lymphoma, 126 were included in the analysis. Median age was 55yrs (range 18- 95yrs), and 67 patients (53%) were female. Thirty-nine patients had non-diagnostic FNA and/or core biopsies at initial assessment. Twenty-five had a prior cancer diagnosis, 30 presented with B symptoms and 57 had palpable enlarged lymph nodes (Table 1). To obtain a definitive diagnosis, 93 patients had biopsies (46 image-guided cores, 37 excisional, 6 FNA, 4 bone marrow); 13 patients received a diagnosis after pathology review, 4 via peripheral blood flow cytometry, and 16 following other clinical or serologic/imaging investigations.Following evaluation, 66 patients (52%) had confirmation of a diagnosis of lymphoma (34 indolent, 18 aggressive, 14 Hodgkin lymphoma (HL)), 2 had acute leukemia, 14 had metastatic cancer, and 44 had non-malignant diagnoses (Table 2). Median time from initial assessment to lymphoma diagnosis was 16 days (interquartile range 9-24 days) for the patients assessed in LRDC and 28 days (interquartile range 19-48 days) for historical controls (p <0.001). Median time from initial LRDC assessment to treatment for aggressive lymphomas and HL was 29 days (interquartile range 21-43 days) compared to 48 days (interquartile range 28-78 days) for historical controls (p= <0.001). The total number of biopsies obtained before diagnosis was significantly fewer for patients assessed in LRDC compared to historical controls (p<0.001, Fisher's exact test).By univariable analysis, lymph node size >3.4 cm and presence of mediastinal or abdominal adenopathy increased the likelihood of a diagnosis of malignancy, while younger age, being a non-smoker, and prior rheumatologic condition were associated with a non-malignant diagnosis. In multivariable analysis, lymph node size, age and prior rheumatologic diagnosis remained significant. Presence of B symptoms was not predictive.Conclusion: Establishing the nurse practitioner-led LRDC was effective in shortening time to diagnosis and treatment, and reduced the number of biopsies required for definitive diagnosis of lymphoma. Younger age, smaller lymph node size and prior rheumatologic disorder reduced the likelihood of a cancer diagnosis in our patient population. DisclosuresKuruvilla:Princess Margaret Cancer Foundation: Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy; Lundbeck: Honoraria; Seattle Genetics: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Karyopharm: Honoraria; Roche: Consultancy, Honoraria, Research Funding; Leukemia and Lymphoma Society Canada: Research Funding; BMS: Consultancy, Honoraria; Celgene: Honoraria; Merck: Consultancy, Honoraria; Amgen: Honoraria.

Modified Plasma-Thrombin Method of Cell Block Preparation for Fine-Needle Aspiration Biopsies in Resource-Limited Settings.

The plasma-thrombin method is commonly used to make cell blocks from fine-needle aspiration (FNA) samples but requires centrifugation. We describe a modification to this method that does not require centrifugation for use in resource-limited settings. Pooled fresh plasma is aliquoted into 2-mL Eppendorf tubes and the FNA sample directly rinsed into the plasma. Two drops of reconstituted thrombin are added and gently mixed. A cell clot is transferred to a tissue bag, fixed in formalin, and processed. This method was applied to FNA samples from 44 patients presenting to the Mbarara University of Science and Technology FNA clinic. The cell blocks were less cellular than the smears but contained adequate material to confirm morphologic impression or perform immunocytochemistry in 36 of 44 cases (82% adequacy rate). The modified plasma-thrombin method is a reliable cell block preparation method that can be easily applied in resource-limited settings.

Risk factors for hypothyroidism in euthyroid thyroid nodule patients with lymphocytic thyroiditis on fine needle aspiration cytology.

Background/AimsLymphocytic thyroiditis as cytology diagnosis from fine needle aspiration (FNA) is frequently detected in patients with thyroid nodules. However, the clinical outcome for upcoming hypothyroid events has been rarely clarified in euthyroid patients.MethodsWe retrospectively reviewed the data of patient who had lymphocytic thyroitidis on FNA cytology of thyroid nodule from January 2005 to December 2010 at a tertiary referral hospital. In total, 109 patients with follow-up thyroid function tests (TFT) were enrolled. Final outcomes included overt and subclinical hypothyroidism with thyroid stimulating hormone (TSH) levels ≥ 10 mIU/L. Potential parameters predicting clinical hypothyroidism were analyzed by multivariate analysis.ResultsOver the mean follow-up duration of 51.6 months, 14 out of 109 patients (12.8%) developed clinical hypothyroidism that required thyroid hormone replacement. The median onset time to hypothyroidism was 16 months (range, 3 to 88) and ≥ 60% of patients experienced clinical hypothyroidism within 1 year. By multivariate analysis, background thyroiditis (relative risk [RR], 9.78; p = 0.004), thyroid peroxidase antibody positivity (RR, 9.90; p = 0.003), nodule size (RR, 1.24; p < 0.001), and initial TSH (RR, 1.47; p = 0.009) were the independent risk factors for predicting hypothyroidism in euthyroid patients.ConclusionsHypothyroidism frequently occurs during the follow-up in euthyroid patients with thyroid nodules which show lymphocytic thyroiditis on FNA cytology. Close surveillance and regular TFT are needed in high-risk patients for upcoming clinical hypothyroidism.

Investigation of correlation between cytological and histological findings in suspected carcinoma of thyroid

ABSTRACT Introduction: The thyroid cytopathologic classification based on The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) standardized results derived from fine-needle aspiration (FNA). It has facilitated communication among clinicians, seems to reduce the number of unnecessary thyroidectomies and also improves the quality of malignancy detection. Objective: To evaluate the correlation between cytopathological samples classified according to TBSRTC and their histological finding after specimen examination following surgical procedure. Methods: Cytopathological samples classified according to TBSRTC were correlated with the respective anatomopathological finding after thyroidectomy. There were retrospectively included all cases of thyroidectomy with previous FNA in the same lateral position of the organ that occurred within two years. Results: The 200 cases of thyroid FNA analyzed were distributed in 25 nondiagnostic or unsatisfactory cases (I; 12.5%), 45 benign cases (II; 22.5%), 48 atypia or follicular lesions of undetermined significance [(AUS/FLUS), III; 24%], 23 suspected cases for follicular neoplasia or follicular neoplasias [(SFN/FN), IV; 11.5%], 40 cases suspected for malignancy (V; 20%), and 19 malignant cases (VI; 9.5%). The malignancy rates observed for categories I to VI were 12%, 13.3%, 29.2%, 43.5%, 85%, and 100%, respectively. Conclusion: The prevalence of Bethesda II category was lower than predicted by TBSRTC (60%-70%), as well as Bethesda III was higher than recommended (7%). Nevertheless, the corresponding malignancy rates were within the expected ranges.

MTE 02.02 Appropriate and Optimized Handling of Biopsy or Cytology Specimens

MTE 02.02 Appropriate and Optimized Handling of Biopsy or Cytology Specimens

Thyroid Nodule Classification in Ultrasound Images by Fine-Tuning Deep Convolutional Neural Network

With many thyroid nodules being incidentally detected, it is important to identify as many malignant nodules as possible while excluding those that are highly likely to be benign from fine needle aspiration (FNA) biopsies or surgeries. This paper presents a computer-aided diagnosis (CAD) system for classifying thyroid nodules in ultrasound images. We use deep learning approach to extract features from thyroid ultrasound images. Ultrasound images are pre-processed to calibrate their scale and remove the artifacts. A pre-trained GoogLeNet model is then fine-tuned using the pre-processed image samples which leads to superior feature extraction. The extracted features of the thyroid ultrasound images are sent to a Cost-sensitive Random Forest classifier to classify the images into “malignant” and “benign” cases. The experimental results show the proposed fine-tuned GoogLeNet model achieves excellent classification performance, attaining 98.29% classification accuracy, 99.10% sensitivity and 93.90% specificity for the images in an open access database (Pedraza et al. 16), while 96.34% classification accuracy, 86% sensitivity and 99% specificity for the images in our local health region database.