Oral mucosa - an examination map for confocal laser endomicroscopy within the oral cavity: an experimental clinical study

OBJECTIVES

Confocal laser endomicroscopy (CLE) is an optical method that enables microscopic visualization of oral mucosa. Previous studies have shown that it is possible to differentiate between physiological and malignant oral mucosa. However, differences in mucosal architecture were not taken into account. The objective was to map the different oral mucosal morphologies and to establish a "CLE map" of physiological mucosa as baseline for further application of this powerful technology.

MATERIALS AND METHODS

The CLE database consisted of 27 patients. The following spots were examined: (1) upper lip (intraoral) (2) alveolar ridge (3) lateral tongue (4) floor of the mouth (5) hard palate (6) intercalary line. All sequences were examined by two CLE experts for morphological differences and video quality.

RESULTS

Analysis revealed clear differences in image quality and possibility of depicting tissue morphologies between the various localizations of oral mucosa: imaging of the alveolar ridge and hard palate showed visually most discriminative tissue morphology. Labial mucosa was also visualized well using CLE. Here, typical morphological features such as uniform cells with regular intercellular gaps and vessels could be clearly depicted. Image generation and evaluation was particularly difficult in the area of the buccal mucosa, the lateral tongue and the floor of the mouth.

CONCLUSION

A physiological "CLE map" for the entire oral cavity could be created for the first time.

CLINICAL RELEVANCE

This will make it possible to take into account the existing physiological morphological features when differentiating between normal mucosa and oral squamous cell carcinoma in future work.

CT predictors of sub-centimeter occult lymph node metastases in oral cavity squamous cell carcinoma: A case-control study

BACKGROUND

For patients with oral cavity squamous cell carcinoma (OCSCC) without evidence of nodal metastasis (cN0) on pre-operative evaluation, there are no clear guidelines who should undergo elective neck dissection (END) versus clinical surveillance.

OBJECTIVE

To identify CT imaging characteristics of sub-centimeter lymph nodes that would help predict the likelihood of nodal metastases on pathology.

METHODS

Retrospective review of cN0 OCSCC patients at a tertiary academic medical center was performed. Inclusion criteria included elective neck dissection, pre-operative CT imaging and presence of metastatic disease within lymph nodes. Control group consisted of patients without nodal metastases on pathology. CT features that were evaluated included asymmetric size, disrupted fatty hilum, asymmetric number, presence of cortical nodule, cortical nodule size, and round/oval shape. We evaluated the associations between CT LN features and the presence of metastases using multi-level mixed-effects logistic regression models. Model evaluation was performed using 5-fold cross-validation. The positive predictive value (PPV) and negative predictive value (NPV) were calculated.

RESULTS

26 patients in each study and control groups were included. Three-level mixed-effects logistic regression models indicated round/oval shape (OR = 1.39, p = .01), asymmetric number (OR = 7.20, p = .005), and disrupted fatty hilum (OR = 3.31, p = .04) to be independently predictive in a 3-variable model with sensitivity = 38.0%, specificity = 92.0%, and PPV = 93.8%.

CONCLUSIONS

In cN0 OCSCC patients undergoing END, round/oval shape, asymmetric number, and disrupted fatty hilum of lymph nodes on pre-operative CT imaging are novel and highly predictive of occult nodal disease.

Application of gel based on medical image inspection in total closure resection of oral cancer patients

Oral cancer is a common malignant tumor, and total closed resection is a common treatment. However, it has always been a challenge to determine the exact extent of excision during surgery. The application of medical image examination in surgery can provide important reference information, but the current methods still have some limitations. This study explored the application of gels based on medical image examination in the total closed resection of oral cancer patients to improve the accuracy of resection range and surgical treatment effect. The study collected medical image data of patients with oral cancer for image enhancement and determination of resection boundaries. By comparing the results of the experimental group and the control group, the application effect of gel in operation was evaluated. Through the application of medical image inspection technology, the determination of surgical resection boundary is more accurate, and the positive incisal margin of patients is effectively avoided. Gel technology improves the success rate and efficacy of surgery, and this method helps to improve the accuracy of surgery and the certainty of the scope of resection, which is of great significance for improving the surgical treatment effect and the survival rate of patients.

Malignant Lesions of the Oral Region

This article focuses on the radiographic presentations of various malignant conditions that affect the oral region and delineates the role of CT, MR imaging, and PET in oral cancer imaging.

Performance of cone-beam computed tomography (CBCT) in comparison to conventional computed tomography (CT) and magnetic resonance imaging (MRI) for the detection of bone invasion in oral squamous cell cancer (OSCC): a prospective study

BACKGROUND

Oral squamous carcinoma (OSCC) is often diagnosed at late stages and bone erosion or invasion of the jawbone is frequently present. Computed tomography (CT) and magnetic resonance imaging (MRI) are known to have high diagnostic sensitivities, specificities, and accuracies in detecting these bone affections in patients suffering from OSCC. To date, the existing data regarding the impact of cone-beam computed tomography (CBCT) have been weak. Therefore, this study aimed to investigate whether CBCT is a suitable tool to detect bone erosion or invasion in patients with OSCC.

METHODS

We investigated in a prospective trial the impact of CBCT in the diagnosis of bone erosion or invasion in patients with OSCC who underwent surgery. Every participant received a CBCT, CT, and MRI scan during staging. Imaging modalities were evaluated by two specialists in oral and maxillofacial surgery (CBCT) and two specialists in radiology (CT and MRI) in a blinded way, to determine whether a bone affection was present or not. Reporting used the following 3-point system: no bony destruction ("0"), cortical bone erosion ("1"), or medullary bone invasion ("2"). Histological examination or a follow-up served to calculate the sensitivities, specificities, and accuracies of the imaging modalities.

RESULTS

Our results revealed high diagnostic sensitivities (95.6%, 84.4%, and 88.9%), specificities (87.0%, 91.7%, and 91.7%), and accuracies (89.5%, 89.5%, and 90.8%) for CBCT, CT, and MRI. A pairwise comparison found no statistical difference between CBCT, CT, and MRI.

CONCLUSION

Our data support the routine use of CBCT in the diagnosis of bone erosion and invasion in patients with OSCC as diagnostic accuracy is equal to CT and MRI, the procedure is cost-effective, and it can be performed during initial contact with the patient.

The impact of COVID-19 on oral squamous cell carcinoma's diagnostic stage-A retrospective study

OBJECTIVE

The COVID-19 pandemic has had an impact on patients' access to primary care services. A timely diagnosis of oral squamosa cell carcinoma is paramount. This study aims to quantify the pandemic's effect on tumor volume at the time of initial diagnosis.

MATERIALS AND METHODS

In a retrospective study, all primarily diagnosed cancer patients between March 2018 and March 2022 were compiled; the TNM stage and the tumor volume were evaluated. Tumor volumes were calculated using pathology or radiology reports.

RESULTS

In total, 162 newly diagnosed tumor cases were included in this study. Of these, 76 (46.9%) cases were allocated in the "pre-COVID-19" group and 86 (53.1%) in the "COVID-19" group. Patients diagnosed during the "COVID-19" period showed a significantly advanced T stage (p < 0.001) and larger mean tumor volumes (53.16 ± 73.55 cm3 vs. 39.89 ± 102.42 cm3 ; p = 0.002) when compared to the control group.

CONCLUSION

Tumor volume and T stage were significantly advanced in the "COVID-19" group when compared to prepandemic data. We hypothesize that the postponement of routine dental check-ups may explain this finding. Hence, dentists and primary care providers are encouraged to place particular emphasis on screening during routine check-ups.

Fluorescent Guided Sentinel Lymph Mapping of the Oral Cavity with Fluorescent-Labeled Tilmanocept

OBJECTIVE

With the shift toward utilization of sentinel lymph node biopsy (SLNB) in oral cavity cancer, improved techniques for intraoperative sentinel node identification are needed. This study investigates the feasibility of fluorescently labeled tilmanoscept in SLNB in an oral cancer rabbit model.

METHODS

An animal study was designed using 21 healthy male New Zealand rabbits. Gallium-68-labeled tilmanocept labeled with IRDye800CW was injected submucosally into the buccal mucosa (n = 6) or lateral tongue (n = 7) followed by PET imaging. One hour after injection, SLNB was performed using fluorescence imaging followed by a bilateral neck dissection and sampling of non-nodal surrounding tissue. All tissues were measured for radioactivity and fluorescence. In addition, eight rabbits were injected with delayed SLNB performed 48 h after injection.

RESULTS

Buccal injections all had ipsilateral SLN drainage and tongue injections exhibited 18.2% contralateral drainage. An average of 1.9 ± 1.0 SLN (range 1-5) were identified. In addition, an average of 16.9 ± 3.3 non-sentinel lymph nodes were removed per animal. SLNs had an average of 0.69 ± 0.60 percent-of-injected dose (%ID) compared with non-sentinel nodes with 0.012 ± 0.025 %ID and surrounding tissue with 0.0067 ± 0.015 %ID. There was 98.0% agreement between sentinel lymph nodes identified using fluorescence compared to radioactivity with Cohen's kappa coefficient of 0.879. In 48-h delayed SLNB, results were consistent with 97.8% agreement with radioactivity and Cohen's Kappa coefficient of 0.884. Fluorescence identified additional lymph nodes that were not identified by radioactivity, and with one false negative.

CONCLUSION

Fluorescent-labeled Tc-99 m-tilmanocept represents a highly accurate adjunct to enhance SLNB for oral cavity cancer.

LEVEL OF EVIDENCE

N/A Laryngoscope, 134:1299-1307, 2024.

FD-Net: Feature Distillation Network for Oral Squamous Cell Carcinoma Lymph Node Segmentation in Hyperspectral Imagery

Oral squamous cell carcinoma (OSCC) has the characteristics of early regional lymph node metastasis. OSCC patients often have poor prognoses and low survival rates due to cervical lymph metastases. Therefore, it is necessary to rely on a reasonable screening method to quickly judge the cervical lymph metastastic condition of OSCC patients and develop appropriate treatment plans. In this study, the widely used pathological sections with hematoxylin-eosin (H&E) staining are taken as the target, and combined with the advantages of hyperspectral imaging technology, a novel diagnostic method for identifying OSCC lymph node metastases is proposed. The method consists of a learning stage and a decision-making stage, focusing on cancer and non-cancer nuclei, gradually completing the lesions' segmentation from coarse to fine, and achieving high accuracy. In the learning stage, the proposed feature distillation-Net (FD-Net) network is developed to segment the cancerous and non-cancerous nuclei. In the decision-making stage, the segmentation results are post-processed, and the lesions are effectively distinguished based on the prior. Experimental results demonstrate that the proposed FD-Net is very competitive in the OSCC hyperspectral medical image segmentation task. The proposed FD-Net method performs best on the seven segmentation evaluation indicators: MIoU, OA, AA, SE, CSI, GDR, and DICE. Among these seven evaluation indicators, the proposed FD-Net method is 1.75%, 1.27%, 0.35%, 1.9%, 0.88%, 4.45%, and 1.98% higher than the DeepLab V3 method, which ranks second in performance, respectively. In addition, the proposed diagnosis method of OSCC lymph node metastasis can effectively assist pathologists in disease screening and reduce the workload of pathologists.

Serial assessment and long-term radiographic evaluation of the maxillary sinus after inferior maxillectomy and soft tissue free flap reconstruction in patients with oral cancer

PURPOSE

This study evaluates serial radiographic changes in the maxillary sinus of patients with oral cancer after an inferior maxillectomy and a soft tissue free flap reconstruction.

METHODS

Fifty-six patients were evaluated between Oct 2005 and Mar 2017 from an institutional database. Preoperative and surveillance imaging was reviewed at set time-points. Maxillary sinus scores were allotted based on a modification of the Lund-MacKay staging system. Patients were evaluated for change in sinus score. A univariate (UV) and multivariate (MV) analysis was performed.

RESULTS

There were 53.5% T3/T4 category tumors and 68% received adjuvant treatment. Median follow-up was 24.4 months. Preoperative mean sinus score was 0.27 ± 0.44 and postoperative mean sinus score at 24 months was 1.2 ± 1.3 (p = <0.001). On UV analysis advanced T-stage at 12 months (OR 6.7, 95% CI 1.2-50.3, p = 0.01) and 24 months (OR 5.2, 95% CI 1.03-36.8, p = 0.04) was associated with significantly higher sinus score. On MV analysis, advanced T-stage continued to be associated with increased odds for higher sinus score (OR 4.9, 95% CI 1.1-26.8, p = 0.039).

CONCLUSION

A mild increase in postoperative sinus score is seen in this cohort of patients. Advanced T-stage is associated with increased odds for higher sinus scores.

Demographic and imaging features of oral squamous cell cancer in Serbia: a retrospective cross-sectional study

BACKGROUND

The mortality of oral squamous cell cancer (OSCC) in Serbia increased in the last decade. Recent studies on the Serbian population focused mainly on the epidemiological aspect of OSCC. This study aimed to investigate the demographic and imaging features of OSCC in the Serbian population at the time of diagnosis.

METHODS

We retrospectively analyzed computed tomography (CT) images of 276 patients with OSCC diagnosed between 2017 and 2022. Age, gender, tumor site, tumor volume (CT-TV, in cm3), depth of invasion (CT-DOI, in mm), and bone invasion (CT-BI, in %) were evaluated. TNM status and tumor stage were also analyzed. All parameters were analyzed with appropriate statistical tests.

RESULTS

The mean age was 62.32 ± 11.39 and 63.25 ± 11.71 for males and females, respectively. Male to female ratio was 1.63:1. The tongue (36.2%), mouth floor (21.0%), and alveolar ridge (19.9%) were the most frequent sites of OSCC. There was a significant gender-related difference in OSCC distribution between oral cavity subsites (Z=-4.225; p < 0.001). Mean values of CT-TV in males (13.8 ± 21.5) and females (5.4 ± 6.8) were significantly different (t = 4.620; p < 0.001). CT-DOI also differed significantly (t = 4.621; p < 0.001) between males (14.4 ± 7.4) and females (10.7 ± 4.4). CT-BI was detected in 30.1%, the most common in the alveolar ridge OSCC. T2 tumor status (31.4%) and stage IVA (28.3%) were the most dominant at the time of diagnosis. Metastatic lymph nodes were detected in 41.1%.

CONCLUSION

Our findings revealed significant gender-related differences in OSCC imaging features. The predominance of moderate and advanced tumor stages indicates a long time interval to the OSCC diagnosis.

Automated evaluation of masseter muscle volume: deep learning prognostic approach in oral cancer

BACKGROUND

Sarcopenia has been identified as a potential negative prognostic factor in cancer patients. In this study, our objective was to investigate the relationship between the assessment method for sarcopenia using the masseter muscle volume measured on computed tomography (CT) images and the life expectancy of patients with oral cancer. We also developed a learning model using deep learning to automatically extract the masseter muscle volume and investigated its association with the life expectancy of oral cancer patients.

METHODS

To develop the learning model for masseter muscle volume, we used manually extracted data from CT images of 277 patients. We established the association between manually extracted masseter muscle volume and the life expectancy of oral cancer patients. Additionally, we compared the correlation between the groups of manual and automatic extraction in the masseter muscle volume learning model.

RESULTS

Our findings revealed a significant association between manually extracted masseter muscle volume on CT images and the life expectancy of patients with oral cancer. Notably, the manual and automatic extraction groups in the masseter muscle volume learning model showed a high correlation. Furthermore, the masseter muscle volume automatically extracted using the developed learning model exhibited a strong association with life expectancy.

CONCLUSIONS

The sarcopenia assessment method is useful for predicting the life expectancy of patients with oral cancer. In the future, it is crucial to validate and analyze various factors within the oral surgery field, extending beyond cancer patients.

Artificial intelligence-integrated optical coherence tomography for screening and early detection of oral cancer

Early detection of oral cancer is essential for improving patient survival rates and leads to higher chances of successful treatment, reduced cost of complex treatments, and improved quality of life of patients. Oral cancer often arises from oral potentially malignant disorders (OPMDs), among which leukoplakia is the most common. Numerous chairside diagnostic aids and imaging modalities have been reviewed for screening detection of OPMDs and oral cancer, but these techniques have limitations. Novel optical diagnostic modalities work on the assumption that neoplastic and dysplastic tissues have different absorbance and reflectance properties when exposed to specific wavelengths of light. Optical coherence tomography (OCT) imaging is a promising new technology in the field of oral oncology. The ability of OCT to provide real-time, nondestructive, high-resolution, radiation-free images makes it an ideal modality for screening and detection of neoplastic changes in the oral mucosa, but interpretation of OCT images requires training and expertise. To overcome this limitation, artificial intelligence-based diagnostic algorithms are being combined with OCT imaging to assist professionals in achieving high-accuracy interpretation of OCT images. This review highlights the applications and scope of artificial intelligence in OCT imaging for the screening and detection of early-stage oral cancer.

Hypervascular floor of mouth tumor: Rare presentation of oral cavity squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is the most common malignancy affecting the oral cavity and commonly presents as an exophytic lesion with red or white granular ulcerations. Most diagnoses are confirmed by biopsy and clinical features; however, early SCC has been shown to hide within benign appearing lesions, such as vascular tumors, resulting in missed diagnoses and delay in treatment. The following case report will discuss a patient who presented with a mass in the floor of the mouth which appeared as a vascular tumor on exam and imaging. This was originally thought to be benign based on FNA findings however was found to harbor invasive squamous cell carcinoma on final pathology. The goal of this case report is to provide a background on the variable presentations of OSCC, vascular tumors, and uncommon presentations for which specialists should be aware of in their practice.

Improved intraoperative identification of close margins in oral squamous cell carcinoma resections using a dual aperture fluorescence ratio approach: first in-human results

Significance

Surgical excision is the main treatment for solid tumors in oral squamous cell carcinomas, where wide local excision (achieving a healthy tissue margin of > 5    mm around the excised tumor) is the goal as it results in reduced local recurrence rates and improved overall survival.

Aim

No clinical methods are available to assess the complete surgical margin intraoperatively while the patient is still on the operating table; and while recent intraoperative back-bench fluorescence-guided surgery approaches have shown promise for detecting "positive" inadequate margins (< 1    mm ), they have had limited success in the detection of "close" inadequate margins (1 to 5 mm). Here, a dual aperture fluorescence ratio (dAFR) approach was evaluated as a means of improving detection of close margins.

Approach

The approach was evaluated on surgical specimens from patients who were administered a tumor-specific fluorescent imaging agent (cetuximab-800CW) prior to surgery. The dAFR approach was compared directly against standard wide-field fluorescence imaging and pathology measurements of margin thickness in specimens from three patients and a total of 12 margin locations (1 positive, 5 close, and 6 clear margins).

Results

The area under the receiver operating characteristic curve, representing the ability to detect close compared to clear margins (> 5    mm ) was found to be 1.0 and 0.57 for dAFR and sAF, respectively. Improvements in dAFR were found to be statistically significant (p < 0.02 ).

Conclusions

These results provide evidence that the dAFR approach potentially improves detection of close surgical margins.

A deep learning and radiomics fusion model based on contrast-enhanced computer tomography improves preoperative identification of cervical lymph node metastasis of oral squamous cell carcinoma

OBJECTIVES

In this study, we constructed and validated models based on deep learning and radiomics to facilitate preoperative diagnosis of cervical lymph node metastasis (LNM) using contrast-enhanced computed tomography (CECT).

MATERIALS AND METHODS

CECT scans of 100 patients with OSCC (217 metastatic and 1973 non-metastatic cervical lymph nodes: development set, 76 patients; internally independent test set, 24 patients) who received treatment at the Peking University School and Hospital of Stomatology between 2012 and 2016 were retrospectively collected. Clinical diagnoses and pathological findings were used to establish the gold standard for metastatic cervical LNs. A reader study with two clinicians was also performed to evaluate the lymph node status in the test set. The performance of the proposed models and the clinicians was evaluated and compared by measuring using the area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE).

RESULTS

A fusion model combining deep learning with radiomics showed the best performance (ACC, 89.2%; SEN, 92.0%; SPE, 88.9%; and AUC, 0.950 [95% confidence interval: 0.908-0.993, P < 0.001]) in the test set. In comparison with the clinicians, the fusion model showed higher sensitivity (92.0 vs. 72.0% and 60.0%) but lower specificity (88.9 vs. 97.5% and 98.8%).

CONCLUSION

A fusion model combining radiomics and deep learning approaches outperformed other single-technique models and showed great potential to accurately predict cervical LNM in patients with OSCC.

CLINICAL RELEVANCE

The fusion model can complement the preoperative identification of LNM of OSCC performed by the clinicians.

Identification of CT-based non-invasive radiomic biomarkers for overall survival prediction in oral cavity squamous cell carcinoma

This study addresses the limited non-invasive tools for Oral Cavity Squamous Cell Carcinoma (OSCC) survival prediction by identifying Computed Tomography (CT)-based biomarkers to improve prognosis prediction. A retrospective analysis was conducted on data from 149 OSCC patients, including CT radiomics and clinical information. An ensemble approach involving correlation analysis, score screening, and the Sparse-L1 algorithm was used to select functional features, which were then used to build Cox Proportional Hazards models (CPH). Our CPH achieved a 0.70 concordance index in testing. The model identified two CT-based radiomics features, Gradient-Neighboring-Gray-Tone-Difference-Matrix-Strength (GNS) and normalized-Wavelet-LLL-Gray-Level-Dependence-Matrix-Large-Dependence-High-Gray-Level-Emphasis (HLE), as well as stage and alcohol usage, as survival biomarkers. The GNS group with values above 14 showed a hazard ratio of 0.12 and a 3-year survival rate of about 90%. Conversely, the GNS group with values less than or equal to 14 had a 49% survival rate. For normalized HLE, the high-end group (HLE > - 0.415) had a hazard ratio of 2.41, resulting in a 3-year survival rate of 70%, while the low-end group (HLE ≤ - 0.415) had a 36% survival rate. These findings contribute to our knowledge of how radiomics can be used to predict the outcome so that treatment plans can be tailored for patients people with OSCC to improve their survival.

ανβ3 integrin-targeted ICG-derived probes for imaging-guided surgery and photothermal therapy of oral cancer

Indocyanine green (ICG), as the only Federal Drug Administration (FDA) approved fluorescence imaging agent, has been widely applied in clinics for near-infrared (NIR) fluorescence imaging-guided surgery and photothermal therapy of cancers. However, its lack of target specificity and poor photo and photothermal stabilities seriously restrict its wide application in clinical practice. Herein, we developed ICG-derived NIR fluorescent probes consisting of a cypate fluorophore and one or two cyclic-(arginine-glycine-aspartic acid) (cRGD) peptides that can specifically target αvβ3 integrin for accurate diagnosis and therapy of oral tumors. Probe Cy-2RGD has been demonstrated to possess bright NIR emission, great tumor targeting capability and a photothermal effect. Moreover, it could be successfully used for effective imaging-guided surgical resection as well as photothermal therapy of oral tumors. This work could provide a valuable tool for sensitive detection and accurate treatment of malignant tumors.

Diagnostic accuracy of contrast-enhanced computed tomography in assessing cervical lymph node status in patients with oral squamous cell carcinoma

OBJECTIVE

Accurate preoperative prediction of lymph node (LN) status plays a pivotal role in determining the extension of neck dissection (ND) required for patients with oral squamous cell carcinoma (OSCC). This study aims to evaluate the diagnostic accuracy of contrast-enhanced computed tomography (CT) in detecting LN metastases (LNMs) and to explore clinicopathological factors associated with its reliability.

METHODS

Data from 239 patients with primary OSCC who underwent preoperative CT and subsequent radical surgery involving ND were retrospectively reviewed. Suspicious LNs were categorized into three groups: accentuated (< 10 mm), enlarged (≥ 10 mm), and melted. Statistical analysis encompassing correlation and comparative analysis, and determination of sensitivity, specificity, PPV, and NPV were performed.

RESULTS

Overall, sensitivity was significantly higher in the accentuated LNs group (83.54%) compared to the melted LNs group (39.24%, p < 0.05, t test). Conversely, specificity was significantly higher in the melted LNs group (98.19%) compared to the accentuated LNs group (55.15%, p < 0.05, t test). Accentuated LNs exhibited a false negative rate of 13.00%. False positive rates were 51.80%, 30.26% and 8.82%, respectively. Diagnostic accuracy for detecting LNMs in level IIa and IIb exceeded that of level III. Patients with solely accentuated LNs were more likely to have a small, well-differentiated tumor. However, no distinctions emerged in terms of the occurrence of T4 tumors among the three groups.

CONCLUSION

CT proves sufficient to predict LNMs in patients with OSCC. Looking ahead, the potential integration of artificial intelligence and deep learning holds promise to further enhance the reliability of CT in LNMs detection. However, this prospect necessitates further investigation.

Urokinase-Type Plasminogen Activator Receptor (uPAR) Expression and [64Cu]Cu-DOTA-AE105 uPAR-PET/CT in Patient-Derived Xenograft Models of Oral Squamous Cell Carcinoma

PURPOSE

[64Cu]Cu-DOTA-AE105 urokinase-type plasminogen activator receptor (uPAR)-PET/CT is a novel and promising imaging modality for cancer visualization, although it has not been tested in head and neck cancer patients nor in preclinical models that closely resemble these heterogenous tumors, i.e., patient-derived xenograft (PDX) models. The aim of the present study was to establish and validate oral squamous cell carcinoma (OSCC) PDX models and to evaluate [64Cu]Cu-uPAR-PET/CT for tumor imaging in these models.

PROCEDURES

PDX flank tumor models were established by engrafting tumor tissue from three patients with locally advanced OSCC into immunodeficient mice. [64Cu]Cu-DOTA-AE105 was injected in passage 2 (P2) mice, and [64Cu]Cu-uPAR-PET/CT was performed 1 h and 24 h after injection. After the last PET scan, all animals were euthanized, and tumors dissected for autoradiography and immunohistochemical (IHC) staining.

RESULTS

Three PDX models were established, and all of them showed histological stability and unchanged heterogenicity, uPAR expression, and Ki67 expression through passages. A significant correlation between uPAR expression and tumor growth was found. All tumors of all models (n=29) showed tumor uptake of [64Cu]Cu-DOTA-AE105. There was a clear visual concordance between the distribution of uPAR expression (IHC) and [64Cu]Cu-DOTA-AE105 uptake pattern in tumor tissue (autoradiography). No significant correlation was found between IHC (H-score) and PET-signal (SUVmax) (r=0.34; p=0.07).

CONCLUSIONS

OSCC PDX models in early passages histologically mimic donor tumors and could serve as a valuable platform for the development of uPAR-targeted imaging and therapeutic modalities. Furthermore, [64Cu]Cu-uPAR-PET/CT showed target- and tumor-specific uptake in OSCC PDX models demonstrating the diagnostic potential of this modality for OSCC patients.

Contribution of FDG-PET in the diagnostic assessment of cervical lymph node metastasis in Oral Cavity Squamous Cell Carcinoma (OCSCC)

INTRODUCTION

The main objective of this study was to evaluate the contribution of FDG-PET in the diagnostic assessment of cervical lymph node metastasis in Oral Cavity Squamous Cell Carcinoma (OCSCC) and to advance a diagnostic threshold value for SUVmax in carcinomatous cervical lymph node.

METHODS

47 patients with OCSCC and suspicious cervical lymph node involvement (cN+) on FDG-PET were included in this retrospective study. The primary outcome was cervical lymph node SUVmax based on histological cervical metastatic disease (« gold standard »).

RESULTS

Among the 77 cervical lymph nodes considered suspicious on patients' FDG-PET, 50 were really metastatic on histological examination. The lymph node SUVmax with metastatic involvement on histological examination was 4.6 ± 3.9 [2.6 - 23.7] versus 3.6 ± 1.2 [2 - 7.3] without carcinomatous involvement (p = 0.004). The lymph node size was not statistically significant according to metastatic disease (p = 0.28).

DISCUSSION

A cervical lymph node SUVmax value of less than 2.6 on FDG-PET would suggest non-metastatic lymph node involvement. Supra Omohyoid Neck Dissection (SOHND) could therefore be performed in OCSCC when the SUVmax of the cervical lymph node is below this value in order to reduce the surgical morbidity of dissection of the lower internal jugular chain (Level IV).

A CNN-based approach for joint segmentation and quantification of nuclei and NORs in AgNOR-stained images

BACKGROUND AND OBJECTIVE

Oral cancer is the sixth most common kind of human cancer. Brush cytology for counting Argyrophilic Nucleolar Organizer Regions (AgNORs) can help early mouth cancer detection, lowering patient mortality. However, the manual counting of AgNORs still in use today is time-consuming, labor-intensive, and error-prone. The goal of our work is to address these shortcomings by proposing a convolutional neural network (CNN) based method to automatically segment individual nuclei and AgNORs in microscope slide images and count the number of AgNORs within each nucleus.

METHODS

We systematically defined, trained and tested 102 CNNs in the search for a high-performing solution. This included the evaluation of 51 network architectures combining 17 encoders with 3 decoders and 2 loss functions. These CNNs were trained and evaluated on a new AgNOR-stained image dataset of epithelial cells from oral mucosa containing 1,171 images from 48 patients, with ground truth annotated by specialists. The annotations were greatly facilitated by a semi-automatic procedure developed in our project. Overlapping nuclei, which tend to hide AgNORs, thus affecting their true count, were discarded using an automatic solution also developed in our project. Besides the evaluation on the test dataset, the robustness of the best performing model was evaluated against the results produced by a group of human experts on a second dataset.

RESULTS

The best performing CNN model on the test dataset consisted of a DenseNet-169 + LinkNet with Focal Loss (DenseNet-169 as encoder and LinkNet as decoder). It obtained a Dice score of 0.90 and intersection over union (IoU) of 0.84. The counting of nuclei and AgNORs achieved precision and recall of 0.94 and 0.90 for nuclei, and 0.82 and 0.74 for AgNORs, respectively. Our solution achieved a performance similar to human experts on a set of 291 images from 6 new patients, obtaining Intraclass Correlation Coefficient (ICC) of 0.91 for nuclei and 0.81 for AgNORs with 95% confidence intervals of [0.89, 0.93] and [0.77, 0.84], respectively, and p-values < 0.001, confirming its statistical significance. Our AgNOR-stained image dataset is the most diverse publicly available AgNOR-stained image dataset in terms of number of patients and the first for oral cells.

CONCLUSIONS

CNN-based joint segmentation and quantification of nuclei and NORs in AgNOR-stained images achieves expert-like performance levels, while being orders of magnitude faster than the later. Our solution demonstrated this by showing strong agreement with the results produced by a group of specialists, highlighting its potential to accelerate diagnostic workflows. Our trained model, code, and dataset are available and can stimulate new research in early oral cancer detection.

Potential of preoperative fluorodeoxyglucose-positron emission tomography/computed tomography to diagnose contralateral lymph node metastases in patients with oral cancer

OBJECTIVE

To establish a decision tree using preoperative PET/computed tomography (CT) parameters for detecting contralateral lymph node metastasis (CLNM) in oral cancer patients.

METHODS

In total, 140 patients with a confirmed histopathological diagnosis of oral carcinoma showed fluorodeoxyglucose accumulation of contralateral lymph nodes in PET images. Of 260 lymph nodes, eight were metastatic. We compared metastatic and non-metastatic nodes using Fisher-Freeman-Halton exact and Fisher's exact and Mann-Whitney U tests. The diagnostic performance was analyzed using receiver operating characteristic curves. We established a decision tree using exhaustive chi-squared automatic interaction detection algorithm.

RESULTS

Five PET/CT parameters were significantly different between metastatic and non-metastatic nodes: the longest ( P  = 0.015) and shortest ( P  = 0.023) diameter, and the maximum standardized uptake values (SUVmax) of the contralateral node ( P  = 0.030), primary tumor ( P  < 0.001), and ipsilateral node ( P  < 0.001). The area under the curves of SUVmax of the primary tumor (0.887), ipsilateral node (0.886), and longest diameter (0.752) were the largest and these three parameters were used as predictive criteria in the decision tree. The accuracy of the decision tree was 97.7% with 100% sensitivity and 97.6% specificity.

CONCLUSION

Preoperative PET/CT imaging with a decision tree has the potential to diagnose CLNM in patients with oral cancer.

The potential of the Crystal Cam handheld gamma-camera for preoperative and intraoperative sentinel lymph node localization in early-stage oral cancer

PURPOSE

Evaluating the Crystal Cam handheld gamma-camera for preoperative and intraoperative sentinel lymph node (SLN) localization in early-stage oral cancer.

METHODS

The handheld gamma-camera was used complementary to conventional gamma-probe guidance for intraoperative SLN localization in 53 early-stage oral cancer patients undergoing SLN biopsy. In 36 of these patients, a blinded comparison was made between preoperative handheld gamma-camera and lymphoscintigraphy outcomes. Of those, the reliability for marking the SLN's location using both handheld gamma-camera and a 57Co-penpoint marker was evaluated in 15 patients.

RESULTS

In the entire cohort, the handheld gamma-camera preoperatively detected 116/122 (95%) of SLNs identified by lymphoscintigraphy. In those patients where the observer was blinded for lymphoscintigraphy (n = 36), 71/77 (92%) SLNs were correctly identified by handheld gamma-camera. Overlooked SLNs by handheld gamma-camera were mainly located near the injection site. The SLN's marked location by handheld gamma-camera and 57Co-penpoint marker was considered accurate in 42/43 (98%) SLNs. The intraoperative use of the handheld gamma-camera led to the extirpation of 16 additional 'hot' lymph nodes in 14 patients, 4 of which harbored metastases, and prevented 2 patients (4%) from being erroneously staged negative for nodal metastasis. In those with follow-up ≥ 24 months or false-negative outcomes < 24 months following SLNB, a sensitivity of 82% and negative predictive value of 93% was obtained.

CONCLUSION

The Crystal Cam handheld gamma-camera offers reliable preoperative and intraoperative SLN localization and might reduce the risk of missing a malignant SLN during surgery. Detecting SLNs near the injection site by handheld gamma-camera remains challenging.

Comparison of image quality and quantitative parameters in intravoxel incoherent motion imaging at 3-T based on turbo spin-echo and echo-planar imaging in patients with oral cancer

PURPOSE

To compare the image quality, apparent diffusion coefficient (ADC), and intravoxel incoherent motion- (IVIM) derived parameters of IVIM imaging based on turbo spin-echo (TSE) and echo-planar imaging (EPI) of patients with oral cancer and to assess the equivalence of the ADC and IVIM-derived parameters.

METHODS

Thirty patients with oral cancer underwent TSE-IVIM and EPI-IVIM imaging using a 3.0-T system. The distortion ratio (DR), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), qualitative evaluations of image quality, ADC, pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) were compared between the two sequences. The consistency of the quantitative parameters in oral cancer between the TSE and EPI sequences was evaluated using a Bland-Altman analysis.

RESULTS

TSE-IVIM had a significantly smaller DR than EPI-IVIM (P < 0.001). The CNR of EPI-IVIM on most of the anatomical sites was significantly higher than that of TSE-IVIM (P < 0.05), while the SNR was not significantly different (P > 0.05). TSE-IVIM had significantly higher image quality, less distortion and artifacts, and lower image contrast compared with EPI-IVIM (P < 0.05). The lesion-edge sharpness and diagnostic confidence of EPI-IVIM were lower than that of TSE-IVIM, although no significant differences existed (P > 0.05). The ADC and D of TSE-IVIM had better reproducibility (intraclass correlation coefficient > 0.9). Although no significant difference existed for the ADC and IVIM-derived parameters of lesions between the two sequences (P > 0.05), wide limits of agreement were found in the Bland-Altman plots.

CONCLUSION

TSE-IVIM could be used as an alternative technique to EPI-IVIM for patients with oral cancer because of its better image quality. Furthermore, TSE-IVIM can provide more accurate quantitative parameters. However, the quantitative parameters derived from the two IVIM techniques cannot be used as equivalent parameters for patients with oral cancer.

Noninvasive diagnosis of oral squamous cell carcinoma by multi-level deep residual learning on optical coherence tomography images

BACKGROUND

Oral Squamous Cell Carcinoma (OSCC) is one of the most severe cancers in the world, and its early detection is crucial for saving patients. There is an inevitable necessity to develop the automatic noninvasive OSCC diagnosis approach to identify the malignant tissues on Optical Coherence Tomography (OCT) images.

METHODS

This study presents a novel Multi-Level Deep Residual Learning (MDRL) network to identify malignant and benign(normal) tissues from OCT images and trains the network in 460 OCT images captured from 37 patients. The diagnostic performances are compared with different methods in the image-level and the resected patch-level.

RESULTS

The MDRL system achieves the excellent diagnostic performance, with 91.2% sensitivity, 83.6% specificity, 87.5% accuracy, 85.3% PPV, and 90.2% NPV in image-level, with 0.92 AUC value. Besides, it also implements 100% sensitivity, 86.7% specificity, 93.1% accuracy, 87.5% PPV, and 100% NPV in the resected patch-level.

CONCLUSION

The developed deep learning system expresses superior performance in noninvasive oral squamous cell carcinoma diagnosis, compared with traditional CNNs and a specialist.

Multimodal Prediction of Cervical Lymph Node Metastasis and Recurrence in Oral Squamous Cell Carcinoma

BACKGROUND/AIM

Oral squamous cell carcinoma (OSCC) is the most common malignancy in the head/neck region, and cervical lymph node (CLN) metastasis is a strong poor-prognosis factor. In addition, many patients with OSCC experience recurrence despite multidisciplinary treatment. We sought to identify factors associated with CLN metastasis and recurrence in patients with OSCC.

PATIENTS AND METHODS

We evaluated a total of 45 patients and 233 target CLNs. The longest diameter of the target CLN, the shortest diameter of the target CLN (LS), the area of the target CLN, and the relative computed tomography (CT) values of the target CLNs calculated based on the CT values of the internal jugular vein (LCT) were obtained from preoperative CT images, and the maximum standardized uptake values of the primary tumor (pSUV) and target CLN (nSUV) were obtained from preoperative 18F-fluorodeoxyglucose-positron emission tomography/CT images. We performed immunohistochemical staining for cytokeratin 13 (CK13) and 17 (CK17) on neck dissection tissues.

RESULTS

A discrimination equation was used that can predict CLN metastasis with a 92.2% discrimination rate using LS, LCT, pSUV, and nSUV. The CLNs were divided into discrimination and non-discrimination groups based on discriminant equations and CK13 and CK17 were used as the objective variables. A significantly higher recurrence rate was observed in the non-discrimination group (CK13: 5-year recurrence rate 28.6% vs. 64.3%, p<0.01; CK17: 5-year recurrence rate 28.0% vs. 76.0%, p<0.01).

CONCLUSION

CLN metastases in OSCC can be assessed by combining preoperative imaging. The combined use of CK13 and CK17 expression with imaging findings offers an integrated approach to predict OSCC recurrence.

Trends in Positive Surgical Margins in cT3-T4 Oral Cavity Squamous Cell Carcinoma

OBJECTIVE

Positive surgical margins in oral cavity squamous cell carcinoma are associated with cost escalation, treatment intensification, and greater risk of recurrence and mortality. The positive margin rate has been decreasing for cT1-T2 oral cavity cancer over the past 2 decades. We aim to evaluate positive margin rates in cT3-T4 oral cavity cancer over time, and determine factors associated with positive margins.

STUDY DESIGN

Retrospective analysis of a national database.

SETTING

National Cancer Database 2004 to 2018.

METHODS

All adult patients diagnosed between 2004 and 2018 who underwent primary curative intent surgery for previously untreated cT3-T4 oral cavity cancer with known margin status were included. Logistic univariable and multivariable regression analyses were performed to identify factors associated with positive margins.

RESULTS

Among 16,326 patients with cT3 or cT4 oral cavity cancer, positive margins were documented in 2932 patients (18.1%). Later year of treatment was not significantly associated with positive margins (odds ratio [OR] 0.98, 95% confidence interval [CI] 0.96-1.00). The proportion of patients treated at academic centers increased over time (OR 1.02, 95% CI 1.01-1.03). On multivariable analysis, positive margins were significantly associated with hard palate primary, cT4 tumors, advancing N stage, lymphovascular invasion, poorly differentiated histology, and treatment at nonacademic or low-volume centers.

CONCLUSION

Despite increased treatment at academic centers for locally advanced oral cavity cancer, there has been no significant decrease in positive margin rates which remains high at 18.1%. Novel techniques for margin planning and assessment may be required to decrease positive margin rates in locally advanced oral cavity cancer.

Confocal microscopy in oral cancer and oral potentially malignant disorders: A systematic review

OBJECTIVE

To systematically identify and summarise current research on the utility of confocal microscopy in oral squamous cell carcinoma and oral epithelial dysplasia in oral potentially malignant disorders.

METHODS

Databases Medline, Embase, Evidence-Based Medicine, and Web of Science were searched with articles screened and included if their primary objective was the use of a confocal microscope in diagnosis of oral cancer or epithelial dysplasia, in vivo or ex vivo.

RESULTS AND DISCUSSION

Twenty-eight relevant studies were identified of which 21 studies included oral squamous cell carcinoma specimens. Fifteen studies included in vivo use. The studies included both qualitative and fluorescence confocal microscope and reflectance confocal microscope analysis along with quantitative analysis of carcinoma and dysplasia. Thirteen studies reported the predictive value of their confocal device in the diagnosis of dysplasia and carcinoma. The quantitative software-based studies show promise in objectifying the diagnostic process for identifying abnormalities within the microstructure of the oral mucosa.

CONCLUSIONS

There was heterogeneity in the criteria for diagnosis of dysplasia and oral squamous cell carcinoma with experience levels of assessors impacting method efficacy. Both qualitative and quantitative confocal assessment methodologies have been explored, the latter highlighting the potential of future machine-augmented diagnostic precision.

Prognostic prediction using maximum standardized uptake value ratio of lymph node-to-primary tumor in preoperative PET-CT for oral squamous cell carcinoma

This study aimed to calculate the ratio of maximum standardized uptake values of cervical lymph nodes to maximum standardized uptake values of primary tumors measured by preoperative fluorodeoxyglucose positron-emission tomography in oral cancer patients, and to retrospectively examine the prognostic association and evaluate whether it could be a prognostic factor. We retrospectively examined consecutive Japanese patients diagnosed with oral squamous cell carcinoma who underwent oral cancer resection and cervical dissection between January 2014 and December 2018. The study included 52 patients aged 39-89 years (median age 66.5 years), excluding non-cervical dissection surgery and/or non-underwent preoperative positron-emission tomography. The maximum standardized uptake value of the cervical lymph nodes and primary tumor was measured, and the ratio of maximum standardized uptake values of the lymph nodes to that of the primary tumor was calculated. The median follow-up of 52 patients was 1,465 days (198-2,553 days), and overall survival was significantly worse in patients with a high lymph node-to-tumor standardized uptake values ratio (>0.4739) (5 years, 58.8% vs. 88.2%; P<0.05). Pretreatment lymph node-to-tumor standardized uptake values ratio can be easily calculated, and as a predictor of prognosis, it may be of assistance when considering the treatment strategy for oral cancer.

Non-Gaussian model-based diffusion-weighted imaging of oral squamous cell carcinoma: associations with Ki-67 proliferation status

OBJECTIVES

To investigate possible associations between diffusion-weighted imaging (DWI) parameters derived from a non-Gaussian model fitting and Ki-67 status in patients with oral squamous cell carcinoma (OSCC).

METHODS

Twenty-four patients with newly diagnosed OSCC were prospectively recruited. DWI was performed using six b-values (0-2500). The diffusion-related parameters of kurtosis value (K), kurtosis-corrected diffusion coefficient (DK), diffusion heterogeneity (α), distributed diffusion coefficient (DDC), slow diffusion coefficient (Dslow), and apparent diffusion coefficient (ADC) were calculated from four diffusion fitting models. Ki-67 status was categorized as low (Ki-67 percentage score < 20%), middle (20-50%), or high (> 50%). Kruskal-Wallis tests were performed between each non-Gaussian diffusion model parameters and Ki-67 grade.

RESULTS

The Kruskal-Wallis tests revealed that multiple parameters (K, ADC, Dk, DDC and Dslow) showed statistically significant differences between the three levels of Ki-67 status (K: p = 0.020, ADC: p = 0.012, Dk: p = 0.027, DDC: p = 0.007 and Dslow: p = 0.026).

CONCLUSIONS

Several non-Gaussian diffusion model parameters and ADC values were significantly associated with Ki-67 status and have potential as promising prognostic biomarkers in patients with OSCC.

Volume-based 18F-fluorodeoxyglucose positron emission tomography/computed tomography parameters correlate with delayed neck metastasis in clinical early-stage oral squamous cell carcinoma

OBJECTIVE

There is no known preoperative marker that can effectively predict the risk of delayed neck metastasis (DNM), which is an important factor that determines the prognosis of early-stage oral cancer. In this study, we examined whether 18F-fluorodeoxyglucose positron emission tomography (18F-FDG-PET)/computed tomography (CT) uptake parameters of primary cancer can predict the risk of DNM in early-stage oral squamous cell carcinoma (OSCC).

METHODS

Data from patients with stage I-II OSCC who underwent surgical resection of the primary tumor without elective neck dissection between January 2009 and December 2016 were retrospectively reviewed. Patient characteristics, histopathological factors, and PET/CT parameters (maximum standardized uptake value [SUVmax], metabolic tumor volume [MTV], and total lesion glycolysis [TLG]) were evaluated for their association with DNM. DNM rates were calculated, and the parameters that were statistically significant in the univariate analysis were used as explanatory variables. Independent factors associated with DNM were identified using multivariate analysis. For all statistical analyses, p-values < 0.05 were considered statistically significant.

RESULTS

Data from 71 patients were analyzed in the study. The overall DNM rate among all patients was 21.8%. The univariate analysis showed that the T classification, depth of invasion, pattern of invasion, lymphovascular invasion, SUVmax, MTV, and TLG were significant predictors of DNM. However, the multivariate analysis revealed that only the depth of invasion, MTV, and TLG were independent predictors of DNM.

CONCLUSION

This study suggests that, in addition to conventional predictors, volume-based PET parameters are useful predictors of DNM in those with early-stage OSCC.

Development of an intraoral handheld optical coherence tomography-based angiography probe for multi-site oral imaging

Oral cancer, primarily oral squamous cell carcinomas (OSCC), is a major health concern worldwide. The current gold standard for the diagnosis of OSCC is biopsy and histopathological analysis, which is invasive and can place a huge financial burden on the healthcare system. Optical coherence tomography-based angiography (OCTA) is a non-invasive imaging technique that shows promise as an imaging modality to aid the diagnosis of OSCC. This Letter outlines the development of a handheld intraoral OCT probe applied to a swept-source OCT system with an angiography function for oral applications. The probe has a thin body with a diameter of 17.8 mm and a two-lens system with a working distance that is adjustable from 20.92 mm to 24.08 mm, a field of view 9 mm in diameter, an imaging depth of ∼1.7 mm, and resolutions of 39.38 µm (laterally) and 33.37 µm (axially). This probe was used to scan 14 oral sites to evaluate its ability to scan various sites in the oral cavity. This system has the potential to reduce invasive procedures and aid early OSCC diagnosis.

Multimodal fluorescence imaging and spectroscopic techniques for oral cancer screening: a real-time approach

The survival rate of oral squamous cell carcinoma (OSCC) patients is very poor, but it can be improved using highly sensitive, specific, and accurate techniques. Autofluorescence and fluorescence techniques are very sensitive and helpful in cancer screening; being directly linked with the molecular levels of human tissue, they can be used as a quantitative tool for cancer detection. Here, we report the development of multi-modal autofluorescence and fluorescence imaging and spectroscopic (MAF-IS) smartphone-based systems for fast and real-time oral cancer screening. MAF-IS system is indigenously developed and offers the advantages of being a low-cost, handy, non-contact, non-invasive, and easily operable device that can be employed in hospitals, including low-resource settings. In this study, we report the results of 43 individuals with 28 OSCC and 15 oral potentially malignant disorders (OPMDs), i.e., epithelial dysplasia and oral submucous fibrosis, using the developed devices. We observed a red shift in fluorescence emission spectrain vivo. We found red-shift of 7.72 ± 6 nm, 3 ± 4.36 nm, and 1.33 ± 0.47 nm in the case of OSCC, epithelial dysplasia, and oral submucous fibrosis, respectively, compared to normal. The results were compared with histopathology and found to be consistent. Further, the MAF-IS system provides results in real-time with higher accuracy and sensitivity compared to devices using a single modality. Our system can achieve an accuracy of 97% with sensitivity and specificity of 100% and 94.7%, respectively, even with a smaller number of patients (28 patients of OSCC). The proposed MAF-IS device has great potential for fast screening and diagnosis of oral cancer in the future.

Invasion depth estimation of carcinoma cells using adaptive stain normalization to improve epidermis segmentation accuracy

Submucosal invasion depth is a significant prognostic factor when assessing lymph node metastasis and cancer itself to plan proper treatment for the patient. Conventionally, oncologists measure the invasion depth by hand which is a laborious, subjective, and time-consuming process. The manual pathological examination by measuring accurate carcinoma cell invasion with considerable inter-observer and intra-observer variations is still challenging. The increasing use of medical imaging and artificial intelligence reveals a significant role in clinical medicine and pathology. In this paper, we propose an approach to study invasive behavior and measure the invasion depth of carcinoma from stained histopathology images. Specifically, our model includes adaptive stain normalization, color decomposition, and morphological reconstruction with adaptive thresholding to separate the epithelium with blue ratio image. Our method splits the image into multiple non-overlapping meaningful segments and successfully finds the homogeneous segments to measure accurate invasion depth. The invasion depths are measured from the inner epithelium edge to outermost pixels of the deepest part of particles in image. We conduct our experiments on skin melanoma tissue samples as well as on organotypic invasion model utilizing myoma tissue and oral squamous cell carcinoma. The performance is experimentally compared to three closely related reference methods and our method provides a superior result in measuring invasion depth. This computational technique will be beneficial for the segmentation of epithelium and other particles for the development of novel computer-aided diagnostic tools in biobank applications.

Emerging clinical applications in oncology for non-invasive multi- and hyperspectral imaging of cell and tissue autofluorescence

Hyperspectral and multispectral imaging of cell and tissue autofluorescence is an emerging technology in which fluorescence imaging is applied to biological materials across multiple spectral channels. This produces a stack of images where each matched pixel contains information about the sample's spectral properties at that location. This allows precise collection of molecularly specific data from a broad range of native fluorophores. Importantly, complex information, directly reflective of biological status, is collected without staining and tissues can be characterised in situ, without biopsy. For oncology, this can spare the collection of biopsies from sensitive regions and enable accurate tumour mapping. For in vivo tumour analysis, the greatest focus has been on oral cancer, whereas for ex vivo assessment head-and-neck cancers along with colon cancer have been the most studied, followed by oral and eye cancer. This review details the scope and progress of research undertaken towards clinical translation in oncology.

EGFR-targeted fluorescence molecular imaging for intraoperative margin assessment in oral cancer patients: a phase II trial

Inadequate surgical margins occur frequently in oral squamous cell carcinoma surgery. Fluorescence molecular imaging (FMI) has been explored for intraoperative margin assessment, but data are limited to phase-I studies. In this single-arm phase-II study (NCT03134846), our primary endpoints were to determine the sensitivity, specificity and positive predictive value of cetuximab-800CW for tumor-positive margins detection. Secondary endpoints were safety, close margin detection rate and intrinsic cetuximab-800CW fluorescence. In 65 patients with 66 tumors, cetuximab-800CW was well-tolerated. Fluorescent spots identified in the surgical margin with signal-to-background ratios (SBR) of ≥2 identify tumor-positive margins with 100% sensitivity, 85.9% specificity, 58.3% positive predictive value, and 100% negative predictive value. An SBR of ≥1.5 identifies close margins with 70.3% sensitivity, 76.1% specificity, 60.5% positive predictive value, and 83.1% negative predictive value. Performing frozen section analysis aimed at the fluorescent spots with an SBR of ≥1.5 enables safe, intraoperative adjustment of surgical margins.

Influence of Data Augmentation Strategies on the Segmentation of Oral Histological Images Using Fully Convolutional Neural Networks

Segmentation of tumor regions in H &E-stained slides is an important task for a pathologist while diagnosing different types of cancer, including oral squamous cell carcinoma (OSCC). Histological image segmentation is often constrained by the availability of labeled training data since labeling histological images is a highly skilled, complex, and time-consuming task. Thus, data augmentation strategies become essential to train convolutional neural networks models to overcome the overfitting problem when only a few training samples are available. This paper proposes a new data augmentation strategy, named Random Composition Augmentation (RCAug), to train fully convolutional networks (FCN) to segment OSCC tumor regions in H &E-stained histological images. Given the input image and their corresponding label, a pipeline with a random composition of geometric, distortion, color transfer, and generative image transformations is executed on the fly. Experimental evaluations were performed using an FCN-based method to segment OSCC regions through a set of different data augmentation transformations. By using RCAug, we improved the FCN-based segmentation method from 0.51 to 0.81 of intersection-over-union (IOU) in a whole slide image dataset and from 0.65 to 0.69 of IOU in a tissue microarray images dataset.

Contrast-enhanced CT predictors of lymph nodal metastasis in dogs with oral melanoma

Canine oral melanoma (OM) has highly aggressive behavior, with frequent local metastasis. Computed tomography 3D volumetric analysis is an accurate predictor of lymph node (LN) metastasis of oral cancers in humans but whether this is true for dogs with OM is unknown. In this retrospective observational study, CT imaging was used to assess mandibular and retropharyngeal lymphocenter (LC) changes in dogs with nodal metastatic (n = 12) and non-metastatic (n = 10) OM, then these findings were compared with those of healthy control dogs (n = 11). Using commercial software (Analyze, Biomedical Imaging Resource), lymphocenters were defined as regions of interest. LC voxels, area (mm2 ), volume (mm3 ), and degree of attenuation (HU) were compared between groups. Mandibular lymphocenter (MLC) metastasis was present in 12 of 22 (54.5%) dogs; no dogs had confirmed retropharyngeal lymphocenter (RLC) metastasis. Mandibular lymphocenter volume was significantly different between positive and negative LCs (median 2221 and 1048 mm3 , respectively, P = 0.008), and between positive and control LCs (median 880 mm3 , P < 0.01). There was no evidence of a significant difference in voxel number or attenuation between groups. Mandibular lymphocenter volume moderately discriminated for metastatic status (AUC 0.754 [95% CI = 0.572-0.894, P = 0.02]), with a positive predictive value of 57.1% (95% CI = 0.389-0.754). Adjusting for patient weight did not improve discrimination (AUC = 0.659 (95% CI = 0.439-0.879, P = 0.13]). In conclusion, these findings suggest 3D CT volume measurement of MLC can predict nodal metastasis in dogs with OM and shows promise but further research, perhaps in combination with other modalities, is required to improve accuracy.

Post-operative PET/CT improves the detection of early recurrence of squamous cell carcinomas of the oral cavity

BACKGROUND

We evaluate the impact of post-operative 18-fluorodeoxyglucose positron emission tomography with computed tomography (PET/CT) for radiation planning on the detection of early recurrence (ER) and treatment outcomes in oral squamous cell carcinoma (OSCC).

METHODS

We retrospectively reviewed the records of patients treated with post-operative radiation between 2005 and 2019 for OSCC at our institution. Extracapsular extension and positive surgical margins were classified as high risk features; pT3-4, node positivity, lymphovascular invasion, perineural invasion, tumor thickness >5 mm, and close surgical margins were considered intermediate risk features. Patients with ER were identified. Inverse probability of treatment weighting (IPTW) was used to adjust for imbalances between baseline characteristics.

RESULTS

391 patients with OSCC were treated with post-operative radiation. 237 (60.6%) patients underwent post-operative PET/CT planning vs. 154 (39.4%) who were planned with CT only. Patients screened with post-operative PET/CT were more likely to be diagnosed with ER than those planned with CT only (16.5 vs. 3.3%, p < 0.0001). Among patients with ER, those with intermediate features were more likely than those high risk features to undergo major treatment intensification, including re-operation, the addition of chemotherapy, or intensification of radiation by ≥ 10 Gy (91% vs. 9%, p < 0.0001). Post-operative PET/CT was associated with improved disease-free and overall survival for patients with intermediate risk features (IPTW log-rank p = 0.026 and p = 0.047, respectively) but not high risk features (IPTW log-rank p = 0.44 and p = 0.96).

CONCLUSIONS

Use of post-operative PET/CT is associated with increased detection of early recurrence. Among patients with intermediate risk features, this may translate to improved disease-free survival.

Evaluating the prognosis of oral squamous cell carcinoma patients via L3 skeletal muscle index

OBJECTIVES

This study aimed to construct a formula to predict L3 skeletal muscle cross-sectional area (CSA) from C3 CSA and to select the cutoff values to evaluate the nutritional status in OSCC.

MATERIALS AND METHODS

A total of 220 OSCC patients in Nanfang Hospital were divided into two groups: the training set (n = 100) and the validation set (n = 120). Patients in the training set were performed the preoperative whole-body positron emission tomography-computed tomography (PET/CT) scans, and patients in the validation set received preoperative head-and-neck computed tomography (CT) scans. C3 CSA and L3 CSA were delineated. The predictive formula was established, and the gender-specific thresholds of malnutrition were obtained by X-tile software in training set. Finally, the formula and cutoff values were validated.

RESULTS

The predictive formula was successfully established. The gender-specific cutoff values for L3 SMI were 55.0 cm² /m² for men and 36.6 cm² /m² for women. There were no differences between the overall survival (OS) of patients diagnosed with malnutrition and that of patients who are not malnutrition.

CONCLUSIONS

Our studies reveal that the L3 CSA could be calculated by C3 CSA conveniently with our formula in OSCC, which allowed us to assess malnutrition with head-and-neck CT image. However, there is no direct connection found between malnutrition and OS in OSCC. Hence, further studies with a larger sample size may be required.

Rational Design of a Self-Assembling High Performance Organic Nanofluorophore for Intraoperative NIR-II Image-Guided Tumor Resection of Oral Cancer

The first line of treatment for most solid tumors is surgical resection of the primary tumor with adequate negative margins. Incomplete tumor resections with positive margins account for over 75% of local recurrences and the development of distant metastases. In cases of oral cavity squamous cell carcinoma (OSCC), the rate of successful tumor removal with adequate margins is just 50-75%. Advanced real-time imaging methods that improve the detection of tumor margins can help improve success rates,overall safety, and reduce the cost. Fluorescence imaging in the second near-infrared (NIR-II) window has the potential to revolutionize the field due to its high spatial resolution, low background signal, and deep tissue penetration properties, but NIR-II dyes with adequate in vivo performance and safety profiles are scarce. A novel NIR-II fluorophore, XW-03-66, with a fluorescence quantum yield (QY) of 6.0% in aqueous media is reported. XW-03-66 self-assembles into nanoparticles (≈80 nm) and has a systemic circulation half-life (t_1/2 ) of 11.3 h. In mouse models of human papillomavirus (HPV)+ and HPV- OSCC, XW-03-66 outperformed indocyanine green (ICG), a clinically available NIR dye, and enabled intraoperative NIR-II image-guided resection of the tumor and adjacent draining lymph node with negative margins. In vitro and in vivo toxicity assessments revealed minimal safety concerns for in vivo applications.

Detection of micro-metastasis using cytokeratins (AE1/AE3) in haematoxylin & eosin-stained N0 lymph nodes of oral squamous cell carcinoma

Background & objectives

Oral squamous cell carcinoma (OSCC) is one of the most common malignancies affecting the head-and-neck region, regional lymph nodes being an important prognostication factor dictating the survival rate. Despite an array of modalities used, clinically, radiographically and routine histopathologically, the detection of micro-metastasis (2-3 mm tumour cell deposits) in the lymph nodes often escapes identification. The presence of few of these tumour epithelial cells in the lymph nodes drastically increases mortality and alters treatment plan. Hence, the identification of these cells is of major prognostic significance for a patient. Thus, the present study was aimed to evaluate and detect the efficacy of the immunohistochemical (IHC) marker [cytokeratin (CK) AE1/AE3] over routine Hematoxylin & eosin (H & E) staining in detecting micro-metastasis in the lymph nodes of OSCC cases.

Methods

Hundred H & E-stained N0 lymph nodes of OSCC cases treated with radical neck dissection were subjected to IHC with marker AE1/AE3 antibody cocktail for detecting micro-metastasis.

Results

The IHC marker CK cocktail (AE1/AE3) did not demonstrate any positive reactivity for the target antigen in all the 100 H & E stained lymph node sections evaluated in the present study.

Interpretation & conclusions

This study was undertaken to check the efficacy of IHC (CK cocktail AE1/AE3) in the detection of micro-metastasis in lymph nodes that are found to be negative in routine H&E stained sections. The findings of this study suggest that the IHC marker AE1/AE3 did not prove to be useful to detect micro-metastasis in this study population.

Contrast-enhanced and indirect computed tomography lymphangiography accurately identifies the cervical lymphocenter at risk for metastasis in pet dogs with spontaneously occurring oral neoplasia

For dogs with oral tumors, cervical lymph node (LN) metastasis alters treatment and prognosis. It is therefore prudent to make an accurate determination of the clinical presence (cN+ neck) or absence (cN0 neck) of metastasis prior to treatment. Currently, surgical LN extirpation with histopathology is the gold standard for a diagnosis of metastasis. Yet, recommendations to perform elective neck dissection (END) for staging are rare due to morbidity. Sentinel lymph node (SLN) mapping with indirect computed tomography lymphangiography (ICTL) followed by targeted biopsy (SLNB) is an alternative option to END. In this prospective study, SLN mapping followed by bilateral END of all mandibular LNs (MLNs) and medial retropharyngeal LNs (MRLNs) was performed in 39 dogs with spontaneously occurring oral neoplasia. A SLN was identified by ICTL in 38 (97%) dogs. Lymphatic drainage patterns were variable although most often the SLN was identified as a single ipsilateral MLN. In the 13 dogs (33%) with histopathologically confirmed LN metastasis, ICTL correctly identified the draining lymphocentrum in all (100%). Metastasis was confined to the SLN in 11 dogs (85%); 2 dogs (15%) had metastasis beyond the SLN ipsilaterally. Contrast enhanced CT features had good accuracy in predicting metastasis, with short axis measurements less than 10.5 mm most predictive. ICTL imaging features alone were unable to predict metastasis. Cytologic or histopathologic SLN sampling is recommended prior to treatment to inform clinical decision-making. This is the largest study to show potential clinical utility of minimally invasive ICTL for cervical LN evaluation in canine oral tumors.

Deep learning-based pathology image analysis predicts cancer progression risk in patients with oral leukoplakia

BACKGROUND

Oral leukoplakia (OL) is associated with an increased risk for oral cancer (OC) development. Prediction of OL cancer progression may contribute to decreased OC morbidity and mortality by favoring early intervention. Current OL progression risk assessment approaches face large interobserver variability and is weakly prognostic. We hypothesized that convolutional neural networks (CNN)-based histology image analyses could accelerate the discovery of better OC progression risk models.

METHODS

Our CNN-based oral mucosa risk stratification model (OMRS) was trained to classify a set of nondysplastic oral mucosa (OM) and a set of OC H&E slides. As a result, the OMRS model could identify abnormal morphological features of the oral epithelium. By applying this model to OL slides, we hypothesized that the extent of OC-like features identified in the OL epithelium would correlate with its progression risk. The OMRS model scored and categorized the OL cohort (n = 62) into high- and low-risk groups.

RESULTS

OL patients classified as high-risk (n = 31) were 3.98 (95% CI 1.36-11.7) times more likely to develop OC than low-risk ones (n = 31). Time-to-progression significantly differed between high- and low-risk groups (p = 0.003). The 5-year OC development probability was 21.3% for low-risk and 52.5% for high-risk patients. The predictive power of the OMRS model was sustained even after adjustment for age, OL site, and OL dysplasia grading (HR = 4.52, 1.5-13.7).

CONCLUSION

The ORMS model successfully identified OL patients with a high risk of OC development and can potentially benefit OC early diagnosis and prevention policies.

Ultrasound-guided resection for squamous cell carcinoma of the buccal mucosa: A feasibility study

BACKGROUND

Image-guided surgery could help obtain clear (≥5.0 mm) resection margins. This feasibility study investigated ultrasound-guided resection accuracy of buccal mucosa squamous cell carcinoma (BMSCC).

METHODS

MRI and ultrasound measurements of tumor thickness were compared to histology in 13 BMSCC-patients. Ultrasound measured margins (at five locations) on the specimen were compared to the corresponding histological margins.

RESULTS

Accuracy of in- and ex-vivo ultrasound (mean deviation from histology: 1.6 mm) for measuring tumor thickness was comparable to MRI (mean deviation from histology: 2.6 mm). The sensitivity to detect clear margins using ex-vivo ultrasound was low (48%). If an ex-vivo ultrasound cutoff of ≥7.5 mm would be used, the sensitivity would increase to 86%.

CONCLUSIONS

Ultrasound-guided resection of BMSCC's is feasible. In- and ex-vivo ultrasound measure tumor thickness in BMSCC accurately. We recommend ≥7.5 mm resection margins on ex-vivo ultrasound to obtain histological clear margins. Additional research is required to establish the effect of 7.5 mm ultrasound cutoff.