Intraoperative Imaging Techniques to Improve Surgical Resection Margins of Oropharyngeal Squamous Cell Cancer: A Comprehensive Review of Current Literature

Application of Targeted Optical Coherence Tomography in Oral Cancer: A Cross-Sectional Preliminary Study

BACKGROUND/OBJECTIVES

The diagnosis of oral potentially malignant disorders (OPMDs) and oral squamous cell carcinoma (OSCC) represent a significant challenge in oral medicine. Optical coherence tomography (OCT) shows promise for evaluating oral tissue microstructure but lacks standardized diagnostic protocols tailored to the structural variability and lesions of oral mucosa.

METHODS

This cross-sectional observational study aims to evaluate the diagnostic accuracy of targeted biopsy-based and site-coded OCT protocols for common OPMDs and OSCC. Adult patients clinically diagnosed with OPMDs, including oral leukoplakia (OL), oral lichen planus (OLP), and OSCC were enrolled. Clinical and OCT evaluation before and after punch scalpel-site registration preceding diagnostic biopsy on the target site was performed. Blinded observers analyzed the OCT scans for OCT-based diagnoses. Sensitivity, specificity, and diagnostic accuracy for OCT evaluations before and after punch scalpel-site registration were statistically compared with histological findings.

RESULTS

A dataset of 2520 OCT scans and 210 selected images from 21 patients was obtained. Sensitivity and specificity post-target site registration were high for OSCC (98.57%, 100.00%), OL (98.57%, 98.57%), and OLP (97.14%, 98.57%). The positive predictive values ranged from 97.14% to 100.00%, while negative predictive values ranged from 98.57% to 99.29%. Inter-observer agreements were strong for OSCC (0.84) and moderate for OL (0.54) and OLP (0.47-0.49). Targeted OCT scans significantly improved diagnostic accuracy for all conditions (p < 0.001).

CONCLUSIONS

This preliminary study supports using site-targeted OCT scans followed by a site-targeted punch biopsy, enhancing precision in oral diagnostics. This approach is foundational for developing pioneering automated algorithms guiding oral cancer and pre-cancer diagnosis via OCT imaging.

Imaging Modalities for Head and Neck Cancer: Present and Future

Several imaging modalities are utilized in the diagnosis, treatment, and surveillance of head and neck cancer. First-line imaging remains computed tomography (CT); however, MRI, PET with CT (PET/CT), and ultrasound are often used. In the last decade, several new imaging modalities have been developed that have the potential to improve early detection, modify treatment, decrease treatment morbidity, and augment surveillance. Among these, molecular imaging, lymph node mapping, and adjustments to endoscopic techniques are promising. The present review focuses on existing imaging, novel techniques, and the recent changes to imaging practices within the field.

Immunotherapeutic advances in glioma management: The rise of vaccine-based approaches

BACKGROUND

Gliomas, particularly glioblastoma multiforme (GBM), are highly aggressive brain tumors that present significant challenges in oncology due to their rapid progression and resistance to conventional therapies. Despite advancements in treatment, the prognosis for patients with GBM remains poor, necessitating the exploration of novel therapeutic approaches. One such emerging strategy is the development of glioma vaccines, which aim to stimulate the immune system to target and destroy tumor cells.

AIMS

This review aims to provide a comprehensive evaluation of the current landscape of glioma vaccine development, analyzing the types of vaccines under investigation, the outcomes of clinical trials, and the challenges and opportunities associated with their implementation. The goal is to highlight the potential of glioma vaccines in advancing more effective and personalized treatments for glioma patients.

MATERIALS AND METHODS

This narrative review systematically assessed the role of glioma vaccines by including full-text articles published between 2000 and 2024 in English. Databases such as PubMed/MEDLINE, EMBASE, the Cochrane Library, and Scopus were searched using key terms like "glioma," "brain tumor," "glioblastoma," "vaccine," and "immunotherapy." The review incorporated both pre-clinical and clinical studies, including descriptive studies, animal-model studies, cohort studies, and observational studies. Exclusion criteria were applied to omit abstracts, case reports, posters, and non-peer-reviewed studies, ensuring the inclusion of high-quality evidence.

RESULTS

Clinical trials investigating various glioma vaccines, including peptide-based, DNA/RNA-based, whole-cell, and dendritic-cell vaccines, have shown promising results. These vaccines demonstrated potential in extending survival rates and managing adverse events in glioma patients. However, significant challenges remain, such as therapeutic resistance due to tumor heterogeneity and immune evasion mechanisms. Moreover, the lack of standardized guidelines for evaluating vaccine responses and issues related to ethical considerations, regulatory hurdles, and vaccine acceptance among patients further complicate the implementation of glioma vaccines.

DISCUSSION

Addressing the challenges associated with glioma vaccines involves exploring combination therapies, targeted approaches, and personalized medicine. Combining vaccines with traditional therapies like radiotherapy or chemotherapy may enhance efficacy by boosting the immune system's ability to fight tumor cells. Personalized vaccines tailored to individual patient profiles present an opportunity for improved outcomes. Furthermore, global collaboration and equitable distribution are critical for ensuring access to glioma vaccines, especially in low- and middle-income countries with limited healthcare resources CONCLUSION: Glioma vaccines represent a promising avenue in the fight against gliomas, offering hope for improving patient outcomes in a disease that is notoriously difficult to treat. Despite the challenges, continued research and the development of innovative strategies, including combination therapies and personalized approaches, are essential for overcoming current barriers and transforming the treatment landscape for glioma patients.

Real-Time Laryngeal Cancer Boundaries Delineation on White Light and Narrow-Band Imaging Laryngoscopy with Deep Learning

OBJECTIVE

To investigate the potential of deep learning for automatically delineating (segmenting) laryngeal cancer superficial extent on endoscopic images and videos.

METHODS

A retrospective study was conducted extracting and annotating white light (WL) and Narrow-Band Imaging (NBI) frames to train a segmentation model (SegMENT-Plus). Two external datasets were used for validation. The model's performances were compared with those of two otolaryngology residents. In addition, the model was tested on real intraoperative laryngoscopy videos.

RESULTS

A total of 3933 images of laryngeal cancer from 557 patients were used. The model achieved the following median values (interquartile range): Dice Similarity Coefficient (DSC) = 0.83 (0.70-0.90), Intersection over Union (IoU) = 0.83 (0.73-0.90), Accuracy = 0.97 (0.95-0.99), Inference Speed = 25.6 (25.1-26.1) frames per second. The external testing cohorts comprised 156 and 200 images. SegMENT-Plus performed similarly on all three datasets for DSC (p = 0.05) and IoU (p = 0.07). No significant differences were noticed when separately analyzing WL and NBI test images on DSC (p = 0.06) and IoU (p = 0.78) and when analyzing the model versus the two residents on DSC (p = 0.06) and IoU (Senior vs. SegMENT-Plus, p = 0.13; Junior vs. SegMENT-Plus, p = 1.00). The model was then tested on real intraoperative laryngoscopy videos.

CONCLUSION

SegMENT-Plus can accurately delineate laryngeal cancer boundaries in endoscopic images, with performances equal to those of two otolaryngology residents. The results on the two external datasets demonstrate excellent generalization capabilities. The computation speed of the model allowed its application on videolaryngoscopies simulating real-time use. Clinical trials are needed to evaluate the role of this technology in surgical practice and resection margin improvement.

LEVEL OF EVIDENCE

III Laryngoscope, 134:2826-2834, 2024.

Hyperspectral imaging and evaluation of surgical margins: where do we stand?

PURPOSE OF REVIEW

To highlight the recent literature on the use of hyperspectral imaging (HSI) for cancer margin evaluation ex vivo, for head and neck cancer pathology and in vivo during head and neck cancer surgery.

RECENT FINDINGS

HSI can be used ex vivo on unstained and stained tissue sections to analyze head and neck tissue and tumor cells in combination with machine learning approaches to analyze head and neck cancer cell characteristics and to discriminate the tumor border from normal tissue. Data on in vivo applications during head and neck cancer surgery are preliminary and limited. Even now an accuracy of 80% for tumor versus nonneoplastic tissue classification can be achieved for certain tasks, within the current in vivo settings.

SUMMARY

Significant progress has been made to introduce HSI for ex vivo head and neck cancer pathology evaluation and for an intraoperative use to define the tumor margins. To optimize the accuracy for in vivo use, larger HSI databases with annotations for head and neck cancer are needed.

Transoral robotic surgery without adjuvant therapy: A systematic review and meta-analysis of the association between surgical margins and local recurrence

BACKGROUND

Transoral robotic surgery (TORS) is increasingly employed in the management of oropharyngeal cancer without adjuvant treatment. Attaining safe surgical margins is paramount to preventing local recurrence (LR), but the necessary surgical margin dimension remains contentious.

METHODS

Systematic review and meta-analysis of studies reporting margin status and LR following TORS without adjuvant therapy for primary OPSCC.

RESULTS

The search identified 269 articles and 11 were selected for inclusion, with 406 patients included in the meta-analysis. Heterogeneity was noted in the definition of "close" margins. Random-effects pooled rate of positive margins was 7 % (95 % CI 0.04-0.12, I2 = 54 %, p = 0.02) and close margins was 7 % (95 % CI 0.02-0.27, I2 = 86 %, p=<0.01). The random-effects overall rate of LR was 6 % (95 % CI 0.04-0.10, I2 = 11 %, p = 0.35), 13 % (95 % CI 0.02-0.620, I2 = 0 %, p = 1.0) after a positive margin, and 3 % (95 % CI 0.03-0.24, I2 = 23 %, p = 0.26) after a close margin. Odds ratio (OR) for LR indicated higher risk of LR for positive compared to close margins (7.5; 95 % CI 1.31-42.91, I2 = 0 %, p = 0.51), and a slightly lower risk of LR between close and negative margins (2.22; 95 % CI 0.67-7.38, I2 = 0 %, p = 0.8). A lack of frozen-section analysis (OR 2.91, p = 0.36) and HPV-negative disease (OR 1.68, p = 0.03) were associated with an elevated risk of LR.

CONCLUSIONS

TORS as a standalone treatment is associated with low rates of LR; however, the literature is hampered by considerable heterogeneity in margin definitions. Larger multicentre studies are required to determine the precise margin cut-off required for oropharyngeal tumours managed with TORS alone.

Translating Biospectroscopy Techniques to Clinical Settings: A New Paradigm in Point-of-Care Screening and/or Diagnostics

As healthcare tools increasingly move towards a more digital and computational format, there is an increasing need for sensor-based technologies that allow for rapid screening and/or diagnostics [...].

3D Ultrasound and MRI in Assessing Resection Margins during Tongue Cancer Surgery: A Research Protocol for a Clinical Diagnostic Accuracy Study

Surgery is the primary treatment for tongue cancer. The goal is a complete resection of the tumor with an adequate margin of healthy tissue around the tumor.Inadequate margins lead to a high risk of local cancer recurrence and the need for adjuvant therapies. Ex vivo imaging of the resected surgical specimen has been suggested for margin assessment and improved surgical results. Therefore, we have developed a novel three-dimensional (3D) ultrasound imaging technique to improve the assessment of resection margins during surgery. In this research protocol, we describe a study comparing the accuracy of 3D ultrasound, magnetic resonance imaging (MRI), and clinical examination of the surgical specimen to assess the resection margins during cancer surgery. Tumor segmentation and margin measurement will be performed using 3D ultrasound and MRI of the ex vivo specimen. We will determine the accuracy of each method by comparing the margin measurements and the proportion of correctly classified margins (positive, close, and free) obtained by each technique with respect to the gold standard histopathology.