Is the prediction of one or two ipsilateral positive lymph nodes by computerized tomography and ultrasound reliable enough to restrict therapeutic neck dissection in oral squamous cell carcinoma (OSCC) patients?

Enhanced Diagnostic Precision: Assessing Tumor Differentiation in Head and Neck Squamous Cell Carcinoma Using Multi-Slice Spiral CT Texture Analysis

This study explores the efficacy of texture analysis by using preoperative multi-slice spiral computed tomography (MSCT) to non-invasively determine the grade of cellular differentiation in head and neck squamous cell carcinoma (HNSCC). In a retrospective study, MSCT scans of patients with HNSCC were analyzed and classified based on its histological grade as moderately differentiated, well-differentiated, or poorly differentiated. The location of the tumor was categorized as either in the bone or in soft tissues. Segmentation of the lesion areas was conducted, followed by texture analysis. Eleven GLCM parameters across five different distances were calculated. Median values and correlations of texture parameters were examined in relation to tumor differentiation grade by using Spearman's correlation coefficient and Kruskal-Wallis and Dunn tests. Forty-six patients were included, predominantly female (87%), with a mean age of 66.7 years. Texture analysis revealed significant parameter correlations with histopathological grades of tumor differentiation. The study identified no significant age correlation with tumor differentiation, which underscores the potential of texture analysis as an age-independent biomarker. The strong correlations between texture parameters and histopathological grades support the integration of this technique into the clinical decision-making process.

Application of CT and MRI images based on artificial intelligence to predict lymph node metastases in patients with oral squamous cell carcinoma: a subgroup meta-analysis

Background

The performance of artificial intelligence (AI) in the prediction of lymph node (LN) metastasis in patients with oral squamous cell carcinoma (OSCC) has not been quantitatively evaluated. The purpose of this study was to conduct a systematic review and meta-analysis of published data on the diagnostic performance of CT and MRI based on AI algorithms for predicting LN metastases in patients with OSCC.

Methods

We searched the Embase, PubMed (Medline), Web of Science, and Cochrane databases for studies on the use of AI in predicting LN metastasis in OSCC. Binary diagnostic accuracy data were extracted to obtain the outcomes of interest, namely, the area under the curve (AUC), sensitivity, and specificity, and compared the diagnostic performance of AI with that of radiologists. Subgroup analyses were performed with regard to different types of AI algorithms and imaging modalities.

Results

Fourteen eligible studies were included in the meta-analysis. The AUC, sensitivity, and specificity of the AI models for the diagnosis of LN metastases were 0.92 (95% CI 0.89-0.94), 0.79 (95% CI 0.72-0.85), and 0.90 (95% CI 0.86-0.93), respectively. Promising diagnostic performance was observed in the subgroup analyses based on algorithm types [machine learning (ML) or deep learning (DL)] and imaging modalities (CT vs. MRI). The pooled diagnostic performance of AI was significantly better than that of experienced radiologists.

Discussion

In conclusion, AI based on CT and MRI imaging has good diagnostic accuracy in predicting LN metastasis in patients with OSCC and thus has the potential for clinical application.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/#recordDetails, PROSPERO (No. CRD42024506159).

Intraoperative Ultrasound for the Management of Oral Tongue Cancer: a Systematic Review and Meta-Analysis

Objective

To evaluate for correlation between intraoperative ultrasound (IOUS)-measured tumor thickness (TT) (uTT) and histopathological TT (hTT), and to compare IOUS-assisted resection with conventional resection in patients with oral tongue cancers.

Data Sources

Ovid MEDLINE (1946-2023), Embase.com (1947-2023), and Web of Science (All Databases 1900-2023).

Review Methods

Inclusion criteria were the use of IOUS for the management of oral tongue cancer. Studies that did not report quantitative data were excluded. Additionally, studies that were not contributory to meta-analysis, or a narrative analysis of pooled results were excluded. Selection was carried out by 2 reviewers. A total of 2417 studies were initially identified, with 12 ultimately being included in this review, and 7 included in the meta-analysis. Data were extracted by 2 investigators and were pooled using a random-effects model.

Results

Our meta-analysis reveals a pooled correlation coefficient of 0.92 (95% confidence interval: 0.80-0.96) for studies comparing uTT to hTT. Studies comparing IOUS-assisted resection to conventional resection found IOUS-assisted resection yielded wider nearest margins in all studies reporting this outcome.

Conclusion

IOUS reliably measures TT, similarly to that of histopathology measurement. IOUS-assisted resection, which allows the surgeon to view the deep extent of tumor invasion, may increase closest radial margin distance compared to conventional resection. IOUS-assisted resection may represent a more reliable approach to achieving clear margins than conventional resection.

Comparative analysis of diagnostic ultrasound and histopathology for detecting cervical lymph node metastases in head and neck cancer

PURPOSE

We evaluated the current performance of diagnostic ultrasound (US) for detecting cervical lymph node (LN) metastases based on objective measures and subjective findings in comparison to the gold standard, histopathological evaluation.

PATIENTS AND METHODS

From 2007 to 2016, we prospectively included patients with head and neck cancer who were scheduled for surgical therapy including neck dissection. LNs were examined by multimodal US by a level III head and neck sonologist and individually assigned to a map containing six AAO-HNS neck LN levels preoperatively. During the operation, LNs were dissected and then assessed by routine histopathology, with 86% of them examined individually and the remaining LNs (14%) per AAO-HNS neck LN level. The optimal cutoff points (OCPs) of four defined LN diameters and 2D and 3D roundness indices per AAO-HNS neck LN level were determined.

RESULTS

In total, 235 patients were included, and 4539 LNs were analyzed by US, 7237 by histopathology and 2684 by both methods. Of these, 259 (9.65%) were classified as suspicious for metastasis by US, whereas 299 (11.14%) were found to be positive by histopathology. Subjective US sensitivity and specificity were 0.79 and 0.99, respectively. The OCPs of the individual LN diameters and the 2D and 3D roundness index were determined individually for all AAO-HNS neck LN levels. Across all levels, the OCP for the 2D index was 1.79 and the 3D index was 14.97. The predictive performance of all distances, indices, and subjective findings improved with increasing metastasis size. Anticipation of pN stage was best achieved with subjective US findings and the smallest diameter (Cohen's κ = 0.713 and 0.438, respectively).

CONCLUSION

Our LN mapping and meticulous 1:1 node-by-node comparison reveals the usefulness of US for detecting metastatic involvement of neck LNs in head and neck carcinomas as compared to histopathology. The predictive ability for small tumor deposits less than 8 mm in size remains weak and urgently needs improvement.

The role of magnetic resonance imaging and computed tomography in oral squamous cell carcinoma patients' preoperative staging

INTRODUCTION

The aim of the study was to evaluate the accuracy of MRI and CT with regard to the detection of lymph node metastases based on the data of specific patients with OSCC who received bilateral neck dissection.

MATERIALS AND METHODS

In a retrospective analysis from 01/2014 to 12/2020 patients who underwent primary tumor resection and bilateral neck dissection were evaluated.

RESULTS

174 preoperative MRI (78.74%, N=137) and CT (21.26%, N=37) were correlated with the histopathological findings. CT had a sensitivity of 67% and specificity of 68% (p=0.76). MRI showed an overall sensitivity of 66% and a specificity of 68% (p=0.76). In 52.87% of all cases no differences between cN and pN were found. MRI is the method to overestimate lymph node involvement compared to CT (overestimation in 27% vs. 21.62%).

CONCLUSION

The current data indicate that MR and CT show poor efficacy in the detection of cervical metastases. Accordingly, attention must be paid to alternatives to correct local staging modalities. The application of structured bilateral neck dissection needs to be questioned.

The Applications and Potential Developments of Ultrasound in Oral Cancer Management

Oral cancer is endemic and causes a great burden in Southern Asia. It is preferably treated by surgery with/without adjuvant radiotherapy (RT) or chemoradiation therapy, depending on the stage of the disease. Close or positive resection margin and cervical lymph node (LN) metastasis are important prognostic factors that have been presented to be related to undesirable locoregional recurrence and poor survival. Ultrasound (US) is a simple, noninvasive, time-saving, and inexpensive diagnostic modality. It can depict soft tissues very clearly without the risk of radiation exposure. Additionally, it is real-time and continuous image is demonstrated during the exam. Furthermore, the clinician can perform US-guided fine needle aspiration (FNA) or core needle biopsy (CNB) at the same time. US with/without US-guided FNA/CNB is reported to be of value in determining tumor thickness (TT), depth of invasion (DOI), and cervical LN metastasis, and in aiding the staging of oral cancer. DOI has a relevant prognostic value as reported in the eighth edition of the American Joint Committee on Cancer staging of oral cancer. In the present review, we describe the clinical applications of US in oral cancer management in different phases and potential applications in the future. In the pretreatment and surgical phase, US can be used to evaluate TT/DOI and surgical margins of oral cancer in vivo and ex vivo. The prediction of a malignant cervical LN (nodal metastasis) by the US-based prediction model can guide the necessity of FNA/CNB and elective neck dissection in clinical early-stage oral cancer. In the posttreatment surveillance phase, US with/without US-guided FNA or CNB is helpful in the detection of nodal persistence or LN recurrence, and can assess the possibility and extent of carotid artery stenosis after irradiation therapy. Both US elastography and US swallowing assessment are potentially helpful to the management of oral cancer.