Assessment of tumor margins in head and neck cancer using a 3D-navigation system based on PET/CT image-fusion - A pilot study

Deep learning-based multimodal CT/MRI image fusion and segmentation strategies for surgical planning of oral and maxillofacial tumors: A pilot study

PURPOSE

This pilot study aims to evaluate the feasibility and accuracy of deep learning-based multimodal computed tomography/magnetic resonance imaging (CT/MRI) fusion and segmentation strategies for the surgical planning of oral and maxillofacial tumors.

MATERIALS AND METHODS

This study enrolled 30 oral and maxillofacial tumor patients visiting our department between 2016 and 2022. All patients underwent enhanced CT and MRI scanning of the oral and maxillofacial region. Furthermore, three fusion models (Elastix, ANTs, and NiftyReg) and three segmentation models (nnU-Net, 3D UX-Net, and U-Net) were combined to generate nine hybrid deep learning models that were trained. The performance of each model was evaluated via the Fusion Index (FI), Dice similarity coefficient (Dice), 95th-percentile Hausdorff distance (HD95), mean surface distance (MSD), precision, and recall analysis.

RESULTS

All three image fusion models (Elastix, ANTs, and NiftyReg) demonstrated satisfactory accuracy, with Elastix exhibiting the best performance. Among the tested segmentation models, the highest degree of accuracy for segmenting the maxilla and mandible was achieved by combining NiftyReg and nnU-Net. Furthermore, the highest overall accuracy of the nine hybrid models was observed with the Elastix and nnU-Net combination, which yielded a Dice coefficient of 0.89 for tumor segmentation.

CONCLUSION

In this study, deep learning models capable of automatic multimodal CT/MRI image fusion and segmentation of oral and maxillofacial tumors were successfully trained with a high degree of accuracy. The results demonstrated the feasibility of using deep learning-based image fusion and segmentation to establish a basis for virtual surgical planning.

Surgical margins in head and neck squamous cell carcinoma: A narrative review

Head and neck squamous cell carcinoma (HNSCC), a prevalent and frequently recurring malignancy, often necessitates surgical intervention. The surgical margin (SM) plays a pivotal role in determining the postoperative treatment strategy and prognostic evaluation of HNSCC. Nonetheless, the process of clinical appraisal and assessment of the SMs remains a complex and indeterminate endeavor, thereby leading to potential difficulties for surgeons in defining the extent of resection. In this regard, we undertake a comprehensive review of the suggested surgical distance in varying circumstances, diverse methods of margin evaluation, and the delicate balance that must be maintained between tissue resection and preservation in head and neck surgical procedures. This review is intended to provide surgeons with pragmatic guidance in selecting the most suitable resection techniques, and in improving patients' quality of life by achieving optimal functional and aesthetic restoration.

Factors influencing the accuracy of multimodal image fusion for oral and maxillofacial tumors: a retrospective study

BACKGROUND

Ensuring high accuracy in multimodal image fusion for oral and maxillofacial tumors is crucial before further application. The aim of this study was to explore the factors influencing the accuracy of multimodal image fusion for oral and maxillofacial tumors.

METHODS

Pairs of single-modality images were obtained from oral and maxillofacial tumor patients, and were fused using a proprietary navigation system by using three algorithms (automatic fusion, manual fusion, and registration point-based fusion). Fusion accuracy was evaluated including two aspects-overall fusion accuracy and tumor volume fusion accuracy-and were indicated by mean deviation and fusion index, respectively. Image modality, fusion algorithm, and other characteristics of multimodal images that may have potential influence on fusion accuracy were recorded. Univariate and multivariate analysis were used to identify relevant affecting factors.

RESULTS

Ninety-three multimodal images were generated by fusing 31 pairs of single-modality images. The interaction effect of image modality and fusion algorithm (P = 0.02, P = 0.003) and thinner slice thickness (P = 0.006) were shown to significantly influence the overall fusion accuracy. The tumor volume (P < 0.001), tumor location (P = 0.007), and image modality (P = 0.01) were significant influencing factors for tumor volume fusion accuracy.

CONCLUSIONS

To ensure high overall fusion accuracy, manual fusion was not preferred in CT/MRI image fusion, and neither was automatic fusion in image fusion containing PET modality. Using image sets with thinner slice thickness could increase overall fusion accuracy. CT/MRI fusion yielded higher tumor volume fusion accuracy than fusion containing PET modality. The tumor volume fusion accuracy should be taken into consideration during image fusion when the tumor volume is small and the tumor is located in the mandible.

Free three-dimensional image software in local extension assessment of oral squamous cell carcinoma: a pilot study

OBJECTIVE

Oral Squamous Cell Carcinoma (OSCC) is conventionally treated by surgical resection, and positive surgical margins strongly increase local recurrence and decrease survival. This study aimed to evaluate whether a Three-Dimensional Segmentation (3DS) image of OSCC confers advantage over Multiplanar Reconstruction (MPR) of OSCC using images of computed tomography scan in surgical planning of tumor resection.

METHODS

Twenty-six patients with locally advanced OSCC had tumor morphology and dimensions evaluated by MPR images, 3DS images, and Surgical Pathology Specimen (SPS) analyses (gold standard). OSCC resection was performed with curative intent using only MPR images.

RESULTS

OSCC morphology was more accurately assessed by 3DS than by MPR images. Similar OSCC volumes and dimensions were obtained when MPR images, 3DS images and SPS measurements were considered. Nevertheless, there was a strong correlation between the OSCC longest axis measured by 3DS and SPS analyses (ICC = 0.82; 95% CI 0.59‒0.92), whereas only a moderate correlation was observed between the longest axis of OSCC measured by MPR images and SPS analyses (ICC = 0.51; 95% CI 0.09‒0.78). Taking only SPS with positive margins into account, MPR images and 3DS images underestimated the tumor's longest axis in eight out of 11 (72.7%) and 5 out of the 11 (45.5%) cases, respectively.

CONCLUSION

Our data present preliminary evidence that 3DS model represents a useful tool for surgical planning of OSCC resection, but confirmation in a larger cohort of patients is required.

LEVEL OF EVIDENCE

Laboratory study.

PET- and SPECT-based navigation strategies to advance procedural accuracy in interventional radiology and image-guided surgery

INTRODUCTION

Nuclear medicine has a crucial role in interventional strategies where a combination between the increasing use of targeted radiotracers and intraprocedural detection modalities enable novel, but often complex, targeted procedures in both the fields of interventional radiology and surgery. 3D navigation approaches could assist the interventional radiologist or surgeon in such complex procedures.

EVIDENCE ACQUISITION

This review aimed to provide a comprehensive overview of the current application of computer-assisted navigation strategies based on nuclear imaging to assist in interventional radiology and image-guided surgery. This work starts with a brief overview of the typical navigation workflow from a technical perspective, which is followed by the different clinical applications organized based on their anatomical organ of interest.

EVIDENCE SYNTHESIS

Although many studies have proven the feasibility of PET- and SPECT-based navigation strategies for various clinical applications in both interventional radiology and surgery, the strategies are spread widely in both navigation workflows and clinical indications, evaluated in small patient groups. Hence, no golden standard has yet been established.

CONCLUSIONS

Despite that the clinical outcome is yet to be determined in large patient cohorts, navigation seems to be a promising technology to translate nuclear medicine findings, provided by PET- and SPECT-based molecular imaging, to the intervention and operating room. Interventional Nuclear Medicine (iNM) has an exciting future to come using both PET- and SPECT-based navigation.

Imaging-based navigation technologies in head and neck surgery

PURPOSE OF REVIEW

Image guided navigation has had significant impact in head and neck surgery, and has been most prolific in endonasal surgeries. Although conventional image guidance involves static computed tomography (CT) images attained in the preoperative setting, the continual evolution of surgical navigation technologies is fast expanding to incorporate both real-time data and bioinformation that allows for improved precision in surgical guidance. With the rapid advances in technologies, this article allows for a timely review of the current and developing techniques in surgical navigation for head and neck surgery.

RECENT FINDINGS

Current advances for cross-sectional-based image-guided surgery include fusion of CT with other imaging modalities (e.g., magnetic resonance imaging and positron emission tomography) as well as the uptake in intraoperative real-time 'on the table' imaging (e.g., cone-beam CT). These advances, together with the integration of virtual/augmented reality, enable potential enhancements in surgical navigation. In addition to the advances in radiological imaging, the development of optical modalities such as fluorescence and spectroscopy techniques further allows the assimilation of biological data to improve navigation particularly for head and neck surgery.

SUMMARY

The steady development of radiological and optical imaging techniques shows great promise in changing the paradigm of head and neck surgery.

Accuracy of multimodal image fusion for oral and maxillofacial tumors: A revised evaluation method and its application

OBJECTIVE

To develop a revised evaluation method for accuracy of multimodal image fusion for oral and maxillofacial tumors and explore its application for comparing the accuracy of three commonly used fusion algorithms, automatic fusion, manual fusion, and registration point-based fusion.

MATERIALS AND METHODS

Image sets of patients with oral and maxillofacial tumor were fused using the iPlan 3.0 navigation system. Fusion accuracy included two aspects: (1) overall fusion accuracy: represented by the mean value of the coordinate differences along the x-, y-, and z- axes (Δx, Δy, and Δz), mean deviation (MD), and root mean square (RMS) of six pairs of landmarks on the two image sets; (2) tumor volume fusion accuracy: represented by Fusion Index (FI), which was calculated based on the volume of tumor delineated on the two image sets.

RESULTS

Eighteen pairs of image sets of 17 patients were enrolled in this study. The Δx and Δy values for the three algorithms were less than 1.5 mm. The Δz values for automatic fusion, manual fusion and registration point-based fusion was 1.049 mm, 1.864 mm and 1.254 mm. The MD for automatic fusion, manual fusion and registration point-based fusion was 1.978 mm, 2.788 mm and 1.926 mm. Significant differences existed in Δz for manual fusion and that for automatic fusion (P = 0.058), in MD for manual fusion and that for automatic fusion (P = 0.087), and in MD for manual fusion and that for registration point-based fusion (P = 0.069). The FI for automatic fusion, manual fusion, and registration point-based fusion was 0.594, 0.520, and 0.549; the inter-algorithm differences were not significant (P = 0.290).

CONCLUSION

The automatic fusion and the registration point-based fusion were more accurate than manual fusion, and therefore were recommended to be used in multimodal image fusion for oral and maxillofacial tumors.

Diagnostic value of navigation-guided core needle biopsy in deep regions of the head and neck with focal FDG uptake on 18F-FDG PET/CT

PURPOSE

The aim of this study was to evaluate the feasibility and diagnostic accuracy of core needle biopsy (CNB) in patients with focal fluorodeoxyglucose (FDG) uptake on positron emission tomography/computed tomography (PET/CT) in deep regions of the head and neck, with the guidance of infrared navigation integrated with PET.

MATERIALS AND METHODS

Patients with suspected primary or recurrent malignancies of the head and neck on PET/CT, from June 2016 to December 2018, were included. Before CNB, the region of interest was delineated and the ideal needle entry points, target sites, and a number of trajectories were designed on iPlan CMF 3.0. CNB was performed with the guidance of infrared navigation integrated with PET, according to the pre-plan. Sensitivity and diagnostic accuracy were analyzed by comparing the biopsy results with the final diagnosis.

RESULTS

Thirty-one consecutive patients were included. Among the 31 lesions, 18 were skull base, six were infratemporal fossa, and seven were maxillary region. The median values for SUVmax, SUVmean, and MTV were 6.09 (range: 1.43-24.67), 3.41 (range: 0.38-20.96), and 25.83 (range: 3.54-361.94) for the 31 lesions, respectively. Combined needle approaches were employed, including temporal (nine), subzygomatic (19), paramaxillary (11), and retromandibular (16) approaches. The depths of the 31 deep-region lesions, measured from the needle entry site on the skin to the target point, ranged from 1.33 cm to 7.82 cm (median 4.25 cm). There were three non-diagnostic lesions resulting from CNB, and these were all skull base. The diagnostic accuracy was 90.3%, while the sensitivity was 88%. According to the binary logistic regression for the final diagnosis, the only significant parameter was SUVmax.

CONCLUSION

With the guidance of navigation integrated with PET, CNB is a feasible and accurate diagnostic modality, which is also an alternative to open biopsy in patients with suspected primary or recurrent malignancies in deep regions of the head and neck on PET/CT.

Navigation-guided resection of maxillary tumors: Can a new volumetric virtual planning method improve outcomes in terms of control of resection margins?

INTRODUCTION

In the present study, our aim was to confirm the role of navigation-guided surgery in reducing the percentage of positive margins in advanced malignant pathologies of the mid-face, by introducing a new volumetric virtual planning method for resection.

MATERIALS AND METHODS

Twenty-eight patients were included in this study. Eighteen patients requiring surgery to treat malignant midface tumors were prospectively selected and stratified into two different study groups. Patients enrolled in the Reference Points Resection group (RPR - 10 patients) underwent resection planning using the anatomical landmarks on CT scan; patients enrolled in the Volume Resection group (VR - 8 patients) underwent resection using the new volumetric virtual planning method. The remaining 10 patients (Control group) were treated without the use of a navigation system.

RESULTS

In total, 127 margins were pathologically assessed in the RPR group, 75 in the VR group, and 85 in the control group. In the control group, 16% of the margins were positive, while in the RPR group the value was 9%, and in the VR group 1%.

CONCLUSIONS

The volumetric tumor resection planning associated to the navigation-guide resection appeared to be an improvement in terms of control of surgical margins in advanced tumors involving the mid-face.