Calculating Tumor Volume Using Three-Dimensional Models in Preoperative Soft-Tissue Sarcoma Surgical Planning: Does Size Matter?

This feasibility study aims to explore the use of three-dimensional virtual surgical planning to preoperatively determine the need for reconstructive surgery following resection of an extremity soft-tissue sarcoma. As flap reconstruction is performed more often in advanced disease, we hypothesized that tumor volume would be larger in the group of patients that had undergone flap reconstruction. All patients that were treated by surgical resection for an extremity soft-tissue sarcoma between 1 January 2016 and 1 October 2019 in the University Medical Center Groningen were included retrospectively. Three-dimensional models were created using the diagnostic magnetic resonance scan. Tumor volume was calculated for all patients. Three-dimensional tumor volume was 107.8 (349.1) mL in the group of patients that had undergone primary closure and 29.4 (47.4) mL in the group of patients in which a flap reconstruction was performed, p = 0.004. Three-dimensional tumor volume was 76.1 (295.3) mL in the group of patients with a complication following ESTS treatment, versus 57.0 (132.4) mL in patients with an uncomplicated course following ESTS treatment, p = 0.311. Patients who had undergone flap reconstruction had smaller tumor volumes compared to those in the group of patients treated by primary closure. Furthermore, a larger tumor volume did not result in complications for patients undergoing ESTS treatment. Therefore, tumor volume does not seem to influence the need for reconstruction. Despite the capability of three-dimensional virtual surgical planning to measure tumor volume, we do not recommend its utilization in the multidisciplinary extremity soft-tissue sarcoma treatment, considering the findings of the study.

Three-Dimensional Evaluation of Isodose Radiation Volumes in Cases of Severe Mandibular Osteoradionecrosis for the Prediction of Recurrence after Segmental Resection.

BACKGROUND: Pre-operative margin planning for the segmental resection of affected bone in mandibular osteoradionecrosis (ORN) is difficult. The aim of this study was to identify a possible relation between the received RT dose, exposed bone volume and the progression of ORN after segmental mandibular resection. METHOD: Patients diagnosed with grade 3-4 ORN for which a segmental resection was performed were included in the study. Three-dimensional reconstructions of RT isodose volumes were fused with postoperative imaging. The primary outcome was the recurrence of ORN after segmental resection. Subsequently, RT exposed mandibular bone volumes were calculated and the location of the bone cuts relative to the isodose volumes were assessed. RESULTS: Five out of thirty-three patients developed recurrent ORN after segmental mandibular resection. All cases with recurrent ORN were resected inside an isodose volume of ≥56 Gy. The absolute mandibular volume radiated with 56 Gy was significantly smaller in the recurrent group (10.9 mL vs. 30.7 mL, p = 0.006), as was the proportion of the mandible radiated with 56 Gy (23% vs. 45%, p = 0.013). CONCLUSION: The volume of radiated bone was not predictive for risk of progression. The finding that recurrent ORN occurred with bone resection margins within the 56 Gy isodose volume suggests that this could serve as a starting point for the pre-operative planning of reducing the risk of ORN recurrence.

Three-Dimensional Guided Zygomatic Implant Placement after Maxillectomy.

Zygomatic implants are used in patients with maxillary defects to improve the retention and stability of obturator prostheses, thereby securing good oral function. Prosthetic-driven placement of zygomatic implants is even difficult for experienced surgeons, and with a free-hand approach, deviation from the preplanned implant positions is inevitable, thereby impeding immediate implant-retained obturation. A novel, digitalized workflow of surgical planning was used in 10 patients. Maxillectomy was performed with 3D-printed cutting, and drill guides were used for subsequent placement of zygomatic implants with immediate placement of implant-retained obturator prosthesis. The outcome parameters were the accuracy of implant positioning and the prosthetic fit of the obturator prosthesis in this one-stage procedure. Zygomatic implants (n = 28) were placed with good accuracy (mean deviation 1.73 ± 0.57 mm and 2.97 ± 1.38° 3D angle deviation), and in all cases, the obturator prosthesis fitted as pre-operatively planned. The 3D accuracy of the abutment positions was 1.58 ± 1.66 mm. The accuracy of the abutment position in the occlusal plane was 2.21 ± 1.33 mm, with a height accuracy of 1.32 ± 1.57 mm. This feasibility study shows that the application of these novel designed 3D-printed surgical guides results in predictable zygomatic implant placement and provides the possibility of immediate prosthetic rehabilitation in head and neck oncology patients after maxillectomy.

Three-dimensional virtual surgical planning in the oncologic treatment of the mandible.

OBJECTIVES: In case of surgical removal of oral squamous cell carcinomas, a resection of mandibular bone is frequently part of the treatment. Nowadays, such resections frequently include the application of 3D virtual surgical planning (VSP) and guided surgery techniques. In this paper, current methods for 3D VSP leads for optimisation of the workflow, and patient-specific application of guides and implants are reviewed. RECENT FINDINGS: Current methods for 3D VSP enable multi-modality fusion of images. This fusion of images is not restricted to a specific software package or workflow. New strategies for 3D VSP in Oral and Maxillofacial Surgery include finite element analysis, deep learning and advanced augmented reality techniques. These strategies aim to improve the treatment in terms of accuracy, predictability and safety. CONCLUSIONS: Application of the discussed novel technologies and strategies will improve the accuracy and safety of mandibular resection and reconstruction planning. Accurate, easy-to-use, safe and efficient three-dimensional VSP can be applied for every patient with malignancies needing resection of the mandible.

Patient-specific finite element models of the human mandible: Lack of consensus on current set-ups.

The use of finite element analysis (FEA) has increased rapidly over the last decennia and has become a popular tool to design implants, osteosynthesis plates and prostheses. With increasing computer capacity and the availability of software applications, it has become easier to employ the FEA. However, there seems to be no consensus on the input variables that should be applied to representative FEA models of the human mandible. This review aims to find a consensus on how to define the representative input factors for a FEA model of the human mandible. A literature search carried out in the PubMed and Embase database resulted in 137 matches. Seven papers were included in this current study. Within the search results, only a few FEA models had been validated. The material properties and FEA approaches varied considerably, and the available validations are not strong enough for a general consensus. Further validations are required, preferably using the same measuring workflow to obtain insight into the broad array of mandibular variations. A lot of work is still required to establish validated FEA settings and to prevent assumptions when it comes to FEA applications.

The use of 3D virtual surgical planning and computer aided design in reconstruction of maxillary surgical defects.

PURPOSE OF REVIEW: The present review describes the latest development of 3D virtual surgical planning (VSP) and computer aided design (CAD) for reconstruction of maxillary defects with an aim of fully prosthetic rehabilitation. The purpose is to give an overview of different methods that use CAD in maxillary reconstruction in patients with head and neck cancer. RECENT FINDINGS: 3D VSP enables preoperative planning of resection margins and osteotomies. The current 3D VSP workflow is expanded with multimodal imaging, merging decision supportive information. Development of more personalized implants is possible using CAD, individualized virtual muscle modelling and topology optimization. Meanwhile the translation of the 3D VSP towards surgery is improved by techniques like intraoperative imaging and augmented reality. Recent improvements of preoperative 3D VSP enables surgical reconstruction and/or prosthetic rehabilitation of the surgical defect in one combined procedure. SUMMARY: With the use of 3D VSP and CAD, ablation surgery, reconstructive surgery, and prosthetic rehabilitation can be planned preoperatively. Many reconstruction possibilities exist and a choice depends on patient characteristics, tumour location and experience of the surgeon. The overall objective in patients with maxillary defects is to follow a prosthetic-driven reconstruction with the aim to restore facial form, oral function, and do so in accordance with the individual needs of the patient.

Automatic segmentation of the mandible from computed tomography scans for 3D virtual surgical planning using the convolutional neural network.

Segmentation of mandibular bone in CT scans is crucial for 3D virtual surgical planning of craniofacial tumor resection and free flap reconstruction of the resection defect, in order to obtain a detailed surface representation of the bones. A major drawback of most existing mandibular segmentation methods is that they require a large amount of expert knowledge for manual or partially automatic segmentation. In fact, due to the lack of experienced doctors and experts, high quality expert knowledge is hard to achieve in practice. Furthermore, segmentation of mandibles in CT scans is influenced seriously by metal artifacts and large variations in their shape and size among individuals. In order to address these challenges we propose an automatic mandible segmentation approach in CT scans, which considers the continuum of anatomical structures through different planes. The approach adopts the architecture of the U-Net and then combines the resulting 2D segmentations from three orthogonal planes into a 3D segmentation. We implement such a segmentation approach on two head and neck datasets and then evaluate the performance. Experimental results show that our proposed approach for mandible segmentation in CT scans exhibits high accuracy.