Research

13 pages, 1170 KiB

Open AccessArticle

Preoperative Prediction of Optimal Femoral Implant Size by Regularized Regression on 3D Femoral Bone Shape

by Adriaan Lambrechts, Christophe Van Dijck, Roel Wirix-Speetjens, Jos Vander Sloten, Frederik Maes and Sabine Van Huffel

Appl. Sci. 2023, 13(7), 4344; https://doi.org/10.3390/app13074344 - 29 Mar 2023

Viewed by 906

Abstract

Preoperative determination of implant size for total knee arthroplasty surgery has numerous clinical and logistical benefits. Currently, surgeons use X-ray-based templating to estimate implant size, but this method has low accuracy. Our study aims to improve accuracy by developing a machine learning approach [...] Read more.

Preoperative determination of implant size for total knee arthroplasty surgery has numerous clinical and logistical benefits. Currently, surgeons use X-ray-based templating to estimate implant size, but this method has low accuracy. Our study aims to improve accuracy by developing a machine learning approach that predicts the required implant size based on a 3D femoral bone mesh, the key factor in determining the correct implant size. A linear regression framework imposing group sparsity on the 3D bone mesh vertex coordinates was proposed based on a dataset of 446 MRI scans. The group sparse regression method was further regularized based on the connectivity of the bone mesh to enforce neighbouring vertices to have similar importance to the model. Our hypergraph regularized group lasso had an accuracy of 70.1% in predicting femoral implant size while the initial implant size prediction provided by the instrumentation manufacturer to the surgeon has an accuracy of 23.1%. Furthermore, our method was capable of predicting the implant size up to one size smaller or larger with an accuracy of 99.1%, thereby surpassing other state-of-the-art methods. The hypergraph regularized group lasso was able to obtain a significantly higher accuracy compared to the implant size prediction provided by the instrumentation manufacturer. Full article

(This article belongs to the Special Issue Novel Advances in Computer-Assisted Surgery)

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17 pages, 6288 KiB

Open AccessArticle

Surgical Tool Detection in Open Surgery Videos

by Ryo Fujii, Ryo Hachiuma, Hiroki Kajita and Hideo Saito

Appl. Sci. 2022, 12(20), 10473; https://doi.org/10.3390/app122010473 - 17 Oct 2022

Cited by 4 | Viewed by 2827

Abstract

Detecting surgical tools is an essential task for analyzing and evaluating surgical videos. However, most studies focus on minimally invasive surgery (MIS) and cataract surgery. Mainly because of a lack of a large, diverse, and well-annotated dataset, research in the area of open [...] Read more.

Detecting surgical tools is an essential task for analyzing and evaluating surgical videos. However, most studies focus on minimally invasive surgery (MIS) and cataract surgery. Mainly because of a lack of a large, diverse, and well-annotated dataset, research in the area of open surgery has been limited so far. Open surgery video analysis is challenging because of its properties: varied number and roles of people (e.g., main surgeon, assistant surgeons, and nurses), a complex interaction of tools and hands, various operative environments, and lighting conditions. In this paper, to handle these limitations and difficulties, we introduce an egocentric open surgery dataset that includes 15 open surgeries recorded with a head-mounted camera. More than 67k bounding boxes are labeled to 19k images with 31 surgical tool categories. Finally, we present a surgical tool detection baseline model based on recent advances in object detection. The results of our new dataset show that our presented dataset provides enough interesting challenges for future methods and that it can serve as a strong benchmark to address the study of tool detection in open surgery. Full article

(This article belongs to the Special Issue Novel Advances in Computer-Assisted Surgery)

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15 pages, 949 KiB

Open AccessArticle

Surgical Phase Recognition: From Public Datasets to Real-World Data

by Kadir Kirtac, Nizamettin Aydin, Joël L. Lavanchy, Guido Beldi, Marco Smit, Michael S. Woods and Florian Aspart

Appl. Sci. 2022, 12(17), 8746; https://doi.org/10.3390/app12178746 - 31 Aug 2022

Cited by 4 | Viewed by 3099

Abstract

Automated recognition of surgical phases is a prerequisite for computer-assisted analysis of surgeries. The research on phase recognition has been mostly driven by publicly available datasets of laparoscopic cholecystectomy (Lap Chole) videos. Yet, videos observed in real-world settings might contain challenges, such as [...] Read more.

Automated recognition of surgical phases is a prerequisite for computer-assisted analysis of surgeries. The research on phase recognition has been mostly driven by publicly available datasets of laparoscopic cholecystectomy (Lap Chole) videos. Yet, videos observed in real-world settings might contain challenges, such as additional phases and longer videos, which may be missing in curated public datasets. In this work, we study (i) the possible data distribution discrepancy between videos observed in a given medical center and videos from existing public datasets, and (ii) the potential impact of this distribution difference on model development. To this end, we gathered a large, private dataset of 384 Lap Chole videos. Our dataset contained all videos, including emergency surgeries and teaching cases, recorded in a continuous time frame of five years. We observed strong differences between our dataset and the most commonly used public dataset for surgical phase recognition, Cholec80. For instance, our videos were much longer, included additional phases, and had more complex transitions between phases. We further trained and compared several state-of-the-art phase recognition models on our dataset. The models’ performances greatly varied across surgical phases and videos. In particular, our results highlighted the challenge of recognizing extremely under-represented phases (usually missing in public datasets); the major phases were recognized with at least 76 percent recall. Overall, our results highlighted the need to better understand the distribution of the video data phase recognition models are trained on. Full article

(This article belongs to the Special Issue Novel Advances in Computer-Assisted Surgery)

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14 pages, 892 KiB

Open AccessArticle

Real-Time Data-Driven Approach for Prediction and Correction of Electrode Array Trajectory in Cochlear Implantation

by Nauman Hafeez, Xinli Du, Nikolaos Boulgouris, Philip Begg, Richard Irving, Chris Coulson and Guillaume Tourrel

Appl. Sci. 2022, 12(13), 6343; https://doi.org/10.3390/app12136343 - 22 Jun 2022

Cited by 2 | Viewed by 1567

Abstract

Cochlear implants provide hearing perception to people with severe to profound hearing loss. The electrode array (EA) inserted during the surgery directly stimulates the hearing nerve, bypassing the acoustic hearing system. The complications during the EA insertion in the inner ear may cause [...] Read more.

Cochlear implants provide hearing perception to people with severe to profound hearing loss. The electrode array (EA) inserted during the surgery directly stimulates the hearing nerve, bypassing the acoustic hearing system. The complications during the EA insertion in the inner ear may cause trauma leading to infection, residual hearing loss, and poor speech perception. This work aims to reduce the trauma induced during electrode array insertion process by carefully designing a sensing method, an actuation system, and data-driven control strategy to guide electrode array in scala tympani. Due to limited intra-operative feedback during the insertion process, complex bipolar electrical impedance is used as a sensing element to guide EA in real time. An automated actuation system with three degrees of freedom was used along with a complex impedance meter to record impedance of consecutive electrodes. Prediction of EA direction (medial, middle, and lateral) was carried out by an ensemble of random forest, shallow neural network, and k-nearest neighbour in an offline setting with an accuracy of 86.86%. The trained ensemble was then utilized in vitro for prediction and correction of EA direction in real time in the straight path with an accuracy of 80%. Such a real-time system also has application in other electrode implants and needle and catheter insertion guidance. Full article

(This article belongs to the Special Issue Novel Advances in Computer-Assisted Surgery)

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7 pages, 1411 KiB

Open AccessArticle

Augmented Reality-Assisted Percutaneous Pedicle Screw Instrumentation: A Cadaveric Feasibility and Accuracy Study

by Chih-Chang Chang, Chao-Hung Kuo, Hsuan-Kan Chang, Tsung-Hsi Tu, Li-Yu Fay, Jau-Ching Wu, Henrich Cheng and Wen-Cheng Huang

Appl. Sci. 2022, 12(10), 5261; https://doi.org/10.3390/app12105261 - 23 May 2022

Cited by 5 | Viewed by 1536

Abstract

Percutaneous pedicle screw instrumentation is the keystone of minimally invasive spine surgery. Percutaneous screw placement demands experience and relies greatly on intra-operative image guidance. This study aims to validate the feasibility and accuracy of augmented-reality (AR)-assisted percutaneous pedicle screw instrumentation. One cadaveric torso [...] Read more.

Percutaneous pedicle screw instrumentation is the keystone of minimally invasive spine surgery. Percutaneous screw placement demands experience and relies greatly on intra-operative image guidance. This study aims to validate the feasibility and accuracy of augmented-reality (AR)-assisted percutaneous pedicle screw instrumentation. One cadaveric torso was prepared for this study. After a pre-operative computed tomography (CT) scan, the images were transferred to an AR station to generate a 3D hologram. The 3D hologram and navigation images were projected to a pair of goggles with a display screen. With registration, the 3D spine hologram was overlayed onto the cadaver. Bilateral instrumentation from T6 to L5 was performed by two surgeons using AR assistance. A post-operative CT scan was obtained. The Gertzbein–Robbins scale (grade 0–3) was used for accuracy assessment. A total of 24 screws were placed. The overall screw accuracy was 87.5%. There were three major medial breaches that occurred on Rt T6/7/8, which were the most distant screws from the iliac reference. The cause of the three major medial breaches appeared to be related to their distance from the iliac reference. AR-assisted percutaneous pedicle screw instrumentation could improve anatomical visualization, facilitate surgical workflow, and provide an intuitive way of performing surgery. Full article

(This article belongs to the Special Issue Novel Advances in Computer-Assisted Surgery)

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12 pages, 1948 KiB

Open AccessArticle

Comparison of Radiation Exposure of AIRO Intraoperative CT with C-Arm Fluoroscopy during Posterior Lumbar Interbody Fusion

by Brecht Van Berkel, Gwendolien Smets, Gertjan Van Schelverghem, Elien Houben, Dieter Peuskens, Thomas Daenekindt, Eveleen Buelens, Frank Weyns, Joris Nens, Albrecht Houben and Sofie Van Cauter

Appl. Sci. 2021, 11(21), 10326; https://doi.org/10.3390/app112110326 - 03 Nov 2021

Cited by 1 | Viewed by 2130

Abstract

Navigation systems used during minimally invasive spine procedures have evolved from uniplanar, two-dimensional C-arm fluoroscopy to multiplanar, 3D intraoperative computed tomography (iCT). In this study, the radiation exposure to the patient and operating room staff in posterior intervertebral lumbar fusion procedures is compared [...] Read more.

Navigation systems used during minimally invasive spine procedures have evolved from uniplanar, two-dimensional C-arm fluoroscopy to multiplanar, 3D intraoperative computed tomography (iCT). In this study, the radiation exposure to the patient and operating room staff in posterior intervertebral lumbar fusion procedures is compared between iCT and C-arm fluoroscopy. The effective dose of the surgeon, operating nurse, and anesthesiologist was measured during surgery with personal dosimeters, and the effective dose of the patient was measured with Gafchromic^TM films. The time efficiency of the procedure was evaluated by recording the duration of pedicle screw fixation and the duration of the total surgery time. A total of 75 patients participated in the study; 30 patients had surgery guided by iCT and 45 by C-arm fluoroscopy. The radiation dose of the surgeon, the operating nurse, and the anesthesiologist was thirteen fold lower with surgeries assisted by iCT compared to C-arm fluoroscopy. In contrast, the effective dose of the patient significantly increased with iCT. Using iCT, radiation exposure of the operating room staff can be significantly reduced. iCT increases the effective dose of the patient and prolongs the operative time. Full article

(This article belongs to the Special Issue Novel Advances in Computer-Assisted Surgery)

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12 pages, 10560 KiB

Open AccessArticle

Preoperative Planning for Superior Mesenteric Artery Aneurysm

by Cristiana Iulia Dumitrescu, Catalin Ciobirca, Radu Teodoru Popa, Daniela Dumitrescu, Cornel Gheorghe Tambura, Diana Maria Ciobirca, Radu Stavaru, Mihai Florin Tiuca, Suzana Maces, Lucian Florentin Barbulescu, Liliana Didi Popa and Sergiu Marian Cazacu

Appl. Sci. 2021, 11(21), 10311; https://doi.org/10.3390/app112110311 - 03 Nov 2021

Cited by 3 | Viewed by 2374

Abstract

Surgical procedures on various artery aneurysms are difficult to perform and require careful preparation. We have developed and now present in this paper a software platform, CardioCTNav, that can help in planning such procedures. The planning consists of a 3D rendering of the [...] Read more.

Surgical procedures on various artery aneurysms are difficult to perform and require careful preparation. We have developed and now present in this paper a software platform, CardioCTNav, that can help in planning such procedures. The planning consists of a 3D rendering of the area of interest, virtual angiography, automated measurements, and virtual stent simulation. Full article

(This article belongs to the Special Issue Novel Advances in Computer-Assisted Surgery)

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18 pages, 19198 KiB

Open AccessArticle

Analysis of Process Costing for the Use of Navigation Systems in Functional Endoscopic Sinus Surgery

by Franziska Eva Schwan, Maximilian Traxdorf, Caroline Theresa Seebauer, Andrzej Sekita, Cornelia Habekost, Heinrich Iro and Christopher Bohr

Appl. Sci. 2021, 11(18), 8616; https://doi.org/10.3390/app11188616 - 16 Sep 2021

Viewed by 2196

Abstract

(1) Background: The use of navigation systems is rarely necessary for routine sinus surgery. They may prove to be advantageous for difficult operations, for example, in finding structures that are difficult to reach, in the treatment of cancers, or in revisional surgery. Navigation [...] Read more.

(1) Background: The use of navigation systems is rarely necessary for routine sinus surgery. They may prove to be advantageous for difficult operations, for example, in finding structures that are difficult to reach, in the treatment of cancers, or in revisional surgery. Navigation systems are also said to have positive effects on the self-confidence of surgeons in stressful situations and in the training of doctors. (2) Methods: This retrospective study included patients who underwent surgical treatment for chronic sinusitis from 2012 to 2016 at the ENT clinic of the University Hospital, Erlangen. Two groups were formed; one includes patients without navigated sinus surgery, the other includes those with navigation. The incision–suture times of both groups and cost analysis are compared. An appropriate cost estimate for sinus surgery is determined. (3) Results: From the available results, no economically efficient navigation systems in sinus surgery at the ENT clinic can be shown. The main reason is that lengthening the operating time leads to higher costs. (4) Conclusions: Although the use of a navigation system for endonasal sinus surgery cannot be economically justified, it is an important tool, especially in cases with complex anatomical conditions, and the system is essential for training purposes. Full article

(This article belongs to the Special Issue Novel Advances in Computer-Assisted Surgery)

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