Artificial intelligence makes surgical resection easier and safer, and, at the same time, can improve oncological results. The robotic system fits perfectly with these more or less diffused ...technologies, and it seems that this benefit is mutual. In liver surgery, robotic systems help surgeons to localize tumors and improve surgical results with well-defined preoperative planning or increased intraoperative detection. Furthermore, they can balance the absence of tactile feedback and help recognize intrahepatic biliary or vascular structures during parenchymal transection. Some of these systems are well known and are already widely diffused in open and laparoscopic hepatectomies, such as indocyanine green fluorescence or ultrasound-guided resections, whereas other tools, such as Augmented Reality, are far from being standardized because of the high complexity and elevated costs. In this paper, we review all the experiences in the literature on the use of artificial intelligence systems in robotic liver resections, describing all their practical applications and their weaknesses.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Background
Modern chemotherapy achieves the shrinking of colorectal cancer liver metastases (CRLM) to such extent that they may disappear from radiological imaging. Disappearing CRLM rarely ...represents a complete pathological remission and have an important risk of recurrence. Augmented reality (AR) consists in the fusion of real-time patient images with a computer-generated 3D virtual patient model created from pre-operative medical imaging. The aim of this prospective pilot study is to investigate the potential of AR navigation as a tool to help locate and surgically resect missing CRLM.
Methods
A 3D virtual anatomical model was created from thoracoabdominal CT-scans using customary software (VR RENDER
®
, IRCAD). The virtual model was superimposed to the operative field using an Exoscope (VITOM
®
, Karl Storz, Tüttlingen, Germany). Virtual and real images were manually registered in real-time using a video mixer, based on external anatomical landmarks with an estimated accuracy of 5 mm. This modality was tested in three patients, with four missing CRLM that had sizes from 12 to 24 mm, undergoing laparotomy after receiving pre-operative oxaliplatin-based chemotherapy.
Results
AR display and fine registration was performed within 6 min. AR helped detect all four missing CRLM, and guided their resection. In all cases the planned security margin of 1 cm was clear and resections were confirmed to be R0 by pathology. There was no postoperative major morbidity or mortality. No local recurrence occurred in the follow-up period of 6–22 months.
Conclusions
This initial experience suggests that AR may be a helpful navigation tool for the resection of missing CRLM.
Full text
Available for:
EMUNI, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UL, UM, UPUK, VKSCE, ZAGLJ
Pre‐operative simulation using three‐dimensional (3D) reconstructions have been suggested to enhance surgical planning of hepatectomy. Evidence on its benefits for hepatectomy patients remains ...limited. This systematic review examined the use and impact of pre‐operative simulation and intraoperative navigation on hepatectomy outcomes. A systematical searched electronic databases for studies reporting on the use and results of simulation and navigation for hepatectomy was performed. The primary outcome was change in operative plan based on simulation. Secondary outcomes included operating time (min), estimated blood loss, surgical margins, 30‐day postoperative morbidity and mortality, and study‐specific outcomes. From 222 citations, we included 11 studies including 497 patients. All were observational cohort studies. No study compared hepatectomy with and without simulation. All studies performed 3D reconstruction and segmentation, most commonly with volumetrics measurements. In six studies reporting intraoperative navigation, five relied on ultrasound, and one on a resection map. Of two studies reporting on it, the resection line was changed intraoperatively in one third of patients, based on simulation. Virtually predicted liver volumes (Pearson correlation r = 0.917 to 0.995) and surgical margins (r = 0.84 to 0.967) correlated highly with actual ones in eight studies. Heterogeneity of the included studies precluded meta‐analysis.Pre‐operative simulation seems accurate in measuring volumetrics and surgical margins. Current studies lack intraoperative transposition of simulation for direct navigation. Simulation appears useful planning of hepatectomies, but further work is warranted focusing on the development of improved tools and appraisal of their clinical impact compared to traditional resection.
Full text
Available for:
FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Background
Augmented reality (AR) in surgery consists in the fusion of synthetic computer-generated images (3D virtual model) obtained from medical imaging preoperative workup and real-time patient ...images in order to visualize unapparent anatomical details. The 3D model could be used for a preoperative planning of the procedure. The potential of AR navigation as a tool to improve safety of the surgical dissection is outlined for robotic hepatectomy.
Materials and methods
Three patients underwent a fully robotic and AR-assisted hepatic segmentectomy. The 3D virtual anatomical model was obtained using a thoracoabdominal CT scan with a customary software (VR-RENDER®, IRCAD). The model was then processed using a VR-RENDER® plug-in application, the Virtual Surgical Planning (VSP®, IRCAD), to delineate surgical resection planes including the elective ligature of vascular structures. Deformations associated with pneumoperitoneum were also simulated. The virtual model was superimposed to the operative field. A computer scientist manually registered virtual and real images using a video mixer (MX 70; Panasonic, Secaucus, NJ) in real time.
Results
Two totally robotic AR segmentectomy V and one segmentectomy VI were performed. AR allowed for the precise and safe recognition of all major vascular structures during the procedure. Total time required to obtain AR was 8 min (range 6–10 min). Each registration (alignment of the vascular anatomy) required a few seconds. Hepatic pedicle clamping was never performed. At the end of the procedure, the remnant liver was correctly vascularized. Resection margins were negative in all cases. The postoperative period was uneventful without perioperative transfusion.
Conclusions
AR is a valuable navigation tool which may enhance the ability to achieve safe surgical resection during robotic hepatectomy.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Radiomics is an emerging field which extracts quantitative radiology data from medical images and explores their correlation with clinical outcomes in a non-invasive manner. This review aims to ...assess whether radiomics is a useful and reproducible method for clinical management of hepatocellular carcinoma (HCC) by reviewing the strengths and weaknesses of current radiomics literature pertaining specifically to HCC. From an initial set of 48 articles recovered through database searches, 23 articles were retained to be included in this review after full screening. Among these 23 studies, 7 used a radiomics approach in magnetic resonance imaging (MRI). Only two studies applied radiomics to positron emission tomography–computed tomography (PET–CT). In the remaining 14 articles, a radiomics analysis was performed on computed tomography (CT). Eight studies dealt with the relationship between biological signatures and imaging findings, and can be classified as radiogenomic studies. For each study included in our review, we computed a Radiomics Quality Score (RQS) as proposed by Lambin et al. We found that the RQS (mean ± standard deviation) was 8.35 ± 5.38 (out of a possible maximum value of 36). Although these scores are fairly low, and radiomics has not yet reached clinical utility in HCC, it is important to underscore the fact that these early studies pave the way for the radiomics field with a focus on HCC. Radiomics is still a very young field, and is far from being mature, but it remains a very promising technology for the future for developing adequate personalized treatment as a non-invasive approach, for complementing or replacing tumor biopsies, as well as for developing novel prognostic biomarkers in HCC patients.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Purpose
We address the automatic segmentation of healthy and cancerous liver tissues (parenchyma, active and necrotic parts of hepatocellular carcinoma (HCC) tumor) on multiphase CT images using a ...deep learning approach.
Methods
We devise a cascaded convolutional neural network based on the
U
-Net architecture. Two strategies for dealing with multiphase information are compared: Single-phase images are concatenated in a multi-dimensional features map on the input layer, or output maps are computed independently for each phase before being merged to produce the final segmentation. Each network of the cascade is specialized in the segmentation of a specific tissue. The performances of these networks taken separately and of the cascaded architecture are assessed on both single-phase and on multiphase images.
Results
In terms of Dice coefficients, the proposed method is on par with a state-of-the-art method designed for automatic MR image segmentation and outperforms previously used technique for interactive CT image segmentation. We validate the hypothesis that several cascaded specialized networks have a higher prediction accuracy than a single network addressing all tasks simultaneously. Although the portal venous phase alone seems to provide sufficient contrast for discriminating tumors from healthy parenchyma, the multiphase information brings significant improvement for the segmentation of cancerous tissues (active versus necrotic part).
Conclusion
The proposed cascaded multiphase architecture showed promising performances for the automatic segmentation of liver tissues, allowing to reliably estimate the necrosis rate, a valuable imaging biomarker of the clinical outcome.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The robotic surgical system has been applied in liver surgery. However, controversies concerns exist regarding a variety of factors including the safety, feasibility, efficacy, and cost-effectiveness ...of robotic surgery. To promote the development of robotic hepatectomy, this study aimed to evaluate the current status of robotic hepatectomy and provide sixty experts' consensus and recommendations to promote its development. Based on the World Health Organization Handbook for Guideline Development, a Consensus Steering Group and a Consensus Development Group were established to determine the topics, prepare evidence-based documents, and generate recommendations. The GRADE Grid method and Delphi vote were used to formulate the recommendations. A total of 22 topics were prepared analyzed and widely discussed during the 4 meetings. Based on the published articles and expert panel opinion, 7 recommendations were generated by the GRADE method using an evidence-based method, which focused on the safety, feasibility, indication, techniques and cost-effectiveness of hepatectomy. Given that the current evidences were low to very low as evaluated by the GRADE method, further randomized-controlled trials are needed in the future to validate these recommendations.
Hepatitis C virus (HCV) is a major cause of liver disease, but therapeutic options are limited and there are no prevention strategies. Viral entry is the first step of infection and requires the ...cooperative interaction of several host cell factors. Using a functional RNAi kinase screen, we identified epidermal growth factor receptor and ephrin receptor A2 as host cofactors for HCV entry. Blocking receptor kinase activity by approved inhibitors broadly impaired infection by all major HCV genotypes and viral escape variants in cell culture and in a human liver chimeric mouse model in vivo. The identified receptor tyrosine kinases (RTKs) mediate HCV entry by regulating CD81-claudin-1 co-receptor associations and viral glycoprotein-dependent membrane fusion. These results identify RTKs as previously unknown HCV entry cofactors and show that tyrosine kinase inhibitors have substantial antiviral activity. Inhibition of RTK function may constitute a new approach for prevention and treatment of HCV infection.
Full text
Available for:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
PDF
