Ozanan R. Meireles's research while affiliated with Massachusetts General Hospital and other places
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Publications (26)
Background
Surgical phase recognition using computer vision presents an essential requirement for artificial intelligence-assisted analysis of surgical workflow. Its performance is heavily dependent on large amounts of annotated video data, which remain a limited resource, especially concerning highly specialized procedures. Knowledge transfer from...
Background
Surgical video recording provides the opportunity to acquire intraoperative data that can subsequently be used for a variety of quality improvement, research, and educational applications. Various recording devices are available for standard operating room camera systems. Some allow for collateral data acquisition including activities of...
Background
The application of artificial intelligence (AI) to minimally invasive surgery has the potential to improve surgical safety, support intraoperative decision making, and reduce operative complications. Computer vision and machine learning are subfields or AI, focused on making statistical inferences and generating predictive calculations a...
Background
Operative courses of laparoscopic cholecystectomies vary widely due to differing pathologies. Efforts to assess intra-operative difficulty include the Parkland grading scale (PGS), which scores inflammation from the initial view of the gallbladder on a 1–5 scale. We investigated the impact of PGS on intra-operative outcomes, including la...
We constantly integrate our knowledge and understanding of the world to enhance our interpretation of what we see. This ability is crucial in application domains which entail reasoning about multiple entities and concepts, such as AI-augmented surgery. In this paper, we propose a novel way of integrating conceptual knowledge into temporal analysis...
Annotation of surgical video is important for establishing ground truth in surgical data science endeavors that involve computer vision. With the growth of the field over the last decade, several challenges have been identified in annotating spatial, temporal, and clinical elements of surgical video as well as challenges in selecting annotators. In...
Aims and background:
Identifying fibrosis in non-alcoholic fatty liver disease (NAFLD) is essential to predict liver-related outcomes and inform treatment decisions. A protein-based signature of fibrosis could serve as a valuable, non-invasive diagnostic tool. This study sought to identify circulating proteins associated with fibrosis in NAFLD.
M...
Background
The growing interest in analysis of surgical video through machine learning has led to increased research efforts; however, common methods of annotating video data are lacking. There is a need to establish recommendations on the annotation of surgical video data to enable assessment of algorithms and multi-institutional collaboration.
M...
Background: The growing interest in analysis of surgical video through machine learning has led to increased research efforts; however, common methods of annotating video data are lacking. There is a need to establish recommendations on the annotation of surgical video data to enable assessment of algorithms and multi-institutional collaboration. M...
Background:
Structured training protocols can safely improve skills prior initiating complex surgical procedures such as robotic-assisted minimally invasive esophagectomy (RAMIE). As no consensus on a training curriculum for RAMIE has been established so far it is our aim to define a protocol for RAMIE with the Delphi consensus methodology.
Metho...
Approaches to manage nonalcoholic fatty liver disease (NAFLD) are limited by an incomplete understanding of disease pathogenesis. The aim of this study was to identify hepatic gene‐expression patterns associated with different patterns of liver injury in a high‐risk cohort of adults with obesity. Using the NanoString Technologies (Seattle, WA) nCou...
Background
Artificial intelligence (AI) and computer vision (CV) have revolutionized image analysis. In surgery, CV applications have focused on surgical phase identification in laparoscopic videos. We proposed to apply CV techniques to identify phases in an endoscopic procedure, peroral endoscopic myotomy (POEM).MethodsPOEM videos were collected f...
In the last decade, we have been witnessing the great potential of a Cognitive Revolution in Medicine that promises to completely transform surgery. Artificial intelligence, with the use of big data, modern-day compute power, novel deep learning algorithms, and increased investments, forms the foundation for this revolution. Surgery, in particular,...
Imagine an Intelligent Operating Room that becomes an extension of the surgeon, extending all the senses using embedded sensors, and guarding all aspects of surgery to ensure the best outcomes.
Desmoid tumors are rare malignancies derived from myofibroblasts, which can cause significant morbidity due to life-threatening invasion of local structures. Risk factors include familial adenomatous polyposis, antecedent surgical trauma and estrogen exposure. We described a previously healthy 27-year-old female in whom a desmoid tumor developed 2...
The goal of this chapter is to help readers understand common indications for and contraindications to endoscopic balloon dilation of the upper GI tract. Technical considerations are described, including a common technique for performing endoscopic balloon dilation of the upper GI tract. Troubleshooting tips are provided for common procedural chall...
Objective(s):
To develop and assess AI algorithms to identify operative steps in laparoscopic sleeve gastrectomy (LSG).
Background:
Computer vision, a form of artificial intelligence (AI), allows for quantitative analysis of video by computers for identification of objects and patterns, such as in autonomous driving.
Methods:
Intraoperative vi...
Background:
Obesity is a known risk factor for nonalcoholic fatty liver disease (NAFLD). However, among individuals undergoing bariatric surgery, the prevalence and risk factors for NAFLD, as well as distinct phenotypes of steatosis, nonalcoholic steatohepatitis (NASH), and fibrosis remain incompletely understood.
Objectives:
To determine the pr...
2017 IEEE. Context-aware segmentation of laparoscopic and robot assisted surgical video has been shown to improve performance and perioperative workflow efficiency, and can be used for education and time-critical consultation. Modern pressures on productivity preclude manual video analysis, and hospital policies and legacy infrastructure are often...
Citations
... The relative paucity of imaging data of Esophagectomy cases, compared to previously investigated procedures, force the community to look creatively at related procedures and investigate similar target features to address. Moreover, the definition of target features and appropriate annotation guidelines for such procedures require careful consideration to be simultaneously clinically relevant as well as applicable to ML algorithms [17]. ...
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... Furthermore, they created an artificial intelligence model that could reliably quantify inflammation compared to a surgeon. This automated assessment could be helpful for operating room workflow optimization, given that operating room time is expensive and a limited resource [18]. ...
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... This may be linked to data characteristics, which are unfavorable for ML-based analysis. ML algorithms are largely based on probabilistic identification of patterns within the data [21,22]. Therefore, the disrupted temporal structures, rather than linear workflows, as well as short phase durations and frequent transitions, present a challenging endeavor for phase recognition. ...
... A multi-stakeholder initiative recently introduced guidelines and flowcharts on the choice of AI evaluation metrics in the medical image domain67 . For surgical video analysis this effort still needs to be taken68 . To overcome the limitations of the proposed AI models for technical skill assessment, valid and representative datasets using predefined performance metrics, and external validation in clinical implementation studies will be essential. ...
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... It is characterized by excessive hepatic steatosis, lobular inflammation, and hepatocyte ballooning changes. Moreover, NAFLD may progress to non-alcoholic steatohepatitis (NASH) and cirrhosis, potentially leading to hepatic carcinoma [1]. NAFLD pathogenesis may be linked to abnormal glucose and lipid metabolism, inflammation, endoplasmic reticulum stress (ERS), oxidative stress, and imbalanced gut microorganisms, according to existing research [2,3]. ...
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... We followed this approach to explore the value of robotics in PFRS with the use of a Delphi methodology. This approach has recently become popular to assess robotic surgery [19,20], including training [21], and the role of innovations related to this surgical approach [22]. ...
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... [96] online tool was used for visualization. Changes in messenger ribonucleic acid (mRNA) and the protein expression of the core targets in the context of NASH were obtained through DGE analysis of the GSE163211 dataset (GPL29503 platform) and a previous publication, respectively [97]. ...
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... Surgical gestures, defined as the smallest meaningful interaction of a surgical instrument with human tissue 4,5 , are a novel approach to deconstruct surgery. They have the potential to objectively quantify surgery meanwhile provide actionable feedback for trainees. ...
... In our case, the two datasets were acquired in two different high-volume centers, and exhibited vastly different surgical traits (bariatric vs. oncological surgery, operating surgeons and teams, camera view, port placement and instruments, etc.). Moreover, divergent approaches to temporal annotation of surgical video data, due to the lack of standardized protocols [23,24], impacts knowledge transfer. A more complex surgical workflow requires more granular annotation, which in turn results in higher clinical relevance [25]. ...
... An in-depth discussion of the appropriateness of individual metrics for a given situation is outside the scope of this article; however, it is important to consider aspects such as the number of annotators and the prevalence of a given annotation [13,14]. Reassuringly, in a preliminary study, pooling annotations from multiple clinical expert annotators did not result in a decrease of the trained model's performance [15]. To help reduce variation across annotators, it is critical to precisely define the phenomenon of interest that is to be annotated. ...
Reference: Challenges in surgical video annotation
