OBJECTIVE:The aim of this review was to summarize major topics in artificial intelligence (AI), including their applications and limitations in surgery. This paper reviews the key capabilities of AI ...to help surgeons understand and critically evaluate new AI applications and to contribute to new developments.
SUMMARY BACKGROUND DATA:AI is composed of various subfields that each provide potential solutions to clinical problems. Each of the core subfields of AI reviewed in this piece has also been used in other industries such as the autonomous car, social networks, and deep learning computers.
METHODS:A review of AI papers across computer science, statistics, and medical sources was conducted to identify key concepts and techniques within AI that are driving innovation across industries, including surgery. Limitations and challenges of working with AI were also reviewed.
RESULTS:Four main subfields of AI were defined(1) machine learning, (2) artificial neural networks, (3) natural language processing, and (4) computer vision. Their current and future applications to surgical practice were introduced, including big data analytics and clinical decision support systems. The implications of AI for surgeons and the role of surgeons in advancing the technology to optimize clinical effectiveness were discussed.
CONCLUSIONS:Surgeons are well positioned to help integrate AI into modern practice. Surgeons should partner with data scientists to capture data across phases of care and to provide clinical context, for AI has the potential to revolutionize the way surgery is taught and practiced with the promise of a future optimized for the highest quality patient care.
Background
Barrier dysfunction is an important feature of atopic dermatitis (AD) in which IL‐4 and IL‐13, signature type 2 cytokines, are involved. Periostin, a matricellular protein induced by IL‐4 ...or IL‐13, plays a crucial role in the onset of allergic skin inflammation, including barrier dysfunction. However, it remains elusive how periostin causes barrier dysfunction downstream of the IL‐13 signal.
Methods
We systematically identified periostin‐dependent expression profile using DNA microarrays. We then investigated whether IL‐24 downregulates filaggrin expression downstream of the IL‐13 signals and whether IL‐13‐induced IL‐24 expression and IL‐24‐induced downregulation of filaggrin expression are dependent on the JAK/STAT pathway. To build on the significance of in vitro findings, we investigated expression of IL‐24 and activation of STAT3 in mite‐treated mice and in AD patients.
Results
We identified IL‐24 as an IL‐13‐induced molecule in a periostin‐dependent manner. Keratinocytes are the main IL‐24‐producing tissue‐resident cells stimulated by IL‐13 in a periostin‐dependent manner via STAT6. IL‐24 significantly downregulated filaggrin expression via STAT3, contributing to barrier dysfunction downstream of the IL‐13/periostin pathway. Wild‐type mite‐treated mice showed significantly enhanced expression of IL‐24 and activation of STAT3 in the epidermis, which disappeared in both STAT6‐deficient and periostin‐deficient mice, suggesting that these events are downstream of both STAT6 and periostin. Moreover, IL‐24 expression was enhanced in the epidermis of skin tissues taken from AD patients.
Conclusions
The IL‐13/periostin pathway induces IL‐24 production in keratinocytes, playing an important role in barrier dysfunction in AD.
Epithelial barrier dysfunction is important in the pathogenesis of atopic dermatitis. We show that IL‐24 produced in keratinocytes downstream of IL‐13 and periostin downregulates filaggrin expression leading to barrier dysfunction.
We here taxonomically revise the suborder Massarineae (Pleosporales, Dothideomycetes, Ascomycota). Sequences of SSU and LSU nrDNA and the translation elongation factor 1-alpha gene (tef1) are newly ...obtained from 106 Massarineae taxa that are phylogenetically analysed along with published sequences of 131 taxa in this suborder retrieved from GenBank. We recognise 12 families and five unknown lineages in the Massarineae. Among the nine families previously known, the monophyletic status of the Dictyosporiaceae, Didymosphaeriaceae, Latoruaceae, Macrodiplodiopsidaceae, Massarinaceae, Morosphaeriaceae, and Trematosphaeriaceae was strongly supported with bootstrap support values above 96 %, while the clades of the Bambusicolaceae and the Lentitheciaceae are moderately supported. Two new families, Parabambusicolaceae and Sulcatisporaceae, are proposed. The Parabambusicolaceae is erected to accommodate Aquastroma and Parabambusicola genera nova, as well as two unnamed Monodictys species. The Parabambusicolaceae is characterised by depressed globose to hemispherical ascomata with or without surrounding stromatic tissue, and multi-septate, clavate to fusiform, hyaline ascospores. The Sulcatisporaceae is established for Magnicamarosporium and Sulcatispora genera nova and Neobambusicola. The Sulcatisporaceae is characterised by subglobose ascomata with a short ostiolar neck, trabeculate pseudoparaphyses, clavate asci, broadly fusiform ascospores, and ellipsoid to subglobose conidia with or without striate ornamentation. The genus Periconia and its relatives are segregated from the Massarinaceae and placed in a resurrected family, the Periconiaceae. We have summarised the morphological and ecological features, and clarified the accepted members of each family. Ten new genera, 22 new species, and seven new combinations are described and illustrated. The complete ITS sequences of nrDNA are also provided for all new taxa for use as barcode markers.
The family Lophiotremataceae (Pleosporales, Dothideomycetes) is taxonomically revised on the basis of morphological observations and phylogenetic analyses of sequences of nuclear rDNA SSU, ITS, and ...LSU regions and tef1 and rpb2 genes. A total of 208
sequences were generated from species of Lophiotremataceae and its relatives. According to phylogenetic analyses, Lophiotremataceae encompasses the genus Lophiotrema and five new genera: Atrocalyx, Crassimassarina, Cryptoclypeus, Galeaticarpa,
and Pseudocryptoclypeus. These genera are characterised by ascomata with or without a slit-like ostiole and pycnidial conidiomata. Three new families, Aquasubmersaceae, Cryptocoryneaceae, and Hermatomycetaceae, are proposed. Two genera previously recognised as members
of Lophiotremataceae, namely, Aquasubmersa having ascomata with a papillate ostiolar neck and pycnidial conidiomata and Hermatomyces possessing sporodochial conidiomata and dimorphic (lenticular and cylindrical) conidia, are included in Aquasubmersaceae and
Hermatomycetaceae, respectively. Cryptocoryneum, characterised by the presence of stromatic sporodochia, cheiroid conidia, and conidial arms developed downward from the cap cells, is placed in Cryptocoryneaceae. Two new genera, Antealophiotrema and Pseudolophiotrema,
are established, but their familial placements remain unresolved. Antealophiotrema bears ascomata morphologically similar to those of Lophiotrema, but is differentiated from the latter by having ascomata with a well-developed peridium and a monodictys-like asexual morph. Pseudolophiotrema
is also similar to Lophiotrema, but can be distinguished by ascomata with a thin peridium. A total of three new families, seven new genera, eight new species, and two new combinations are described and illustrated.
Wearable technologies are small electronic and mobile devices with wireless communication capabilities that can be worn on the body as a part of devices, accessories or clothes. Sensors incorporated ...within wearable devices enable the collection of a broad spectrum of data that can be processed and analysed by artificial intelligence (AI) systems. In this narrative review, we performed a literature search of the MEDLINE, Embase and Scopus databases. We included any original studies that used sensors to collect data for a sporting event and subsequently used an AI-based system to process the data with diagnostic, treatment or monitoring intents. The included studies show the use of AI in various sports including basketball, baseball and motor racing to improve athletic performance. We classified the studies according to the stage of an event, including pre-event training to guide performance and predict the possibility of injuries; during events to optimise performance and inform strategies; and in diagnosing injuries after an event. Based on the included studies, AI techniques to process data from sensors can detect patterns in physiological variables as well as positional and kinematic data to inform how athletes can improve their performance. Although AI has promising applications in sports medicine, there are several challenges that can hinder their adoption. We have also identified avenues for future work that can provide solutions to overcome these challenges.
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 laparoscopic duration, attainment of the critical view of safety (CVS), and gallbladder injury. We additionally trained an artificial intelligence (AI) model to identify PGS.
Methods
One surgeon labeled surgical phases, PGS, CVS attainment, and gallbladder injury in 200 cholecystectomy videos. We used multilevel Bayesian regression models to analyze the PGS’s effect on intra-operative outcomes. We trained AI models to identify PGS from an initial view of the gallbladder and compared model performance to annotations by a second surgeon.
Results
Slightly inflamed gallbladders (PGS-2) minimally increased duration, adding 2.7 95% compatibility interval (CI) 0.3–7.0 minutes to an operation. This contrasted with maximally inflamed gallbladders (PGS-5), where on average 16.9 (95% CI 4.4–33.9) minutes were added, with 31.3 (95% CI 8.0–67.5) minutes added for the most affected surgeon. Inadvertent gallbladder injury occurred in 25% of cases, with a minimal increase in gallbladder injury observed with added inflammation. However, up to a 28% (95% CI − 2, 63) increase in probability of a gallbladder hole during PGS-5 cases was observed for some surgeons. Inflammation had no substantial effect on whether or not a surgeon attained the CVS. An AI model could reliably (Krippendorff’s
α
= 0.71, 95% CI 0.65–0.77) quantify inflammation when compared to a second surgeon (
α
= 0.82, 95% CI 0.75–0.87).
Conclusions
An AI model can identify the degree of gallbladder inflammation, which is predictive of cholecystectomy intra-operative course. This automated assessment could be useful for operating room workflow optimization and for targeted per-surgeon and per-resident feedback to accelerate acquisition of operative skills.
Graphical abstract
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).
Methods
POEM videos were collected from Massachusetts General and Showa University Koto Toyosu Hospitals. Videos were labeled by surgeons with the following ground truth phases: (1) Submucosal injection, (2) Mucosotomy, (3) Submucosal tunnel, (4) Myotomy, and (5) Mucosotomy closure. The deep-learning CV model—Convolutional Neural Network (CNN) plus Long Short-Term Memory (LSTM)—was trained on 30 videos to create POEMNet. We then used POEMNet to identify operative phases in the remaining 20 videos. The model’s performance was compared to surgeon annotated ground truth.
Results
POEMNet’s overall phase identification accuracy was 87.6% (95% CI 87.4–87.9%). When evaluated on a per-phase basis, the model performed well, with mean unweighted and prevalence-weighted F1 scores of 0.766 and 0.875, respectively. The model performed best with longer phases, with 70.6% accuracy for phases that had a duration under 5 min and 88.3% accuracy for longer phases.
Discussion
A deep-learning-based approach to CV, previously successful in laparoscopic video phase identification, translates well to endoscopic procedures. With continued refinements, AI could contribute to intra-operative decision-support systems and post-operative risk prediction.
Background
Per oral endoscopic myotomy (POEM) has been shown to be an efficacious and safe therapy for the treatment of achalasia. Compared to laparoscopic Heller myotomy however, no antireflux ...procedure is routinely combined with POEM and therefore the development of symptomatic or silent reflux is of concern. This study was designed to determine if various patient factors and anatomy would predict the development of gastroesophageal reflux disease post-operatively.
Methods
This was a retrospective cohort study of all patients who underwent a POEM at a single institution by a single surgeon over an eight-year period (2014–2022). It has been our practice to obtain a postoperative ambulatory pH test on all patients 6 months after POEM off all acid reducing medications. Patients without a postoperative ambulatory esophageal pH monitoring test were excluded. Age, sex, obesity (BMI > 30), achalasia type, presence of a hiatal hernia, history of prior endoscopic achalasia treatments or myotomy were analyzed using univariate analysis as predictive factors for the development of postoperative GERD (DeMeester score > 14.7 on ambulatory pH monitoring).
Results
There were 179 total patients included in the study with 42 patients (23.5%) having undergone postoperative ambulatory pH testing. The majority of patients (137 or 76.5%) were lost to follow up and did not undergo ambulatory pH testing. Twenty-three out of those 42 patients (55%) had evidence of GERD on ambulatory pH testing. Multiple preoperative patient characteristics including demographics, manometric results, EGD findings, and history of prior achalasia interventions did not correlate with the development of post-operative GERD.
Conclusions
Despite the high rate of reflux after POEM, there does not appear to be any reliable preoperative indicators of which patients have a higher risk of developing post-operative GERD after POEM.
Background
While per oral endoscopic myotomy (POEM) has been shown to be efficacious in the treatment of achalasia, it can be difficult to predict who will have a robust and durable response. ...Historically, high lower esophageal sphincter pressures have been shown to predict a worse response to endoscopic therapies such as botox therapy. This study was designed to evaluate if modern preoperative manometric data could predict a response to therapy after POEM.
Methods
This was a retrospective study of 144 patients who underwent a POEM at a single institution by a single surgeon over an 8-year period (2014–2022) who had high-resolution manometry performed preoperatively and had an Eckardt symptom score performed both preoperatively and postoperatively. The achalasia type and integrated relaxation pressures (IRP) were then tested for potential correlation with need for any further achalasia interventions postoperatively as well as the degree of Eckardt score reduction using univariate analysis.
Results
The achalasia type on preoperatively manometry was not predictive of need for further interventions or degree of Eckardt score reduction (
p
= 0.74 and 0.44, respectively). A higher IRP was not predictive of need for further interventions however it was predictive of a greater reduction in postoperative Eckardt scores (
p
= 0.03) as shown by a nonzero regression slope.
Conclusion
In this study, achalasia type was not a predictive factor in need for further interventions or degree of symptom relief. While IRP was not predictive of need for further interventions, a higher IRP did predict better symptomatic relief postoperatively. This result is opposite that of other endoscopic treatment modalities. Therefore, patients with higher IRP on high-resolution manometry would likely benefit from myotomy which provides significant symptomatic relief postoperatively.
The Role of Artificial Intelligence in Surgery Hashimoto, Daniel A.; Ward, Thomas M.; Meireles, Ozanan R.
Advances in surgery (Chicago),
September 2020, 2020-09-00, 20200901, Volume:
54
Journal Article
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