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Article ; Online: Using Diffuse Reflectance Spectroscopy to Classify Tumor Tissue in Upper Gastrointestinal Cancers-Reply.

Nazarian, Scarlet / Gkouzionis, Ioannis / Peters, Christopher J

2023 Volume 158, Issue 7, Page(s) 773

MeSH term(s)	Humans ; Spectrum Analysis/methods ; Gastrointestinal Neoplasms/diagnosis
Language	English
Publishing date	2023-03-01
Publishing country	United States
Document type	Letter ; Comment
ZDB-ID	2701841-6
ISSN	2168-6262 ; 2168-6254
ISSN (online)	2168-6262
ISSN	2168-6254
DOI	10.1001/jamasurg.2022.8433
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Article ; Online: Real-time classification of tumour and non-tumour tissue in colorectal cancer using diffuse reflectance spectroscopy and neural networks to aid margin assessment.

Nazarian, Scarlet / Gkouzionis, Ioannis / Murphy, Jamie / Darzi, Ara / Patel, Nisha / Peters, Christopher J / Elson, Daniel S

International journal of surgery (London, England)

2024 Volume 110, Issue 4, Page(s) 1983–1991

Abstract: Background: Colorectal cancer is the third most commonly diagnosed malignancy and the second leading cause of mortality worldwide. A positive resection margin following surgery for colorectal cancer is linked with higher rates of local recurrence and ... ...

Abstract	Background: Colorectal cancer is the third most commonly diagnosed malignancy and the second leading cause of mortality worldwide. A positive resection margin following surgery for colorectal cancer is linked with higher rates of local recurrence and poorer survival. The authors investigated diffuse reflectance spectroscopy (DRS) to distinguish tumour and non-tumour tissue in ex-vivo colorectal specimens, to aid margin assessment and provide augmented visual maps to the surgeon in real-time. Methods: Patients undergoing elective colorectal cancer resection surgery at a London-based hospital were prospectively recruited. A hand-held DRS probe was used on the surface of freshly resected ex-vivo colorectal tissue. Spectral data were acquired for tumour and non-tumour tissue. Binary classification was achieved using conventional machine learning classifiers and a convolutional neural network (CNN), which were evaluated in terms of sensitivity, specificity, accuracy and the area under the curve. Results: A total of 7692 mean spectra were obtained for tumour and non-tumour colorectal tissue. The CNN-based classifier was the best performing machine learning algorithm, when compared to contrastive approaches, for differentiating tumour and non-tumour colorectal tissue, with an overall diagnostic accuracy of 90.8% and area under the curve of 96.8%. Live on-screen classification of tissue type was achieved using a graduated colourmap. Conclusion: A high diagnostic accuracy for a DRS probe and tracking system to differentiate ex-vivo tumour and non-tumour colorectal tissue in real-time with on-screen visual feedback was highlighted by this study. Further in-vivo studies are needed to ensure integration into a surgical workflow.
MeSH term(s)	Humans ; Colorectal Neoplasms/pathology ; Colorectal Neoplasms/surgery ; Colorectal Neoplasms/classification ; Neural Networks, Computer ; Female ; Male ; Margins of Excision ; Prospective Studies ; Aged ; Spectrum Analysis/methods ; Middle Aged ; Machine Learning ; Aged, 80 and over
Language	English
Publishing date	2024-04-01
Publishing country	United States
Document type	Journal Article
ZDB-ID	2212038-5
ISSN	1743-9159 ; 1743-9191
ISSN (online)	1743-9159
ISSN	1743-9191
DOI	10.1097/JS9.0000000000001102
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Article ; Online: Diagnostic Accuracy of Smartwatches for the Detection of Cardiac Arrhythmia: Systematic Review and Meta-analysis.

Nazarian, Scarlet / Lam, Kyle / Darzi, Ara / Ashrafian, Hutan

Journal of medical Internet research

2021 Volume 23, Issue 8, Page(s) e28974

Abstract: Background: Significant morbidity, mortality, and financial burden are associated with cardiac rhythm abnormalities. Conventional investigative tools are often unsuccessful in detecting cardiac arrhythmias because of their episodic nature. Smartwatches ... ...

Abstract	Background: Significant morbidity, mortality, and financial burden are associated with cardiac rhythm abnormalities. Conventional investigative tools are often unsuccessful in detecting cardiac arrhythmias because of their episodic nature. Smartwatches have gained popularity in recent years as a health tool for the detection of cardiac rhythms. Objective: This study aims to systematically review and meta-analyze the diagnostic accuracy of smartwatches in the detection of cardiac arrhythmias. Methods: A systematic literature search of the Embase, MEDLINE, and Cochrane Library databases was performed in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to identify studies reporting the use of a smartwatch for the detection of cardiac arrhythmia. Summary estimates of sensitivity, specificity, and area under the curve were attempted using a bivariate model for the diagnostic meta-analysis. Studies were examined for quality using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Results: A total of 18 studies examining atrial fibrillation detection, bradyarrhythmias and tachyarrhythmias, and premature contractions were analyzed, measuring diagnostic accuracy in 424,371 subjects in total. The signals analyzed by smartwatches were based on photoplethysmography. The overall sensitivity, specificity, and accuracy of smartwatches for detecting cardiac arrhythmias were 100% (95% CI 0.99-1.00), 95% (95% CI 0.93-0.97), and 97% (95% CI 0.96-0.99), respectively. The pooled positive predictive value and negative predictive value for detecting cardiac arrhythmias were 85% (95% CI 0.79-0.90) and 100% (95% CI 1.0-1.0), respectively. Conclusions: This review demonstrates the evolving field of digital disease detection. The current diagnostic accuracy of smartwatch technology for the detection of cardiac arrhythmias is high. Although the innovative drive of digital devices in health care will continue to gain momentum toward screening, the process of accurate evidence accrual and regulatory standards ready to accept their introduction is strongly needed. Trial registration: PROSPERO International Prospective Register of Systematic Reviews CRD42020213237; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=213237.
MeSH term(s)	Atrial Fibrillation ; Humans ; Mass Screening ; Photoplethysmography ; Predictive Value of Tests
Language	English
Publishing date	2021-08-27
Publishing country	Canada
Document type	Journal Article ; Meta-Analysis ; Review ; Systematic Review
ZDB-ID	2028830-X
ISSN	1438-8871 ; 1439-4456
ISSN (online)	1438-8871
ISSN	1439-4456
DOI	10.2196/28974
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Article ; Online: Abdominal Drainage in Complicated Appendicectomy - Resources Down the Drain?

Nazarian, Scarlet / Boardman, Charlotte / Chohda, Ezzat / Shah, Ankur

Journal of Nepal Health Research Council

2021 Volume 18, Issue 4, Page(s) 672–675

Abstract: Background: There is currently no clear consensus on the use of drains during an appendicectomy to prevent abscess formation. Our aim was to ascertain whether the use of drains in complicated appendicitis reduces post-operative complications and length ... ...

Abstract	Background: There is currently no clear consensus on the use of drains during an appendicectomy to prevent abscess formation. Our aim was to ascertain whether the use of drains in complicated appendicitis reduces post-operative complications and length of stay. Methods: We performed a retrospective review of patients with complicated appendicitis undergoing appendicectomy from March-November 2018. Complicated appendicectomy (perforated or gangrenous appendicitis) patients were divided into two groups; with drain Group 1 (G1) and no drain Group 2 (G2). Groups were compared for post-operative complications and length of stay. Results: Out of a total 76 patients, 26 (34%) had drain (G1) and 50 (66%) had no drain (G2). The pre-operative CRP in G1 vs. G2 (124.8 vs. 48.3, p= 0.02); post-operative complication 9 (34.6%) vs. 6 (12%), p=0.019); intra-abdominal abscess 5 (19.2%) vs. 3 (6%), p=0.07 and LOS 5.5 days vs. 3 days, p=0.0001 were significantly higher in patients with a drain. Conclusions: The use of an intra-operative drain in complicated appendicitis increases the risk of a post-operative complication and increases length of stay.
MeSH term(s)	Appendectomy/adverse effects ; Appendicitis/surgery ; Drainage ; Humans ; Length of Stay ; Nepal ; Postoperative Complications/epidemiology ; Retrospective Studies
Language	English
Publishing date	2021-01-21
Publishing country	Nepal
Document type	Journal Article
ZDB-ID	2551251-1
ISSN	1999-6217 ; 1999-6217
ISSN (online)	1999-6217
ISSN	1999-6217
DOI	10.33314/jnhrc.v18i4.2466
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Article ; Online: Diagnostic Accuracy of Artificial Intelligence and Computer-Aided Diagnosis for the Detection and Characterization of Colorectal Polyps: Systematic Review and Meta-analysis.

Nazarian, Scarlet / Glover, Ben / Ashrafian, Hutan / Darzi, Ara / Teare, Julian

Journal of medical Internet research

2021 Volume 23, Issue 7, Page(s) e27370

Abstract: Background: Colonoscopy reduces the incidence of colorectal cancer (CRC) by allowing detection and resection of neoplastic polyps. Evidence shows that many small polyps are missed on a single colonoscopy. There has been a successful adoption of ... ...

Abstract	Background: Colonoscopy reduces the incidence of colorectal cancer (CRC) by allowing detection and resection of neoplastic polyps. Evidence shows that many small polyps are missed on a single colonoscopy. There has been a successful adoption of artificial intelligence (AI) technologies to tackle the issues around missed polyps and as tools to increase the adenoma detection rate (ADR). Objective: The aim of this review was to examine the diagnostic accuracy of AI-based technologies in assessing colorectal polyps. Methods: A comprehensive literature search was undertaken using the databases of Embase, MEDLINE, and the Cochrane Library. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. Studies reporting the use of computer-aided diagnosis for polyp detection or characterization during colonoscopy were included. Independent proportions and their differences were calculated and pooled through DerSimonian and Laird random-effects modeling. Results: A total of 48 studies were included. The meta-analysis showed a significant increase in pooled polyp detection rate in patients with the use of AI for polyp detection during colonoscopy compared with patients who had standard colonoscopy (odds ratio [OR] 1.75, 95% CI 1.56-1.96; P<.001). When comparing patients undergoing colonoscopy with the use of AI to those without, there was also a significant increase in ADR (OR 1.53, 95% CI 1.32-1.77; P<.001). Conclusions: With the aid of machine learning, there is potential to improve ADR and, consequently, reduce the incidence of CRC. The current generation of AI-based systems demonstrate impressive accuracy for the detection and characterization of colorectal polyps. However, this is an evolving field and before its adoption into a clinical setting, AI systems must prove worthy to patients and clinicians. Trial registration: PROSPERO International Prospective Register of Systematic Reviews CRD42020169786; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020169786.
MeSH term(s)	Artificial Intelligence ; Colonic Polyps/diagnosis ; Colonoscopy ; Colorectal Neoplasms/diagnosis ; Computers ; Humans
Language	English
Publishing date	2021-07-14
Publishing country	Canada
Document type	Journal Article ; Meta-Analysis ; Review ; Systematic Review
ZDB-ID	2028830-X
ISSN	1438-8871 ; 1438-8871
ISSN (online)	1438-8871
ISSN	1438-8871
DOI	10.2196/27370
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Article ; Online: A case for improved assessment of gut permeability: a meta-analysis quantifying the lactulose:mannitol ratio in coeliac and Crohn's disease.

Gan, Jonathan / Nazarian, Scarlet / Teare, Julian / Darzi, Ara / Ashrafian, Hutan / Thompson, Alex J

BMC gastroenterology

2022 Volume 22, Issue 1, Page(s) 16

Abstract: Background: A widely used method in assessing small bowel permeability is the lactulose:mannitol test, where the lactulose:mannitol ratio (LMR) is measured. However, there is discrepancy in how the test is conducted and in the values of LMR obtained ... ...

Abstract	Background: A widely used method in assessing small bowel permeability is the lactulose:mannitol test, where the lactulose:mannitol ratio (LMR) is measured. However, there is discrepancy in how the test is conducted and in the values of LMR obtained across studies. This meta-analysis aims to determine LMR in healthy subjects, coeliac and Crohn's disease. Methods: A literature search was performed using PRISMA guidance to identify studies assessing LMR in coeliac or Crohn's disease. 19 studies included in the meta-analysis measured gut permeability in coeliac disease, 17 studies in Crohn's disease. Outcomes of interest were LMR values and comparisons of standard mean difference (SMD) and weighted mean difference (WMD) in healthy controls, inactive Crohn's, active Crohn's, treated coeliac and untreated coeliac. Pooled estimates of differences in LMR were calculated using the random effects model. Results: Pooled LMR in healthy controls was 0.014 (95% CI: 0.006-0.022) while pooled LMRs in untreated and treated coeliac were 0.133 (95% CI: 0.089-0.178) and 0.037 (95% CI: 0.019-0.055). In active and inactive Crohn's disease, pooled LMRs were 0.093 (95% CI: 0.031-0.156) and 0.028 (95% CI: 0.015-0.041). Significant differences were observed in LMR between: (1) healthy controls and treated coeliacs (SMD = 0.409 95% CI 0.034 to 0.783, p = 0.032), (2) healthy controls and untreated coeliacs (SMD = 1.362 95% CI: 0.740 to 1.984, p < 0.001), (3) treated coeliacs and untreated coeliacs (SMD = 0.722 95% CI: 0.286 to 1.157, p = 0.001), (4) healthy controls and inactive Crohn's (SMD = 1.265 95% CI: 0.845 to 1.686, p < 0.001), (5) healthy controls and active Crohn's (SMD = 2.868 95% CI: 2.112 to 3.623, p < 0.001), and (6) active Crohn's and inactive Crohn's (SMD = 1.429 (95% CI: 0.580 to 2.278, p = 0.001). High heterogeneity was observed, which was attributed to variability in protocols used across different studies. Conclusion: The use of gut permeability measurements in screening and monitoring of coeliac and Crohn's disease is promising. LMR is useful in performing this function with significant limitations. More robust alternative tests with higher degrees of clinical evidence are needed if measurements of gut permeability are to find widespread clinical use.
MeSH term(s)	Celiac Disease ; Crohn Disease ; Humans ; Lactulose ; Mannitol ; Permeability
Chemical Substances	Mannitol (3OWL53L36A) ; Lactulose (4618-18-2)
Language	English
Publishing date	2022-01-10
Publishing country	England
Document type	Journal Article ; Meta-Analysis
ZDB-ID	2041351-8
ISSN	1471-230X ; 1471-230X
ISSN (online)	1471-230X
ISSN	1471-230X
DOI	10.1186/s12876-021-02082-z
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Article: Does computer-aided diagnostic endoscopy improve the detection of commonly missed polyps? A meta-analysis.

Sivananthan, Arun / Nazarian, Scarlet / Ayaru, Lakshmana / Patel, Kinesh / Ashrafian, Hutan / Darzi, Ara / Patel, Nisha

Clinical endoscopy

2022 Volume 55, Issue 3, Page(s) 355–364

Abstract: Background/aims: Colonoscopy is the gold standard diagnostic method for colorectal neoplasia, allowing detection and resection of adenomatous polyps; however, significant proportions of adenomas are missed. Computer-aided detection (CADe) systems in ... ...

Abstract	Background/aims: Colonoscopy is the gold standard diagnostic method for colorectal neoplasia, allowing detection and resection of adenomatous polyps; however, significant proportions of adenomas are missed. Computer-aided detection (CADe) systems in endoscopy are currently available to help identify lesions. Diminutive (≤5 mm) and nonpedunculated polyps are most commonly missed. This meta-analysis aimed to assess whether CADe systems can improve the real-time detection of these commonly missed lesions. Methods: A comprehensive literature search was performed. Randomized controlled trials evaluating CADe systems categorized by morphology and lesion size were included. The mean number of polyps and adenomas per patient was derived. Independent proportions and their differences were calculated using DerSimonian and Laird random-effects modeling. Results: Seven studies, including 2,595 CADe-assisted colonoscopies and 2,622 conventional colonoscopies, were analyzed. CADe-assisted colonoscopy demonstrated an 80% increase in the mean number of diminutive adenomas detected per patient compared with conventional colonoscopy (0.31 vs. 0.17; effect size, 0.13; 95% confidence interval [CI], 0.09-0.18); it also demonstrated a 91.7% increase in the mean number of nonpedunculated adenomas detected per patient (0.32 vs. 0.19; effect size, 0.05; 95% CI, 0.02-0.07). Conclusion: CADe-assisted endoscopy significantly improved the detection of most commonly missed adenomas. Although this method is a potentially exciting technology, limitations still apply to current data, prompting the need for further real-time studies.
Language	English
Publishing date	2022-05-12
Publishing country	Korea (South)
Document type	Journal Article
ZDB-ID	2643507-X
ISSN	2234-2443 ; 2234-2400
ISSN (online)	2234-2443
ISSN	2234-2400
DOI	10.5946/ce.2021.228
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Article ; Online: A YOLOv5-based network for the detection of a diffuse reflectance spectroscopy probe to aid surgical guidance in gastrointestinal cancer surgery.

Gkouzionis, Ioannis / Zhong, Yican / Nazarian, Scarlet / Darzi, Ara / Patel, Nisha / Peters, Christopher J / Elson, Daniel S

International journal of computer assisted radiology and surgery

2023 Volume 19, Issue 1, Page(s) 11–14

Abstract: Purpose: A positive circumferential resection margin (CRM) for oesophageal and gastric carcinoma is associated with local recurrence and poorer long-term survival. Diffuse reflectance spectroscopy (DRS) is a non-invasive technology able to distinguish ... ...

Abstract	Purpose: A positive circumferential resection margin (CRM) for oesophageal and gastric carcinoma is associated with local recurrence and poorer long-term survival. Diffuse reflectance spectroscopy (DRS) is a non-invasive technology able to distinguish tissue type based on spectral data. The aim of this study was to develop a deep learning-based method for DRS probe detection and tracking to aid classification of tumour and non-tumour gastrointestinal (GI) tissue in real time. Methods: Data collected from both ex vivo human tissue specimen and sold tissue phantoms were used for the training and retrospective validation of the developed neural network framework. Specifically, a neural network based on the You Only Look Once (YOLO) v5 network was developed to accurately detect and track the tip of the DRS probe on video data acquired during an ex vivo clinical study. Results: Different metrics were used to analyse the performance of the proposed probe detection and tracking framework, such as precision, recall, mAP 0.5, and Euclidean distance. Overall, the developed framework achieved a 93% precision at 23 FPS for probe detection, while the average Euclidean distance error was 4.90 pixels. Conclusion: The use of a deep learning approach for markerless DRS probe detection and tracking system could pave the way for real-time classification of GI tissue to aid margin assessment in cancer resection surgery and has potential to be applied in routine surgical practice.
MeSH term(s)	Humans ; Retrospective Studies ; Spectrum Analysis ; Gastrointestinal Neoplasms/diagnosis ; Gastrointestinal Neoplasms/surgery ; Neural Networks, Computer ; Digestive System Surgical Procedures
Language	English
Publishing date	2023-06-08
Publishing country	Germany
Document type	Journal Article
ZDB-ID	2365628-1
ISSN	1861-6429 ; 1861-6410
ISSN (online)	1861-6429
ISSN	1861-6410
DOI	10.1007/s11548-023-02944-9
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Article ; Online: The influence of procedural volume on short-term outcomes for robotic pancreatoduodenectomy-a cohort study and a learning curve analysis.

Kawka, Michal / Gall, Tamara M H / Hand, Fiona / Nazarian, Scarlet / Cunningham, David / Nicol, David / Jiao, Long R

Surgical endoscopy

2023 Volume 37, Issue 6, Page(s) 4719–4727

Abstract: Background: An increasing number of robotic pancreatoduodenectomies (RPD) are reported, however, questions remain on the number of procedures needed for gaining technical proficiency in RPD. Therefore, we aimed to assess the influence of procedure ... ...

Abstract	Background: An increasing number of robotic pancreatoduodenectomies (RPD) are reported, however, questions remain on the number of procedures needed for gaining technical proficiency in RPD. Therefore, we aimed to assess the influence of procedure volume on short-term RPD outcomes and assess the learning curve effect. Methods: A retrospective review of consecutive RPD cases was undertaken. Non-adjusted cumulative sum (CUSUM) analysis was performed to identify the procedure volume threshold, following which before-threshold and after-threshold outcomes were compared. Results: Since May 2017, 60 patients had undergone an RPD at our institution. The median operative time was 360 min (IQR 302.25-442 min). CUSUM analysis of operative time identified 21 cases as proficiency threshold, indicated by curve inflexion. Median operative time was significantly shorter after the threshold of 21 cases (470 vs 320 min, p < 0.001). No significant difference was found between before- and after-threshold groups in major Clavien-Dindo complications (23.8 vs 25.6%, p = 0.876). Conclusions: A decrease in operative time after 21 RPD cases suggests a threshold of technical proficiency potentially associated with an initial adjustment to new instrumentation, port placement and standardisation of operative step sequence. RPD can be safely performed by surgeons with prior laparoscopic surgery experience.
MeSH term(s)	Humans ; Cohort Studies ; Pancreaticoduodenectomy/methods ; Robotic Surgical Procedures/methods ; Learning Curve ; Retrospective Studies ; Operative Time ; Laparoscopy/methods
Language	English
Publishing date	2023-03-08
Publishing country	Germany
Document type	Journal Article
ZDB-ID	639039-0
ISSN	1432-2218 ; 0930-2794
ISSN (online)	1432-2218
ISSN	0930-2794
DOI	10.1007/s00464-023-09941-8
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Article ; Online: Real-time Tracking and Classification of Tumor and Nontumor Tissue in Upper Gastrointestinal Cancers Using Diffuse Reflectance Spectroscopy for Resection Margin Assessment.

Nazarian, Scarlet / Gkouzionis, Ioannis / Kawka, Michal / Jamroziak, Marta / Lloyd, Josephine / Darzi, Ara / Patel, Nisha / Elson, Daniel S / Peters, Christopher J

JAMA surgery

2022 Volume 157, Issue 11, Page(s) e223899

Abstract: Importance: Cancers of the upper gastrointestinal tract remain a major contributor to the global cancer burden. The accurate mapping of tumor margins is of particular importance for curative cancer resection and improvement in overall survival. Current ... ...

Abstract	Importance: Cancers of the upper gastrointestinal tract remain a major contributor to the global cancer burden. The accurate mapping of tumor margins is of particular importance for curative cancer resection and improvement in overall survival. Current mapping techniques preclude a full resection margin assessment in real time. Objective: To evaluate whether diffuse reflectance spectroscopy (DRS) on gastric and esophageal cancer specimens can differentiate tissue types and provide real-time feedback to the operator. Design, setting, and participants: This was a prospective ex vivo validation study. Patients undergoing esophageal or gastric cancer resection were prospectively recruited into the study between July 2020 and July 2021 at Hammersmith Hospital in London, United Kingdom. Tissue specimens were included for patients undergoing elective surgery for either esophageal carcinoma (adenocarcinoma or squamous cell carcinoma) or gastric adenocarcinoma. Exposures: A handheld DRS probe and tracking system was used on freshly resected ex vivo tissue to obtain spectral data. Binary classification, following histopathological validation, was performed using 4 supervised machine learning classifiers. Main outcomes and measures: Data were divided into training and testing sets using a stratified 5-fold cross-validation method. Machine learning classifiers were evaluated in terms of sensitivity, specificity, overall accuracy, and the area under the curve. Results: Of 34 included patients, 22 (65%) were male, and the median (range) age was 68 (35-89) years. A total of 14 097 mean spectra for normal and cancerous tissue were collected. For normal vs cancer tissue, the machine learning classifier achieved a mean (SD) overall diagnostic accuracy of 93.86% (0.66) for stomach tissue and 96.22% (0.50) for esophageal tissue and achieved a mean (SD) sensitivity and specificity of 91.31% (1.5) and 95.13% (0.8), respectively, for stomach tissue and of 94.60% (0.9) and 97.28% (0.6) for esophagus tissue. Real-time tissue tracking and classification was achieved and presented live on screen. Conclusions and relevance: This study provides ex vivo validation of the DRS technology for real-time differentiation of gastric and esophageal cancer from healthy tissue using machine learning with high accuracy. As such, it is a step toward the development of a real-time in vivo tumor mapping tool for esophageal and gastric cancers that can aid decision-making of resection margins intraoperatively.
MeSH term(s)	Humans ; Male ; Aged ; Aged, 80 and over ; Female ; Margins of Excision ; Esophageal Neoplasms/diagnosis ; Esophageal Neoplasms/surgery ; Prospective Studies ; Stomach Neoplasms/diagnosis ; Stomach Neoplasms/surgery ; Spectrum Analysis/methods ; Adenocarcinoma/diagnosis ; Adenocarcinoma/surgery ; Upper Gastrointestinal Tract/pathology
Language	English
Publishing date	2022-11-09
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2701841-6
ISSN	2168-6262 ; 2168-6254
ISSN (online)	2168-6262
ISSN	2168-6254
DOI	10.1001/jamasurg.2022.3899
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