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Record W3108008106 · doi:10.1016/j.xjtc.2020.11.027

Commentary: Finding a needle in a haystack—technology and innovation for precise intraoperative localization of deep-seated pulmonary nodules

2020· editorial· en· W3108008106 on OpenAlex
Taha Huseini, Moïshe Liberman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJTCVS Techniques · 2020
Typeeditorial
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHaystackFiducial markerFluoroscopyMedicineRadiologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Central MessageIntraoperative localization of small, deep pulmonary nodules can be technically challenging. The use of a radiofrequency identification system may be a promising option to localize deep lesions.See Article page 301 in the December 2020 issue. Intraoperative localization of small, deep pulmonary nodules can be technically challenging. The use of a radiofrequency identification system may be a promising option to localize deep lesions. See Article page 301 in the December 2020 issue. Video-assisted thoracoscopic surgery without adjunctive localization techniques is best used for medium- to large-sized nodules located superficially or close to the pleural surface, because of the ability to visually inspect or palpate these lesions.1Bernard A. Resection of pulmonary nodules using video-assisted thoracic surgery. The thorax group.Ann Thorac Surg. 1996; 61 (discussion: 204-5): 202-204Abstract Full Text PDF PubMed Scopus (104) Google Scholar For deeper nodules, accurate localization can be challenging, and various techniques have been used preoperatively, including the use of hook wires, fiducial markers, micro-coils, injected dyes, and fluoroscopy.1Bernard A. Resection of pulmonary nodules using video-assisted thoracic surgery. The thorax group.Ann Thorac Surg. 1996; 61 (discussion: 204-5): 202-204Abstract Full Text PDF PubMed Scopus (104) Google Scholar, 2Sharma A. McDermott S. Mathisen D.J. Shepard J.O.A. Preoperative localization of lung nodules with fiducial markers: feasibility and technical considerations.Ann Thorac Surg. 2017; 103: 1114-1120Abstract Full Text Full Text PDF PubMed Scopus (31) Google Scholar, 3Zaman M. Bilal H. Woo C.Y. Tang A. In patients undergoing video-assisted thoracoscopic surgery excision, what is the best way to locate a subcentimetre solitary pulmonary nodule in order to achieve successful excision?.Interact Cardiovasc Thorac Surg. 2012; 15: 266-272Crossref PubMed Scopus (86) Google Scholar The choice of technique depends on its availability, safety, operator experience, hospital resource availability, and cost- and time-effectiveness. We read with great interest and congratulate Sato and colleagues4Sato T. Yutaka Y. Nakamura T. Date H. First clinical application of radiofrequency identification (RFID) marking system—precise localization of a small lung nodule.J Thorac Cardiovasc Surg Tech. 2020; 4: 301-304Google Scholar on their article on clinical application of a radiofrequency identification (RFID) marking system. The authors propose a novel technique to precisely locate small pulmonary nodules intraoperatively based on RFID technology. In their technique, a radiofrequency tag is inserted under virtual bronchoscopy and fluoroscopic guidance in proximity to the target lesion, the position of which is then confirmed with cone beam computed tomography. This tag communicates with an antenna to aid localization of the nodule intraoperatively and allow successful wedge resection with clear margins. The authors have indeed made an important contribution, given that there is no gold standard for precisely locating small pulmonary nodules before surgical resection. Accurate localization of the target lesion is of high importance, since adequate wedge resection with clear margins may reduce the risk of disease recurrence.5Wolf A.S. Swanson S.J. Yip R. Liu B. Tarras E.S. Yankelevitz D.F. et al.The impact of margins on outcomes after wedge resection for stage I non–small cell lung cancer.Ann Thorac Surg. 2017; 104: 1171-1178Abstract Full Text Full Text PDF PubMed Scopus (39) Google Scholar This technology has several positive attributes, including its potential relative simplicity, accuracy, and low risk in terms of complications. However, some key clinical aspects need to be taken into consideration before further clinical extrapolation of this novel technique for intraoperative localization of small lung nodules. First, the entire procedure including setup can be time-consuming, which could limit the number of procedures that can be performed and prolong the waiting period for critical surgeries, especially in high- volume centers. Second, the authors describe only a single case; widespread application will require larger series of cases with evaluation of accuracy, risk, marker displacement, and reproducibility. Furthermore, if a tissue diagnosis is obtained before surgery, it would be interesting to see whether the tag can be inserted during the same procedure to save cost and time. Other important limitations to widespread application of this technique is the requirement for both a virtual bronchoscopic system, cone beam computed tomography availability in the operating room, and the training, experience, and skill set required to accurately use these systems. As we enter the era of increased ground glass opacity detection, lung cancer screening with resulting small nodules and an increased incidence of benign nodules and surgery for patients with limited pulmonary function with intraoperative localization techniques is becoming increasingly important. RFID marking may be an important adjunct to intraoperative localization to help us find that “needle in a haystack.” First clinical application of radiofrequency identification (RFID) marking system—Precise localization of a small lung noduleJTCVS TechniquesVol. 4PreviewPrecise small lung nodule resection is challenging in minimally invasive thoracoscopic surgery. Various methods that help surgeons to locate the target nodule have been devised; however, the ideal way that satisfies the demand has not yet been realized. We have developed and applied a novel marking system to localize small lung nodules for the first time in humans. Full-Text PDF Open Access

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.594
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.319
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it