EUS-guided FNA of solid pancreatic masses: a learning curve with 300 consecutive procedures

Eloubeidi, Mohamad A.; Tamhane, Ashutosh

doi:10.1016/s0016-5107(05)00363-9

Cited by 165 publications

(130 citation statements)

References 24 publications

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“…Of the main imaging modalities employed to detect IPMN (computed tomography, endoscopic retrograde cholangiopancreatography, magnetic resonance cholangiopancreatography, and endoscopic ultrasonography (EUS)), EUS offers the highest resolution [3] and enables a cytologic diagnosis of IPMN via fine-needle aspiration (EUS-FNA). However, the sensitivity of EUS-FNA cytology diagnosis is low (44-75%) [4,5] and the technique suffers from a steep learning curve and high inter-operator variability [6]. Thus, the effectiveness of identifying cancer precursor lesions such as IPMN could be improved by developing a more sensitive and quantitative detection method.…”

Section: Introductionmentioning

confidence: 99%

Characterizing human pancreatic cancer precursor using quantitative tissue optical spectroscopy

Lee

Lloyd

Chandra

et al. 2013

Biomed. Opt. Express

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Abstract:In a pilot study, multimodal optical spectroscopy coupled with quantitative tissue-optics models distinguished intraductal papillary mucinous neoplasm (IPMN), a common precursor to pancreatic cancer, from normal tissues in freshly excised human pancreas. A photon-tissue interaction (PTI) model extracted parameters associated with cellular nuclear size and refractive index (from reflectance spectra) and extracellular collagen content (from fluorescence spectra). The results suggest that tissue optical spectroscopy has the potential to characterize pre-cancerous neoplasms in human pancreatic tissues.

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Section: Introductionmentioning

confidence: 99%

Characterizing human pancreatic cancer precursor using quantitative tissue optical spectroscopy

Lee

Lloyd

Chandra

et al. 2013

Biomed. Opt. Express

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“…For example, in surgical procedures how fast trainees achieve the ability to get surgery adequately performed without complications [42,43] . Also in endoscopy some reports use colonoscopy models [44] and endoscopic ultrasound fine needle aspiration [45] with similar methodology. A single report exists on the learning curve for the diagnostic performance of endoscopy.…”

Section: Discussionmentioning

confidence: 99%

Web-based system for training and dissemination of a magnification chromoendoscopy classification

Dinis-Ribeiro¹,

Cruz‐Correia²,

Costa-Santos³

et al. 2008

WJG

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AIM:To evaluate the use of web-based technologies to assess the learning curve and reassess reproducibility of a simplified version of a classification for gastric magnification chromoendoscopy (MC). METHODS: As part of a multicenter trial, a hybrid approach was taken using a CD-ROM, with 20 films of MC lasting 5 s each and an "autorun" file triggering a local HTML frameset referenced to a remote questionnaire through an Internet connection. Three endoscopists were asked to prospectively and independently classify 10 of these films randomly selected with at least 3 d apart. The answers were centrally stored and returned to participants together with adequate feedback with the right answer. RESULTS: For classification in 3 groups, both intra-[Cohen's kappa (κ) = 0.79-1.00 to 0.89-1.00] and inter-observer agreement increased from 1st (moderate) to 6th observation (κ = 0.94). Also, agreement with reference increased in the last observations (0.90, 1.00 and 1.00, for observers A, B and C, respectively). Validity of 100% was obtained by all observers at their 4th observation. When a 4th (sub)group was considered, inter-observer agreement was almost perfect (κ = 0.92) at 6th observation. The relation with reference clearly improved into κ (0.93-1.00) and sensitivity (75%-100%) at their 6th observations. CONCLUSION: This MC classification seems to be easily explainable and learnable as shown by excellent intra-and inter-observer agreement, and improved agreement with reference. A web system such as the one used in this study may be useful for endoscopic or other image based diagnostic procedures with respect to definition, education and dissemination.

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“…Summarizing the results of 23 studies including 1,096 patients over a 21-year period, the sensitivity of EUS for the detection of a pancreatic mass was in the range of 85-100%. (Al-Haddad & Eloubeidi, 2010;Yasuda et al, 1988;DeWitt et al, 2004;Chhieng et al, 2002;Eloubeidi & Tamhane, 2005) The operating characteristics of EUS-FNA of solid pancreatic masses in 547 patients were: sensitivity 95%, specificity 92%, positive predictive value 98% and negative predictive value 80%, with and overall accuracy of 94.1%. (Eloubeidi et al, 2007) Such accuracy numbers allow for preoperative counseling of patients, minimizing surgeon's operative time in cases of unresectable disease, and avoiding surgical biopsies in those with inoperable disease, also allowing for conservative management of patients with benign pathology results.…”

Section: Diagnosis and Stagingmentioning

confidence: 99%

Endoscopic Management of Pancreatic Cancer: From Diagnosis to Palliative Therapy

Madrigal¹,

Chennat²

2012

Pancreatic Cancer - Clinical Management

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EUS-guided FNA of solid pancreatic masses: a learning curve with 300 consecutive procedures

Cited by 165 publications

References 24 publications

Characterizing human pancreatic cancer precursor using quantitative tissue optical spectroscopy

Characterizing human pancreatic cancer precursor using quantitative tissue optical spectroscopy

Web-based system for training and dissemination of a magnification chromoendoscopy classification

Endoscopic Management of Pancreatic Cancer: From Diagnosis to Palliative Therapy

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