Literature DB >> 23194044

Root cause analysis of problems in the frozen section diagnosis of in situ, minimally invasive, and invasive adenocarcinoma of the lung.

Ann E Walts1, Alberto M Marchevsky.   

Abstract

CONTEXT: Frozen sections can help determine the extent of surgery by distinguishing in situ, minimally invasive, and invasive adenocarcinoma of the lung.
OBJECTIVE: To evaluate our experience with the frozen section diagnosis of these lesions using root-cause analysis.
DESIGN: Frozen sections from 224 consecutive primary pulmonary adenocarcinomas (in situ, 27 [12.1%]; minimally invasive, 46 [20.5%]; invasive, 151 [67.4%]) were reviewed. Features that could have contributed to frozen section errors and deferrals were evaluated.
RESULTS: There were no false-positive diagnoses of malignancy. Frozen section errors and deferrals were identified in 12.1% (27 of 224) and 6.3% (14 of 224) of the cases, respectively. Significantly more errors occurred in the diagnosis of in situ and minimally invasive adenocarcinoma than in the diagnosis of invasive adenocarcinoma (P < .001). Frozen section errors and deferrals were twice as frequent in lesions smaller than 1.0 cm (P = .09). Features significantly associated with errors and deferrals included intraoperative consultation by more than one pathologist (P = .003) and more than one sample of frozen lung section (P = .001). Inflammation with reactive atypia, fibrosis/scar, sampling problems, and suboptimal quality sections were identified in 51.2% (21 of 41), 36.6% (15 of 41), 26.8% (11 of 41), and 9.8% (4 of 41) of the errors and deferrals, respectively (more than one of these factors was identified in some cases). Frozen section errors and deferrals had significant clinical impact in only 4 patients (1.8%); each had to undergo completion video-assisted thoracoscopic lobectomy less than 90 days after the initial surgery.
CONCLUSIONS: The distinction of in situ from minimally invasive adenocarcinoma is difficult in both frozen and permanent sections. We identified several technical and interpretive features that likely contributed to frozen section errors and deferrals and suggest practice modifications that are likely to improve diagnostic accuracy.

Entities:  

Mesh:

Year:  2012        PMID: 23194044     DOI: 10.5858/arpa.2012-0042-OA

Source DB:  PubMed          Journal:  Arch Pathol Lab Med        ISSN: 0003-9985            Impact factor:   5.534


  17 in total

1.  A random forest algorithm predicting model combining intraoperative frozen section analysis and clinical features guides surgical strategy for peripheral solitary pulmonary nodules.

Authors:  Liqiang Qian; Yinjie Zhou; Wanqin Zeng; Xiaoke Chen; Zhengping Ding; Yujia Shen; Yifeng Qian; Davide Tosi; Mario Silva; Yuchen Han; Xiaolong Fu
Journal:  Transl Lung Cancer Res       Date:  2022-06

2.  3D Specimen Mapping Expedites Frozen Section Diagnosis of Nonpalpable Ground Glass Opacities.

Authors:  Gregory T Kennedy; Feredun S Azari; Elizabeth Bernstein; Charuhas Desphande; Azra Din; Isvita Marfatia; John C Kucharczuk; Edward J Delikatny; Philip S Low; Sunil Singhal
Journal:  Ann Thorac Surg       Date:  2021-11-10       Impact factor: 5.102

3.  Using frozen section to identify histological patterns in stage I lung adenocarcinoma of ≤ 3 cm: accuracy and interobserver agreement.

Authors:  Yi-Chen Yeh; Jun-ichi Nitadori; Kyuichi Kadota; Akihiko Yoshizawa; Natasha Rekhtman; Andre L Moreira; Camelia S Sima; Valerie W Rusch; Prasad S Adusumilli; William D Travis
Journal:  Histopathology       Date:  2015-02-05       Impact factor: 5.087

Review 4.  What we know about surgical therapy in early-stage non-small-cell lung cancer: a guide for the medical oncologist.

Authors:  Sassine Ghanem; Sandy El Bitar; Sami Hossri; Chanudi Weerasinghe; Jean Paul Atallah
Journal:  Cancer Manag Res       Date:  2017-07-06       Impact factor: 3.989

5.  The combined nomogram based on the CT features may be used as a complementary method of frozen sections to predict invasive lung adenocarcinoma manifesting as ground-glass nodules.

Authors:  Yangyang Sun; Bin Wang; Ke Bi; Xue Meng; Lei Zhang; Xiwen Sun
Journal:  J Thorac Dis       Date:  2020-05       Impact factor: 2.895

6.  3D convolutional neural network for differentiating pre-invasive lesions from invasive adenocarcinomas appearing as ground-glass nodules with diameters ≤3 cm using HRCT.

Authors:  Shengping Wang; Rui Wang; Shengjian Zhang; Ruimin Li; Yi Fu; Xiangjie Sun; Yuan Li; Xing Sun; Xinyang Jiang; Xiaowei Guo; Xuan Zhou; Jia Chang; Weijun Peng
Journal:  Quant Imaging Med Surg       Date:  2018-06

7.  Rapid Diagnosis of Lung Tumors, a Feasability Study Using Maldi-Tof Mass Spectrometry.

Authors:  Geoffrey Brioude; Fabienne Brégeon; Delphine Trousse; Christophe Flaudrops; Véronique Secq; Florence De Dominicis; Eric Chabrières; Xavier-Benoit D'journo; Didier Raoult; Pascal-Alexandre Thomas
Journal:  PLoS One       Date:  2016-05-26       Impact factor: 3.240

Review 8.  Clinicopathological Characteristics and Mutations Driving Development of Early Lung Adenocarcinoma: Tumor Initiation and Progression.

Authors:  Kentaro Inamura
Journal:  Int J Mol Sci       Date:  2018-04-23       Impact factor: 5.923

Review 9.  [Strategies of Individual Surgical Treatment for Early Stage Non-small Cell Lung Cancer and the Guidance of Intraoperative Frozen Pathology].

Authors:  Bin Hu; Qiang Li
Journal:  Zhongguo Fei Ai Za Zhi       Date:  2016-06-20

10.  An effective inflation treatment for frozen section diagnosis of small-sized lesions of the lung.

Authors:  Zhenzhen Xiang; Jie Zhang; Jikai Zhao; Jinchen Shao; Lanxiang Zhao; Ye Zhang; Gang Qin; Jie Xing; Yuchen Han; Keke Yu
Journal:  J Thorac Dis       Date:  2020-04       Impact factor: 2.895

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