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Full-field optical coherence tomography for the analysis of fresh unstained human lobectomy specimens.

Jain M, Narula N, Salamoon B, Shevchuk MM, Aggarwal A, Altorki N, Stiles B, Boccara C, Mukherjee S - J Pathol Inform (2013)

Bottom Line: Further analysis of these images revealed two major confounding features: (a) Extensive lung collapse and (b) presence of smoker's macrophages.We posit that greater pathologist experience, complemented with morphometric analysis and color-coding of image components, may help minimize the contribution of these confounders in the future.We foresee its potential as an adjunct to intra-surgical frozen section analysis for margin assessment, especially in limited lung resections.

View Article: PubMed Central - PubMed

Affiliation: Department of Urology, Weill Medical College of Cornell University, New York, USA ; Department of Biochemistry, Weill Medical College of Cornell University, New York, USA.

ABSTRACT

Background: Full-field optical coherence tomography (FFOCT) is a real-time imaging technique that generates high-resolution three-dimensional tomographic images from unprocessed and unstained tissues. Lack of tissue processing and associated artifacts, along with the ability to generate large-field images quickly, warrants its exploration as an alternative diagnostic tool.

Materials and methods: One section each from the tumor and from adjacent non-neoplastic tissue was collected from 13 human lobectomy specimens. They were imaged fresh with FFOCT and then submitted for routine histopathology. Two blinded pathologists independently rendered diagnoses based on FFOCT images.

Results: Normal lung architecture (alveoli, bronchi, pleura and blood vessels) was readily identified with FFOCT. Using FFOCT images alone, the study pathologists were able to correctly identify all tumor specimens and in many cases, the histological subtype of tumor (e.g., adenocarcinomas with various patterns). However, benign diagnosis was provided with high confidence in roughly half the tumor-free specimens (others were diagnosed as equivocal or false positive). Further analysis of these images revealed two major confounding features: (a) Extensive lung collapse and (b) presence of smoker's macrophages. On a closer inspection, however, the smoker's macrophages could often be identified as distinct from tumor cells based on their relative location in the alveoli, size and presence of anthracosis. We posit that greater pathologist experience, complemented with morphometric analysis and color-coding of image components, may help minimize the contribution of these confounders in the future.

Conclusion: Our study provides evidence for the potential utility of FFOCT in identifying and differentiating lung tumors from non-neoplastic lung tissue. We foresee its potential as an adjunct to intra-surgical frozen section analysis for margin assessment, especially in limited lung resections.

No MeSH data available.


Related in: MedlinePlus

Comparative full-field optical coherence tomography (FFOCT) and H&E images of non-neoplastic lung. (a, b) Large-field images show lung parenchyma composed of alveoli (signal void areas; arrows) surrounded by pleura (connective tissue-bright signals; arrowheads). Some thickening of the alveolar septa is shown (right arrow). (c, d) Images of blood vessel (arrowheads) and surrounding alveoli (arrows). (e, f) Images of a bronchus, with columnar epithelial lining (box and inset) and underlying connective tissue (connective tissue-bright signal). (Scale bars for FFOCT: (a) 1 mm; (c, e) 0.5 mm. Inset in (e) 0.1 mm. H&E total magnifications: (b) ×40 and (d, f) ×200. Inset in (f) = ×2.5 zoom)
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Figure 2: Comparative full-field optical coherence tomography (FFOCT) and H&E images of non-neoplastic lung. (a, b) Large-field images show lung parenchyma composed of alveoli (signal void areas; arrows) surrounded by pleura (connective tissue-bright signals; arrowheads). Some thickening of the alveolar septa is shown (right arrow). (c, d) Images of blood vessel (arrowheads) and surrounding alveoli (arrows). (e, f) Images of a bronchus, with columnar epithelial lining (box and inset) and underlying connective tissue (connective tissue-bright signal). (Scale bars for FFOCT: (a) 1 mm; (c, e) 0.5 mm. Inset in (e) 0.1 mm. H&E total magnifications: (b) ×40 and (d, f) ×200. Inset in (f) = ×2.5 zoom)

Mentions: To assess the ability of FFOCT to identify lung tumor, we first assessed the images from the non-neoplastic lung tissue adjacent to the tumor. In non-neoplastic lung tissue, we could easily recognize the typical lace-like pattern of lung parenchyma formed by alveoli (signal-void dark areas), along with their septal walls (bright signal) [Figure 2a and b]. Since the non-neoplastic tissues were taken from an area adjacent to lung tumor, some emphysematous changes (loss and thickening of the alveolar septa) were observed in these sections [Figure 2a and b]. We could also readily identify the following other major normal lung components: (A) Pleura, which is rich in connective tissue and produces a bright signal [Figure 2a and b]; (B) blood vessels [Figure 2c and d] and (C) bronchi, with their columnar epithelial lining (the cells generating a dull gray signal) [Figure 2e and f].


Full-field optical coherence tomography for the analysis of fresh unstained human lobectomy specimens.

Jain M, Narula N, Salamoon B, Shevchuk MM, Aggarwal A, Altorki N, Stiles B, Boccara C, Mukherjee S - J Pathol Inform (2013)

Comparative full-field optical coherence tomography (FFOCT) and H&E images of non-neoplastic lung. (a, b) Large-field images show lung parenchyma composed of alveoli (signal void areas; arrows) surrounded by pleura (connective tissue-bright signals; arrowheads). Some thickening of the alveolar septa is shown (right arrow). (c, d) Images of blood vessel (arrowheads) and surrounding alveoli (arrows). (e, f) Images of a bronchus, with columnar epithelial lining (box and inset) and underlying connective tissue (connective tissue-bright signal). (Scale bars for FFOCT: (a) 1 mm; (c, e) 0.5 mm. Inset in (e) 0.1 mm. H&E total magnifications: (b) ×40 and (d, f) ×200. Inset in (f) = ×2.5 zoom)
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3814996&req=5

Figure 2: Comparative full-field optical coherence tomography (FFOCT) and H&E images of non-neoplastic lung. (a, b) Large-field images show lung parenchyma composed of alveoli (signal void areas; arrows) surrounded by pleura (connective tissue-bright signals; arrowheads). Some thickening of the alveolar septa is shown (right arrow). (c, d) Images of blood vessel (arrowheads) and surrounding alveoli (arrows). (e, f) Images of a bronchus, with columnar epithelial lining (box and inset) and underlying connective tissue (connective tissue-bright signal). (Scale bars for FFOCT: (a) 1 mm; (c, e) 0.5 mm. Inset in (e) 0.1 mm. H&E total magnifications: (b) ×40 and (d, f) ×200. Inset in (f) = ×2.5 zoom)
Mentions: To assess the ability of FFOCT to identify lung tumor, we first assessed the images from the non-neoplastic lung tissue adjacent to the tumor. In non-neoplastic lung tissue, we could easily recognize the typical lace-like pattern of lung parenchyma formed by alveoli (signal-void dark areas), along with their septal walls (bright signal) [Figure 2a and b]. Since the non-neoplastic tissues were taken from an area adjacent to lung tumor, some emphysematous changes (loss and thickening of the alveolar septa) were observed in these sections [Figure 2a and b]. We could also readily identify the following other major normal lung components: (A) Pleura, which is rich in connective tissue and produces a bright signal [Figure 2a and b]; (B) blood vessels [Figure 2c and d] and (C) bronchi, with their columnar epithelial lining (the cells generating a dull gray signal) [Figure 2e and f].

Bottom Line: Further analysis of these images revealed two major confounding features: (a) Extensive lung collapse and (b) presence of smoker's macrophages.We posit that greater pathologist experience, complemented with morphometric analysis and color-coding of image components, may help minimize the contribution of these confounders in the future.We foresee its potential as an adjunct to intra-surgical frozen section analysis for margin assessment, especially in limited lung resections.

View Article: PubMed Central - PubMed

Affiliation: Department of Urology, Weill Medical College of Cornell University, New York, USA ; Department of Biochemistry, Weill Medical College of Cornell University, New York, USA.

ABSTRACT

Background: Full-field optical coherence tomography (FFOCT) is a real-time imaging technique that generates high-resolution three-dimensional tomographic images from unprocessed and unstained tissues. Lack of tissue processing and associated artifacts, along with the ability to generate large-field images quickly, warrants its exploration as an alternative diagnostic tool.

Materials and methods: One section each from the tumor and from adjacent non-neoplastic tissue was collected from 13 human lobectomy specimens. They were imaged fresh with FFOCT and then submitted for routine histopathology. Two blinded pathologists independently rendered diagnoses based on FFOCT images.

Results: Normal lung architecture (alveoli, bronchi, pleura and blood vessels) was readily identified with FFOCT. Using FFOCT images alone, the study pathologists were able to correctly identify all tumor specimens and in many cases, the histological subtype of tumor (e.g., adenocarcinomas with various patterns). However, benign diagnosis was provided with high confidence in roughly half the tumor-free specimens (others were diagnosed as equivocal or false positive). Further analysis of these images revealed two major confounding features: (a) Extensive lung collapse and (b) presence of smoker's macrophages. On a closer inspection, however, the smoker's macrophages could often be identified as distinct from tumor cells based on their relative location in the alveoli, size and presence of anthracosis. We posit that greater pathologist experience, complemented with morphometric analysis and color-coding of image components, may help minimize the contribution of these confounders in the future.

Conclusion: Our study provides evidence for the potential utility of FFOCT in identifying and differentiating lung tumors from non-neoplastic lung tissue. We foresee its potential as an adjunct to intra-surgical frozen section analysis for margin assessment, especially in limited lung resections.

No MeSH data available.


Related in: MedlinePlus