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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5528_Библиотеки_им_академика_М_И_Перельмана.pdf
160 M. Jain
(a) (b) (c) (d)
(e) (f ) (g) (h)
(i) (j) (k) (l)
Figure 2. Comparative multiphoton microscopy (MPM) and hematoxylin-eosin images of nonneoplastic lung. (a, b) Low-magnification images show lung parenchyma composed of alveoli (arrows)
surrounded by pleura (arrowheads). Inset in MPM shows pleura with collagen (red) and elastin (green)
components. (c, d) High-magnification images show primarily elastin fibers, with some collagen in
the septal wall (arrowheads) of the alveoli (arrows). (e, f) Low-magnification i mages show bronchus
(*) with cartilage (arrowheads) and a medium-sized blood vessel (arrows). (g, h) High-magnification
images show columnar lining of the bronchus (arrows) and underlying connective tissue (arrowheads).
MPM, original magnifications × 48 (a and e), × 96 (a inset), and × 300 (c, g); hematoxylin-eosin,
original magnifications × 40 (b, f) and × 200 (d, h). Figure reproduced with permission, courtesy of
Archives of Pathology and Laboratory Medicine.
et al.
4
signal (color-coded green) can be easily separated from the intima and
adventitia (SHG signal; color-coded red).
All the normal structures identified with FFOCT (Figure 1(a, c, e))
and MPM images (Figure 2(a, c, e, g)) are shown in the corresponding h
& e-stained slides (Figure 1(b, d, f) and Figure 2(b, d, f, h)) prepared from
the same specimens. Nucleus usually appears dark with both FFOCT and
MPM as no exogenous nuclear dye or contrast agents are used with these
two techniques.
Lungs 161
(c) (d)
Figure 3. FCM images of tissue sections ofnormal lung (c) and the correspondinghematoxylin-eosinstained tissue section (d) (original magnific ations × 100 [d]). Figure reproduced with permission,
courtesy of Archives of Pathology and Laboratory Medicine.
5
Similar to FFOCT and MPM, FCM has shown the capability of identifying normal lung parenchyma. However,unlike FFOCT and MPM images
where the nucleus appears dark, nuclear staining from the acridine orange
provides necessary contrast (bright nucleus) between the nuclear and cytoplasmic areas of the cell (Figure 3).
FFOCT, MPM, and FCM can diagnose lung cancers in ex vivo tissue
The three main subtypes of non-small-cell lung cancer (NSCLC) are adenocarcinoma, squamous cell carcinoma, and large-cell carcinoma. Lung
adenocarcinoma is histologically heterogeneous with 5 distinct growth pat-
17–19
terns: lepidic, acinar, papillary, micropapillary, and solid patterns.
The
lepidic growth pattern consists of a single-cell layer of atypical cells growing along the alveolar septa.
FFOCT can identify varioushistomorphologic growthpatterns of lung
adenocarcinoma
3
(see Figure 4).Specifically,the adenocarcinoma with lepidic growth pattern can be easily distinguishable from the adenocarcinomas
with a solid growth pattern.
Additionally, due to a higher cellular resolution obtained with MPM,
identification of atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), and invasive adenocarcinoma is feasible (Figure 5).
An incidental AAH identified on MPM in tumor-free lung tissue is shown
in Figure 5(a–b). Proliferation of atypical pneumocytes along the preexisting alveolar wall is highlighted with gaps between the cells (discontinuous
162 M. Jain
(a) (b)
(c) (d)
Figure 4. Comparative full-field optical coherence tomography (FFOCT) and H&E images of neoplastic lung. (a, b) Images of adenocarcinoma of lung with lepidic-predominant pattern. Boxed areas
and insets show tumor cells lining the alveolar septa. (c, d) Images of adenocarcinoma of lung with
solid-predominant pattern. Boxed areas and insets show clusters of tumor cells. (Scale bars for
FFOCT: (a, c) 1 mm. Insets in (a, c) 0.1 mm. H&E total magnifications: (b, d) × 100. Insets: (b, d) ×
200). Figure reproduced with permission, courtesy of the Journal of Pathology Informatics.
et al.
3
layer of pneumocytes) to support the diagnosis of AAH. Adenocarcinoma
of lung with a lepidic predominant pattern, in contrast, shows continuous proliferation of tumor cells along the alveolar wall. In addition, some
free-floating tumor cells are visible in the airspace, the presence of which
precludes its classification as AIS (Figure 5(a–b)).
Adenocarcinomas with an acinar pattern show duct-likestructures and
irregularly angulated and often complex branching glands. Cohesive sheets
of tumor cells with nest-like architecture or single-tumor cells are considered solid growth patterns. Invasive adenocarcinoma with acinar pattern
(Figure 5(e–f))shows round to ovalmalignant glands (autofluorescence signal; color-coded green) invading the stroma (SHG signal; color-coded red)
Lungs 163
(a) (b) (c) (d)
(e) (f) (g) (h)
(i) (j) (k) (l)
Figure 5. Comparative multiphoton microscopy and hematoxylin-eosin images showing progression from atypical lesion to various patterns of invasive adenocarcinoma of lung. (a, b) Images of
atypical adenomatous hyperplasia show a focus on pneumocyte proliferation (cuboidal cells with
gaps between them) along the alveolar wall (arrows and insets). (c, d) Images of adenocarcinoma
of lung with lepidic-predominant pattern (arrows) and a few clusters of free-floating tumor cells
(arrowheads). (e, f) Images of adenocarcinoma of lung with acinar-predominant pattern (arrows).
(g, h) Images showing solid pattern (arrows) with suggestion of gland formation (arrowheads).
(i, j) Images showing papillary pattern (papillae with fibrovascular core; arrows). (k, l) Images showing micropapillary pattern, with complete destruction of normal lung parenchyma. The airspace
shows small papillary clusters of tumor cells (arrows) lacking true fibrovascular cores (multiphoton
microscopy, original magnifications × 300 (a, c, e, g, i, and k) and × 600 [inset]; hematoxylin-eosin,
original magnifications × 200 (b, d, f, h, j, and l) × 400 [inset]). Figure reproduced with permission,
courtesy of Archives of Pathology and Laboratory Medicine.
4
and a solid pattern (Figure 5(g–h)) shows sheets of malignant cells (autofluorescence signal; color-coded green) by MPM. It is difficult to differentiate
the solid pattern of adenocarcinoma from squamous cell carcinoma, large
cell carcinoma, and neuroendocrine carcinoma by these imaging modalities. Future studies involving various subtypes of lung cancer with solid
164 M. Jain
et al.
growth patterns are needed in order to assess the ability of MPM in differentiating these subtypes.
The papillary growth pattern is characterized by central fibrovascular stromal cores, whereas the micropapillary growth pattern is defined
by stroma-free micropapillae frequently present in the alveolar spaces.
MPM shows adenocarcinoma with a papillary-predominant pattern (Figure 5(i–j)) with clear papillary projections composed of cuboidal to columnar cells (autofluorescence signal from cell cytoplasm; color-coded green),
which line collagen-rich fibrovascular cores (SHG s ignal; color-coded
red). Micropapillary adenocarcinoma (Figure 5(k–l)), on the other hand,
shows small papillary clusters of malignant cells (autofluorescence signal
from cell cytoplasm; color-coded green) within the airspace, with no true
fibrovascular cores. Of note, MPM imaging allows for a clear visual distinction between the papillary and micropapillary growth patterns, which
have important prognostic implications. The micropapillary subtype is
considered to be poorly differentiated and has been associated with a worse
prognosis.
Squamous-cell carcinoma (SCC), the second most common nonsmall-cell carcinoma, accounts for about 30% of lung cancers. They typically occur centrally close to large airways and by H&E are composed
of sheets or islands of large polygonal cells with keratinization (in the
more differentiated forms) and intercellular bridges. Figure 6 shows highmagnification MPM images from the tumor in a patient with a diagnosis of
SCC. Figure6(a–b) demonstrate sheets ofmalignant cells (autofluorescence
signal from cell cytoplasm; color-coded green) with a complete loss of the
normal architecture of the lung parenchyma. Tumor cells are arranged in a
pavement-like fashion which is characteristicof SCC. An increased amount
of stroma (SHG signal; color-coded red) and mononuclear inflammatory
cells (autofluorescence signal; color-coded green) surrounding the tumor
were also noted (Figure 6(a), inset). Review of the H&E (Figure 6(b))
confirmed a correct diagnosis of SCC. Figure 6(c) and (d) show images
from the tumor (autofluorescence signal from cell cytoplasm; color-coded
green) of another subject, also diagnosed with SCC on H&E. However, it
was misdiagnosed as adenocarcinoma on MPM, primarily due to the central
necrosis in the tumor nest which was misinterpreted as gland formation.
Lungs 165
(a) (b)
(c) (d)
Figure 6. Comparative multiphoton microscopy and hematoxylin-eosin images of squamous cell
carcinoma of the lung. (a, b) Images of squamous cell carcinoma (SCC) of the lung showing sheets
of malignant cells with high nuclear to cytoplasmic ratio (arrows), surrounded by lymphocytes (arrowheads) interspersed in collagen bundles (inset). (c, d) Images of SCC of the lung showing pavementlike arrangement of the cells (arrows). Also shown is a nest of squamous cells with focal necrosis
(arrowheads) forming pseudoglands, leading to a misdiagnosis of adenocarcinoma (multiphoton
microscopy, original magnifications × 300 (a and c) and × 600 [inset]; hematoxylin-eosin, original magnifications × 200 (b and d)). Figure reproduced with permission, courtesy of Archives of
Pathology and Laboratory Medicine.
4
When the images were reanalyzed with knowledge of the SCC diagnosis,
the pavement-like arrangement of cells was identified.
Pleural invasion is an important prognostic factor that is critical to
identify lung cancer staging
20
The current TNM staging system upgrades
lung cancer to a T2 if visceral pleural invasion is present. MPM imaging
clearly outlinesvisceral pleura (Figure 2(a), inset) due to its rich SHG signal
(color-coded red) originating from collagen I/III and could potentially be
useful to detect visceral pleural invasion.
166 M. Jain
et al.
Studies have reported the amount of collagen in a lung tumor as
a prognostic factor in small, peripheral lung adenocarcinomas
23
SCCs.
ferent patterns of lung carcinoma. Jain et al.
MPM has been used to assess the degree of collagen in dif-
4
categorized adenocarcino-
21,22
and
mas into (1) well-differentiated adenocarcinomas with lepidic-predominant
patterns, (2) moderately differentiated adenocarcinomas with acinarpredominant patterns, and (3) poorly differentiated adenocarcinomas with
solid-predominant patterns. Lepidic-predominant lung tumors exhibited
well-preservedlung architecture with slight alveolar septal thickening from
collagen deposition(Figure 7 (a–c)).In contrast, both acinar (Figure 7(d–f))
and solid-predominant (Figure 7 (g–i)) patterns showed marked increasesin
collagen content, with significantly more collagen in s olid pattern tumors.
The presence of collagen was confirmed using Masson trichrome stain
(Figure 7(c, f, and i). A significant correlation was identified between tumor
differentiation and the amount of tumor-associatedcollagen, with both well
and moderately differentiated tumors exhibiting less fibrosis compared to
poorly differentiated tumors ( P = .009 and 0.03, respectively).
FCM has been shown to identify features of adenocarcinoma (n = 7)
and squamous cell carcinoma (n = 2) in a study using a small sample
size (Figure 8). FCM images matched with the corresponding H&E tissue
sections in this study.
In vivo application of optical imaging techniques in normal human lung and lung cancer
The use of OCT to assess normal and diseased lung tissue in vivo will
have high clinical impact. To date, however, there are few published in vivo
studies. A recent study has shown that combining near infrared-based OCT
with bronchoscopy results in the generation of highly detailed images of
the normal airway wall with histological correlation.
5 patients with biopsy-proven lung cancer underwent bronchoscopy with
in vivo OCT imaging. Airway wall layer (mucosa, submucosa, and total
wall areas) perimeters of 13 airways from 5 patients were evaluated and
calculated by two independent observers. The ex vivo OCT imaging and
histology from the resected lung specimen were compared with the in vivo
imaging. In total, 51 ex vivo OCT images were matched with 39 in vivo
8
Prior to lobectomy,
Lungs 167
(a) (b) (c)
(d) (e) (f)
(h) (i)
(j)
Figure 7. (Continued )
168 M. Jain
et al.
←−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−
Figure 7. (Continued) Comparative low-magnification multiphoton microscopy (MPM) and
hematoxylin-eosin images of adenocarcinoma of lung showing variable amounts of collagen. Colorcombined MPM images (a, d, and g), grayscale MPM images of the second harmonic generation
(collagen) channel alone (b, e, and h), and corresponding histopathologic sections stained with
Masson trichrome stain (c, f, and i). a through c, Adenocarcinoma with lepidic-predominant pattern,
showing well-preserved lung architecture and collagen in thickened septal walls (arrows). d through
f, Images of invasive adenocarcinoma with acinar-predominant pattern, with moderate increase in
collagen (arrows). g through i, Images of invasive carcinoma showing complete destruction of the
normal lung architecture, replaced by sheets of tumor cells (green in MPM; arrowheads) and signifi-
cant amounts of dense collagen (arrows). Collagen is also visible as a normal component of a blood
vessel wall (arrowheads; a through f). j, Histogram showing amount of collagen as the mean [SD]
percentage of the threshold area in well-differentiated adenocarcinoma (w; 39% [1.2%]), moderately
differentiated adenocarcinoma (m; 42% [1.6%]), and poorly differentiated adenocarcinoma (p; 54%
[2.7]) (MPM, original magnifications × 48 [a, b, d, e, g, and h]; Masson trichrome, original magnifi-
cations × 40 [c, f, and i]). Figure reproduced with permission, courtesy of Archives of Pathology and
Laboratory Medicine.
4
(c) (d)
Figure 8. FCM images (c) and corresponding hematoxylin-eosin-stainedtissue sections (d) of a case
of an adenocarcinoma in lung (c and d). Note that the FCM image allows recognition of the tissue
similar to the image of H&E tissue sections (original magnifications × 200 [d]). Figure reproduced
with permission, courtesy of Archives of Pathology and Laboratory Medicine.
5
OCT images and a significant correlation was identified for measurements
involving the airway wall layers ( p < 0.0001) with high inter-observer
reproducibility.
8
Another clinical application of OCT was recently demonstrated using
rapidly generated helical cross-sectional images during transbronchial needle aspiration of lymph nodes for lung cancer staging.
7
Sampling of lymph
nodes intraoperatively is critical for surgical and treatment implications.
Shostak et al.
7
performed ex vivo needle-based OCT sampling from 26
Lungs 169
thoracic lymph nodes with and without known cancer. Based on matching histology, OCT successfully distinguished metastatic carcinoma in 6 of
the 26 lymph nodes and also identified several normal structures including
blood vessels, adjacent airway wall, lymphoid follicles, adipose tissue, and
histiocytes. The study proposed OCT as a useful guide to transbronchial
needle aspiration lymph node sampling as an adjunct diagnostic tool to
endobronchial ultrasound.
Likewise, pCLE miniprobes measuring 0.6 mm (CholangioFlex for
apical and posterior segments of the upper lobes) and 1.4mm (AlveoFlex
for other segments) have been used to evaluate malignant solitary pulmonary nodules (SPNs) in all lobes of the human lung.
9
In this pilot study,
48 patients with malignant SPN were imaged using endobronchial ultrasound coupled with pCLE probes. Normal alveolar network and its cells,
elastin fibers, and blood vessels were readily identified. All the SPNs were
successfully explored with either one of the probes. In 30 pCLE explorations, a specific solid pattern in the SPN correlated with the diagnosis
of lung cancer, mainly pulmonary adenocarcinoma. An overall diagnostic accuracy of 79.2% was found for lung cancer detection using pCLE
miniprobes.
Conclusion
Optical biopsy techniques, such as FFOCT and MPM, facilitate real-time
visualization of tissue at cellular resolution without the need to excise, process, section, or stain tissue. Other optical biopsy techniques have been
used to evaluate human lung pathology in vivo, such as optical coherence tomography, confocal endomicroscopy, and endocytoscopy. Optical
coherence tomography, the most advanced of those technologies, is an
interference-basedoptical imaging technique, similar, in principle, to ultrasound imaging. Current, commercial optical coherence tomography systems have lateral resolutions of 10–15µm, with a depth of imaging of
1 mm or more. Thus, although that technique is good at rapidly generating three-dimensional image volumes that reflect different layers of tissue
components (e.g. cells and connective tissue), the image resolution (similar
to the 34x objective of a histology microscope) is typically not sufficient