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Masayuki Nakao
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MA18 - Advances in Diagnosis of Common Types of NSCLC (ID 145)
- Event: WCLC 2019
- Type: Mini Oral Session
- Track: Pathology
- Presentations: 1
- Now Available
- Moderators:Yuko Minami, Mary Beth Beasley
- Coordinates: 9/10/2019, 11:30 - 13:00, Tokyo (1982)
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MA18.03 - Distinction Between Primary Lung Cancer and Pulmonary Metastasis of Esophageal Cancer Using the Nanostring nCounter System (Now Available) (ID 1228)
11:30 - 13:00 | Author(s): Masayuki Nakao
- Abstract
- Presentation
Background
It is very difficult to distinguish between primary lung squamous cell carcinoma (LSCC) and pulmonary metastasis of esophageal squamous cell carcinoma (ESCC) in patients with past history of ESCC, even by histological examination of the resected specimen. This study aimed to distinguish between LSCC and metastasis of ESCC by multiplex gene expression analysis using the Nanostring nCounter analysis system.
Method
RNA was extracted from the FFPE samples of eight LSCCs, thirteen ESCCs, and nine indeterminate SCCs in the lung of patients with history of ESCC. We selected ten genes which were differently expressed markedly between LSCC and ESCC using the nCounter PanCancer Pathways Panel (XT-CSO-PATH1-12). We performed linear discriminant analysis between the two groups. The derived discriminant function was applied to the nine indeterminate SCCs. The nCounter diagnosis was compared to the preoperative features, pathological findings and postoperative prognosis.
Result
Four of nine pulmonary tumors were diagnosed as LSCC and five were diagnosed as metastasis of ESCC. None of four patients with LSCC died and one developed recurrence, while all of five patients with metastasis of ESCC died and all developed recurrence. The prognosis of the latter was significantly poorer than the former (logrank test, p = 0.02). The preoperative features which indicate metastasis of ESCC (multiple lesions, short disease-free interval and presence of local recurrence) were found only in the metastasis group.
Conclusion
Multiplex gene expression analysis using the nCounter was useful for discrimination between LSCC and pulmonary metastasis of ESCC.
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P1.09 - Pathology (ID 173)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Pathology
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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P1.09-20 - Significance of Maximal Diameter Measurement in Small-Sized Adenocarcinomas (ID 2168)
09:45 - 18:00 | Author(s): Masayuki Nakao
- Abstract
Background
8th edition of the TNM classification for lung cancer has been available since Jan. 2017. The changes are based on a new database of about 90 000 evaluable patients with lung cancer. The proposed changes primarily reflect stratification of patients with lung cancer into prognostically more-precise categories. The revision includes new tumor-size criteria and better-defined classification of additional tumor nodules, subclassifications of lymph node, and systemic metastases. However, invasive size measurement is difficult in some cases, so interobserver variability is inevitable. A maximal size measurement can reduce the interobserver variability to assess the small tumors. To clarify the significance of the maximal diameter measurement, small-sized tumors (10mm or less in maximal diameter) was also subclassified and prognosis after surgery was compared with conventional classification. In addition, we identified the characteristics of small-sized tumor with a worse prognosis.
Method
Pulmonary adenocarcinoma treated surgically at our hospital between Jan. 2006 and Dec. 2011 were recruited. All the cases were evaluated according to the 8th TNM classification. Subsequently, the group with maximal diameter 10mm or less were subcategorized. The Kaplan-Meier method was used to calculate survival. Moreover, clinicopathological characteristics of recurrent cases were also reviewed.
Result
Tumors with 10mm or less maximal diameter comprised 33.6% (94/288) of pTis, pT1mi and pT1a tumors. Average maximal diameter did not differ statistically between pT1mi and pT1a groups (P=0.38). Prolapse-free and disease-specific survivals of the cases with maximal diameter 10mm or less tumors without nodal metastasis were 98.8% and 100%, respectively. Only two cases with maximal diameter 10mm or less tumors recurred (2%, 2/94), both being solid type on CT image and one of the two cases exceptionally showed vascular and pleural invasion as well as nodal metastasis. The maximal diameter of recurrent cases clustered around the value of 10mm.
Conclusion
Only a small fraction of tumors with maximal diameter 10mm or less recurred in our series. Since the recurrent cases clearly showed particular findings including vascular and pleural invasion and a solid image on CT, they can be differentiated from other tumors pathologically or by CT. The maximal diameter measurement is useful in tumors with 10mm diameter or less to estimate the tumor prognosis.
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P1.13 - Staging (ID 181)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Staging
- Presentations: 1
- Now Available
- Moderators:
- Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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P1.13-09 - Utility of Artificial Intelligence in Estimation of the Histologic Type of Lung Cancer (Now Available) (ID 1038)
09:45 - 18:00 | Author(s): Masayuki Nakao
- Abstract
Background
With the development of artificial intelligence (AI), various activities using AI have become able to be performed without specialized knowledge. Computer-aided diagnosis systems using AI have also made great strides in decades. We examined the qualitative diagnostic ability to estimate the histologic type of lung cancer using an image recognition system that can be used online.
Method
We used 316 computed tomography (CT) images of lung cancer with solid component diameter less than 3 cm resected at our hospital. All images were trimmed at the tumor edge to increase the accuracy of machine learning by AI. Prepared images were classified by pathological diagnosis into adenocarcinoma (AD) group and non-adenocarcinoma (non-AD) group. 159 images were assigned to the training set and 157 were assigned to the test set. IBM watson studio; visual recognition app developed for image recognition was used for machine learning and judgment. The established algorithm by the training set was applied to the test set. The histologic type of which possibility calculated by AI was over 0.5 was defined as the AI answer.
Result
There were 93 AD and 66 non-AD in the training set and 92 AD and 65 non-AD in the test set. In the AD group, the median of the solid component diameter was 1.5 cm (0 - 2.9 cm). 21 images were pure ground-glass nodules, 122 images were part-solid ground-glass nodules and 42 images were consisted of solid component. In the non-AD group, the median of the solid component diameter was 2.0 cm (0.5 - 3.0 cm) and all images were consisted of solid component.
Of the 65 non-AD images in the test set, the AI answer was correct in all images (100%). However, of the 92 AD images in the test set, the AI answer was correct only in 49 images (53%). When the 47 AD images with dominant ground-glass opacity were analyzed, the AI answer was correct in 33 images (70%).
Conclusion
Although the CT image recognition using AI could accurately estimate the histologic type of lung cancer in tumors with dominant ground-glass opacity, it was difficult to distinguish solid AD from solid non-AD. The multimodal image analysis including enhanced CT and FDG-PET seems necessary.
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P1.17 - Treatment of Early Stage/Localized Disease (ID 188)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Treatment of Early Stage/Localized Disease
- Presentations: 1
- Now Available
- Moderators:
- Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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P1.17-06 - Long-Term Oncological Outcome After Thoracoscopic Lobectomy for Non-Small Cell Lung Cancer Patients (Now Available) (ID 702)
09:45 - 18:00 | Presenting Author(s): Masayuki Nakao
- Abstract
Background
Thoracoscopic surgery (TS) has been used more commonly as a less invasive procedure for early-stage non-small cell lung cancer (NSCLC) than conventional thoracotomy (TH) in Japan. However, limited evidential data are available to compare the treatment efficacy of TS and TH. The purpose of this study was to retrospectively investigate the difference in the long-term outcome and invasiveness of TS and TH.
Method
Total 1,166 NSCLC patients who underwent surgery between 2005 and 2013 were enrolled. Of these, 844 patients underwent surgery via TH and 322 via TS. We compared several clinicopathological factors and the long-term outcome between the two groups. We performed propensity score matching analysis to minimize differences in the patient background and tumor states. Median follow-up period was 62 months.
Result
The TS group included more women, non-smokers or light smokers, and healthy patients. In the TS group, the disease states were significantly less aggressive. The TS group had a much better 5-year overall survival (OS) rate and cancer specific survival (CSS) rate than the TH group (p <0.0001, p <0.0001). Using propensity score matching, we extracted 190 patients each from the two groups. No statistical differences were present in the OS and CSS rates of the two matched groups (p =0.2223, p=0.0736), indicating the achievement of adequate balance. For a balanced cohort, intraoperative blood loss was significantly less (44 + 40ml vs. 100 + 78ml, p <0.0001), and the duration of postoperative drainage was shorter (2.1 + 1.7 days vs. 3.5 + 2.9 days, p <0.0001 ) in the TS group.
Conclusion
We reported the excellent long-term oncological outcomes in patients with early-stage NSCLC after TS lobectomy. Although this is a single institutional, retrospective study, we successfully avoided selection bias in the patients and showed comparable treatment outcomes with lower invasiveness of TS as compared to that of TH.
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P2.09 - Pathology (ID 174)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Pathology
- Presentations: 1
- Now Available
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.09-10 - INSM1 Is a Good Marker for Diagnosis of Small Cell Lung Carcinoma Even When Neuroendocrine Marker Negative (Now Available) (ID 1104)
10:15 - 18:15 | Author(s): Masayuki Nakao
- Abstract
Background
To diagnose small cell lung carcinoma (SCLC), neuroendocrine (NE) phenotype markers such as chromogranin A, synaptophysin and CD56 are helpful. However, because they are dispensable, SCLCs occur without neuroendocrine phenotypes. Insulinoma-associated protein 1 (INSM1) is a transcription factor for neuroendocrine differentiation and has emerged as a single practical marker for SCLC.
Method
Using the surgical samples of 141 NE tumors (78 SCLCs, 44 large cell neuroendocrine carcinomas (LCNECs), and 19 carcinoids), and 246 non-NE carcinomas, we examined the immunohistochemical expression and prognostic relevance of INSM1 in association with NE phenotype markers in each histologic type. We evaluated its sensitivity and specificity for SCLC diagnosis, as well as its usefulness to diagnose SCLC without NE marker expression and to estimate the prognosis of the subgroups of SCLC stratified by the expression levels of the NE markers. Those of 13 lung cancer cell lines (9 SCLCs and 4 ADCs) were also evaluated.
Result
INSM1 was expressed in SCLCs (92%, 72/78), LCNECs (68%, 30/44), and carcinoids (95%, 18/19). Additionally, among SCLCs with no expression of NE phenotype markers (n=12), 9 (75%) were positive for INSM1. These data suggest the superiority of INSM1 to the phenotype markers. SCLC with low INSM1 expression (n=28) had a significantly better prognosis (P=0.040) than the high-INSM1 group (n=50). Only 7% of adenocarcinomas (9/134) and 4% of squamous cell carcinomas (4/112) were positive for INSM1. In cell lines, most SCLCs were positive for INSM1 (7/9), whereas all ADCs were negative (0/4).
Conclusion
Our study revealed that INSM1 is highly sensitive to detect SCLC, is positive in most phenotype marker-negative SCLCs and can estimate prognosis. INSM1 will be a promising marker for SCLC.
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P2.13 - Staging (ID 315)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Staging
- Presentations: 1
- Now Available
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.13-14 - The Utility of Three-Dimensional CT for Prediction of Tumor Invasiveness in Clinical IA Lung Acenocarcinoma (Now Available) (ID 2478)
10:15 - 18:15 | Author(s): Masayuki Nakao
- Abstract
Background
In the evaluation of clinical T factor, there are some cases that the measurement of the solid component diameter of the tumor is difficult in conventional two-dimensional computed tomography (CT) because of heterogeneity and indistinctness of tumor density. So there is a problem in the preoperative estimation of the tumor invasiveness in these cases. Three-dimensional image analysis software, Synapse Vincent can quantify the volume of solid component of the lung nodule based on the CT value semi-automatically.The purpose of this study was to investigate the relationship between the histological grade of adenocarcinoma and the solid component volume by three-dimensional CT.
Method
We enrolled 195 cases of cIA adenocarcinoma resected at our hospital in 2017. Two observers measured the solid component diameter of the tumors after consultation.
The relationship of solid component diameter (2D), solid component volume (3D) and pathological subtypes (AIS, MIA or invasive cancer) were analyzed.
We additionally performed the same analysis with a focus on 57 cases (29.2%) in which we judged that 2D measurement of the tumor was difficult.
The cut-off value of each item was determined using the ROC curve.
Result
The number of AIS / MIA were 86 and of invasive cancer were 109 cases respectively. The median value of 3D was 442.2 mm3 (0-7044 mm3). About the prediction of invasive cancer by 2D, the sensitivity was 95.4% and the specificity was 64.0%. In the analysis of 3D, the sensitivity was 93.6% and the specificity was 69.6% assuming that the 3D cutoff value was 225 mm3. They were not statistically higher than that of 2D.
In subgroup analysis for 57 cases with difficulty in 2D measurement , when the cutoff value of 3D is 225mm3, the sensitivity is relatively good at 92.9% and the specificity 65.5%, and the accuracy is almost the same as the usual tumors with measurable solid components for invasive cancer prediction. In the analysis of 2D, the sensitivity was good at 92.9%, but the degree of specificity clearly decreased at 44.8%, and the diameter of the solid component tended to be overestimated.
Conclusion
Measurement of the solid component diameter by two-dimensional CT tends to over-estimate shadows that are difficult to measure. Three-dimensional CT, semi-automatic measurement of solid component volume, can be performed easily, and the usefulness of it was suggested, especially in cases with the tumors which are difficult to measure the solid component diameter by two-dimensional CT.
