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Zhang X, Zeng J, Huang X, Li Z. When chronic obstructive pulmonary disease meets small cell lung cancer: an unusual case report of rapid progression. BMC Geriatr 2023; 23:836. [PMID: 38082430 PMCID: PMC10714477 DOI: 10.1186/s12877-023-04508-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 11/23/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disease and a risk factor for lung cancer. Small cell lung cancer is a neuroendocrine tumor with a high degree of malignancy and an overall five-year survival rate of less than 7%. CASES PRESENTATION Herein, we report the case of an 68-year-old male presented to the respiratory department with cough, sputum, and dyspnea. He was diagnosed as community acquired pneumonia and treated with intravenous anti-infection. Previous pulmonary function was definitively diagnosed as COPD. About 7 months after discharge, the patient returned to the hospital for cough and dyspnea. After diagnosis of the tumor, cisplatin, etoposide and durvalumab were administered. Finally the patient died of respiratory failure approximately 9 months after his diagnosis. CONCLUSIONS For COPD patients with immunocompromised manifestations, it is necessary to be alert to complications and shorten the follow-up interval of chest CT. COPD may accelerate the formation and progression of SCLC.
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Affiliation(s)
- Xu Zhang
- Department of Respiratory and Critical Care Medicine, Guangyuan Central Hospital, 10 Lianhua Road, Lizhou District, Guangyuan City, 628000, Sichuan Province, China
| | - Jia Zeng
- Department of Respiratory and Critical Care Medicine, Guangyuan Central Hospital, 10 Lianhua Road, Lizhou District, Guangyuan City, 628000, Sichuan Province, China
| | - Xiyu Huang
- Sichuan Academy of Medical Sciences, Cardiac Surgery Center, Sichuan Provincial People's Hospital, Chengdu, 610000, China
| | - Zhishu Li
- Department of Respiratory and Critical Care Medicine, Guangyuan Central Hospital, 10 Lianhua Road, Lizhou District, Guangyuan City, 628000, Sichuan Province, China.
- Department of Respiratory and Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, 300000, China.
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Shimoji K, Nakashima T, Masuda T, Namba M, Sakamoto S, Yamaguchi K, Horimasu Y, Mimae T, Miyamoto S, Iwamoto H, Fujitaka K, Hamada H, Okada M, Hattori N. Hypoxia-inducible factor 1α modulates interstitial pneumonia-mediated lung cancer progression. J Transl Med 2023; 21:857. [PMID: 38012636 PMCID: PMC10680219 DOI: 10.1186/s12967-023-04756-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Accepted: 11/24/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND The prognosis of patients with lung cancer accompanied by interstitial pneumonia is poorer than that of patients with lung cancer but without interstitial pneumonia. Moreover, the available therapeutic interventions for lung cancer patients with interstitial pneumonia are limited. Therefore, a new treatment strategy for these patients is required. The aim of the present study was to investigate the pathophysiological relationship between interstitial pneumonia and lung cancer and explore potential therapeutic agents. METHODS A novel hybrid murine model of lung cancer with interstitial pneumonia was established via bleomycin-induced pulmonary fibrosis followed by orthotopic lung cancer cell transplantation into the lungs. Changes in tumor progression, lung fibrosis, RNA expression, cytokine levels, and tumor microenvironment in the lung cancer with interstitial pneumonia model were investigated, and therapeutic agents were examined. Additionally, clinical data and samples from patients with lung cancer accompanied by interstitial pneumonia were analyzed to explore the potential clinical significance of the findings. RESULTS In the lung cancer with interstitial pneumonia model, accelerated tumor growth was observed based on an altered tumor microenvironment. RNA sequencing analysis revealed upregulation of the hypoxia-inducible factor 1 signaling pathway. These findings were consistent with those obtained for human samples. Moreover, we explored whether ascorbic acid could be an alternative treatment for lung cancer with interstitial pneumonia to avoid the disadvantages of hypoxia-inducible factor 1 inhibitors. Ascorbic acid successfully downregulated the hypoxia-inducible factor 1 signaling pathway and inhibited tumor progression and lung fibrosis. CONCLUSIONS The hypoxia-inducible factor 1 pathway is critical in lung cancer with interstitial pneumonia and could be a therapeutic target for mitigating interstitial pneumonia-mediated lung cancer progression.
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Affiliation(s)
- Kiyofumi Shimoji
- Department of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Taku Nakashima
- Department of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
| | - Takeshi Masuda
- Department of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Masashi Namba
- Department of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Shinjiro Sakamoto
- Department of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Kakuhiro Yamaguchi
- Department of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Yasushi Horimasu
- Department of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Takahiro Mimae
- Department of Surgical Oncology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan
| | - Shintaro Miyamoto
- Department of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Hiroshi Iwamoto
- Department of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Kazunori Fujitaka
- Department of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Hironobu Hamada
- Department of Physical Analysis and Therapeutic Sciences, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Morihito Okada
- Department of Surgical Oncology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan
| | - Noboru Hattori
- Department of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
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Park S, Lee SM, Choe J, Choi S, Kim S, Do KH, Seo JB. Sublobar resection in non-small cell lung cancer: patient selection criteria and risk factors for recurrence. Br J Radiol 2023; 96:20230143. [PMID: 37561432 PMCID: PMC10546461 DOI: 10.1259/bjr.20230143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 07/03/2023] [Accepted: 07/11/2023] [Indexed: 08/11/2023] Open
Abstract
OBJECTIVE To validate selection criteria for sublobar resection in patients with lung cancer with respect to recurrence, and to investigate predictors for recurrence in patients for whom the criteria are not suitable. METHODS Patients who underwent sublobar resection for lung cancer between July 2010 and December 2018 were retrospectively included. The criteria for curative sublobar resection were consolidation-to-tumor ratio ≤0.50 and size ≤3.0 cm in tumors with a ground-glass opacity (GGO) component (GGO group), and size of ≤2.0 cm and volume doubling time ≥400 days in solid tumors (solid group). Cox regression was used to identify predictors for time-to-recurrence (TTR) in tumors outside of these criteria (non-curative group). RESULTS Out of 530 patients, 353 were classified into the GGO group and 177 into the solid group. In the GGO group, the 2-year recurrence rates in curative and non-curative groups were 2.1 and 7.7%, respectively (p = 0.054). In the solid group, the 2-year recurrence rates in curative and non-curative groups were 0.0 and 28.6%, respectively (p = 0.03). Predictors of 2-year TTR after non-curative sublobar resection were pathological nodal metastasis (hazard ratio [HR], 6.63; p = 0.02) and lymphovascular invasion (LVI; HR, 3.28; p = 0.03) in the GGO group, and LVI (HR, 4.37; p < 0.001) and fibrosis (HR, 3.18; p = 0.006) in the solid group. CONCLUSION The current patient selection criteria for sublobar resection are satisfactory. LVI was a predictor for recurrence after non-curative resection. ADVANCES IN KNOWLEDGE This result supports selection criteria of patients for sublobar resection. LVI may help predict recurrence after non-curative sublobar resection.
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Affiliation(s)
- Sohee Park
- Department of Radiology, Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Sang Min Lee
- Department of Radiology, Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Jooae Choe
- Department of Radiology, Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Sehoon Choi
- Department of Cardiothoracic Surgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Sehee Kim
- Department of Medical Statistics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Kyung-Hyun Do
- Department of Radiology, Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Joon Beom Seo
- Department of Radiology, Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
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Jiang X, Liu MW, Zhang X, Dong JY, Miao L, Sun ZH, Dong SS, Zhang L, Yang L, Li M. Observational Study of the Natural Growth History of Peripheral Small-Cell Lung Cancer on CT Imaging. Diagnostics (Basel) 2023; 13:2560. [PMID: 37568923 PMCID: PMC10417025 DOI: 10.3390/diagnostics13152560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 07/18/2023] [Accepted: 07/24/2023] [Indexed: 08/13/2023] Open
Abstract
BACKGROUND This study aimed to investigate the natural growth history of peripheral small-cell lung cancer (SCLC) using CT imaging. METHODS A retrospective study was conducted on 27 patients with peripheral SCLC who underwent at least two CT scans. Two methods were used: Method 1 involved direct measurement of nodule dimensions using a calliper, while Method 2 involved tumour lesion segmentation and voxel volume calculation using the "py-radiomics" package in Python. Agreement between the two methods was assessed using the intraclass correlation coefficient (ICC). Volume doubling time (VDT) and growth rate (GR) were used as evaluation indices for SCLC growth, and growth distribution based on GR and volume measurements were depicted. We collected potential factors related to imaging VDT and performed a differential analysis. Patients were classified into slow-growing and fast-growing groups based on a VDT cut-off point of 60 days, and univariate analysis was used to identify factors influencing VDT. RESULTS Median VDT calculated by the two methods were 61 days and 71 days, respectively, with strong agreement. All patients had continuously growing tumours, and none had tumours that decreased in size or remained unchanged. Eight patients showed possible growth patterns, with six possibly exhibiting exponential growth and two possibly showing Gompertzian growth. Tumours deeper in the lung grew faster than those adjacent to the pleura. CONCLUSIONS Peripheral SCLC tumours grow rapidly and continuously without periods of nongrowth or regression. Tumours located deeper in the lung tend to grow faster, but further research is needed to confirm this finding.
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Affiliation(s)
- Xu Jiang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
| | - Meng-Wen Liu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
| | - Xue Zhang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
| | - Ji-Yan Dong
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (J.-Y.D.); (Z.-H.S.)
| | - Lei Miao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
| | - Zi-Han Sun
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (J.-Y.D.); (Z.-H.S.)
| | - Shu-Shan Dong
- Clinical Science, Philips Healthcare, Beijing 100600, China;
| | - Li Zhang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
| | - Lin Yang
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (J.-Y.D.); (Z.-H.S.)
| | - Meng Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
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Accuracy of two deep learning–based reconstruction methods compared with an adaptive statistical iterative reconstruction method for solid and ground-glass nodule volumetry on low-dose and ultra–low-dose chest computed tomography: A phantom study. PLoS One 2022; 17:e0270122. [PMID: 35737734 PMCID: PMC9223620 DOI: 10.1371/journal.pone.0270122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 06/04/2022] [Indexed: 11/19/2022] Open
Abstract
No published studies have evaluated the accuracy of volumetric measurement of solid nodules and ground-glass nodules on low-dose or ultra–low-dose chest computed tomography, reconstructed using deep learning–based algorithms. This is an important issue in lung cancer screening. Our study aimed to investigate the accuracy of semiautomatic volume measurement of solid nodules and ground-glass nodules, using two deep learning–based image reconstruction algorithms (Truefidelity and ClariCT.AI), compared with iterative reconstruction (ASiR-V) in low-dose and ultra–low-dose settings. We performed computed tomography scans of solid nodules and ground-glass nodules of different diameters placed in a phantom at four radiation doses (120 kVp/220 mA, 120 kVp/90 mA, 120 kVp/40 mA, and 80 kVp/40 mA). Each scan was reconstructed using Truefidelity, ClariCT.AI, and ASiR-V. The solid nodule and ground-glass nodule volumes were measured semiautomatically. The gold-standard volumes could be calculated using the diameter since all nodule phantoms are perfectly spherical. Subsequently, absolute percentage measurement errors of the measured volumes were calculated. Image noise was also calculated. Across all nodules at all dose settings, the absolute percentage measurement errors of Truefidelity and ClariCT.AI were less than 11%; they were significantly lower with Truefidelity or ClariCT.AI than with ASiR-V (all P<0.05). The absolute percentage measurement errors for the smallest solid nodule (3 mm) reconstructed by Truefidelity or ClariCT.AI at all dose settings were significantly lower than those of this nodule reconstructed by ASiR-V (all P<0.05). Furthermore, the lowest absolute percentage measurement errors for ground-glass nodules were observed with Truefidelity or ClariCT.AI at all dose settings. The absolute percentage measurement errors for ground-glass nodules reconstructed with Truefidelity at ultra–low-dose settings were significantly lower than those of all sizes of ground-glass nodules reconstructed with ASiR-V (all P<0.05). Image noise was lowest with Truefidelity (all P<0.05). In conclusion, the deep learning–based algorithms were more accurate for volume measurements of both solid nodules and ground-glass nodules than ASiR-V at both low-dose and ultra–low-dose settings.
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Yamamichi T, Nakao M, Omura K, Hashimoto K, Ichinose J, Matsuura Y, Sato Y, Oikado K, Okumura S, Mun M. Relationship between the three-dimensionally measured tumor doubling time of lung cancer and underlying interstitial lung disease: A retrospective case-control study. Cancer Treat Res Commun 2021; 29:100446. [PMID: 34450406 DOI: 10.1016/j.ctarc.2021.100446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 08/09/2021] [Accepted: 08/10/2021] [Indexed: 11/28/2022]
Abstract
OBJECTIVE The coexistence of interstitial lung disease (ILD) is associated with poor prognosis in patients with lung cancer. The tumor doubling time (TDT) of lung cancer reflects cancer aggressiveness and is related to its prognosis. However, the relationship between the TDT of lung cancer and underlying ILD has not been fully evaluated. This study aimed to identify this crucial relationship. MATERIALS AND METHODS Patients with lung cancer who underwent surgery between 2007 and 2020 were reviewed retrospectively. The propensity score matching method was used to balance the characteristics of patients with ILD (n = 100) and those without ILD (n = 100). TDT was calculated based on the difference of three-dimensional volumes defined from the two-time CT scans before surgery. We compared the TDT of lung cancer and other characteristics between the two groups. RESULTS The median TDT of all patients was 149 days. The TDT was significantly shorter in patients with ILD (134 days) than in those without (204 days). The rate of short-term tumor enlargement (TDT < 90 days) was significantly higher in patients with ILD than in those without ILD, and ILD was an independent factor related to short-term tumor enlargement (odds ratio, 2.30; p = 0.015). We focused on 25 patients with usual interstitial pneumonitis (UIP) findings of patients with ILD. However, the presence of the UIP pattern was not related to the TDT among patients with ILD. CONCLUSION ILD was an independent predictor of short-term tumor enlargement in lung cancer patients, regardless of the presence of the UIP pattern.
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Affiliation(s)
- Takashi Yamamichi
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital of Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Masayuki Nakao
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital of Japanese Foundation for Cancer Research, Tokyo, Japan.
| | - Kenshiro Omura
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital of Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Kohei Hashimoto
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital of Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Junji Ichinose
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital of Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Yosuke Matsuura
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital of Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Yoshinao Sato
- Department of Diagnostic Imaging Center, Cancer Institute Hospital of Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Katsunori Oikado
- Department of Diagnostic Imaging Center, Cancer Institute Hospital of Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Sakae Okumura
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital of Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Mingyon Mun
- Department of Thoracic Surgical Oncology, Cancer Institute Hospital of Japanese Foundation for Cancer Research, Tokyo, Japan
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Park S, Lee SM, Do KH, Lee JG, Bae W, Park H, Jung KH, Seo JB. Deep Learning Algorithm for Reducing CT Slice Thickness: Effect on Reproducibility of Radiomic Features in Lung Cancer. Korean J Radiol 2020; 20:1431-1440. [PMID: 31544368 PMCID: PMC6757001 DOI: 10.3348/kjr.2019.0212] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Accepted: 07/12/2019] [Indexed: 01/26/2023] Open
Affiliation(s)
- Sohee Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Sang Min Lee
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
| | - Kyung Hyun Do
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - June Goo Lee
- Department of Convergence Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | | | | | | | - Joon Beom Seo
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
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Park S, Lee SM, Kim S, Lee JG, Choi S, Do KH, Seo JB. Volume Doubling Times of Lung Adenocarcinomas: Correlation with Predominant Histologic Subtypes and Prognosis. Radiology 2020; 295:703-712. [PMID: 32228296 DOI: 10.1148/radiol.2020191835] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Background The volume doubling time (VDT) is a key parameter in the differentiation of aggressive tumors from slow-growing tumors. How different histologic subtypes of primary lung adenocarcinomas vary in their VDT and the prognostic value of this measurement is unknown. Purpose To investigate differences in VDT between the predominant histologic subtypes of primary lung adenocarcinomas and to assess the correlation between VDT and prognosis. Materials and Methods This retrospective study included patients who underwent at least two serial CT examinations before undergoing operation between July 2010 and December 2018. Three-dimensional tumor segmentation was performed on two CT images and VDTs were calculated. VDTs were compared between predominant histologic subtypes and lesion types by using Kruskal-Wallis tests. Disease-free survival (DFS) was obtained in patients undergoing surgical procedures before July 2017. Univariable and multivariable Cox proportional hazards regression analyses were performed to determine predictors of DFS. Results Among 268 patients (mean age, 64 years ± 8 [standard deviation]; 143 men), there were 30 lepidic, 87 acinar, 109 papillary, and 42 solid or micropapillary predominant subtypes. The median VDT was 529 days (interquartile range, 278-872 days) for lung adenocarcinomas. VDTs differed across subtypes (P < .001) and were shortest in solid or micropapillary subtypes (229 days; interquartile range, 77-530 days). Solid lesions (VDT, 248 days) had shorter VDTs than subsolid lesions (part-solid lesions, 665 days; nonsolid lesions, 648 days) (P < .001). In the 148 patients (mean age, 64 years ± 8; 89 men) included in the survival analysis, 35 patients had disease recurrence and 17 patients died. VDT (<400 days) was an independent risk factor for poor DFS (hazard ratio, 2.6; P = .01) and higher TNM stage. Adding VDT to TNM stage improved model performance (C-index, 0.69 for TNM stage vs 0.77 for combined VDT class and TNM stage; P = .002). Conclusion Volume doubling times varied significantly according to the predominant histologic subtypes of lung adenocarcinoma and had additional prognostic value for disease-free survival. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Ko in this issue.
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Affiliation(s)
- Sohee Park
- From the Department of Radiology and Research Institute of Radiology (S.P., S.M.L., K.H.D., J.B.S.); Department of Medical Statistics (S.K.), Department of Convergence Medicine (J.G.L.), and Department of Cardiothoracic Surgery (S.C.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43 Gil, Songpa-gu, Seoul 138-736, Korea
| | - Sang Min Lee
- From the Department of Radiology and Research Institute of Radiology (S.P., S.M.L., K.H.D., J.B.S.); Department of Medical Statistics (S.K.), Department of Convergence Medicine (J.G.L.), and Department of Cardiothoracic Surgery (S.C.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43 Gil, Songpa-gu, Seoul 138-736, Korea
| | - Seonok Kim
- From the Department of Radiology and Research Institute of Radiology (S.P., S.M.L., K.H.D., J.B.S.); Department of Medical Statistics (S.K.), Department of Convergence Medicine (J.G.L.), and Department of Cardiothoracic Surgery (S.C.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43 Gil, Songpa-gu, Seoul 138-736, Korea
| | - June-Goo Lee
- From the Department of Radiology and Research Institute of Radiology (S.P., S.M.L., K.H.D., J.B.S.); Department of Medical Statistics (S.K.), Department of Convergence Medicine (J.G.L.), and Department of Cardiothoracic Surgery (S.C.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43 Gil, Songpa-gu, Seoul 138-736, Korea
| | - Sehoon Choi
- From the Department of Radiology and Research Institute of Radiology (S.P., S.M.L., K.H.D., J.B.S.); Department of Medical Statistics (S.K.), Department of Convergence Medicine (J.G.L.), and Department of Cardiothoracic Surgery (S.C.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43 Gil, Songpa-gu, Seoul 138-736, Korea
| | - Kyung-Hyun Do
- From the Department of Radiology and Research Institute of Radiology (S.P., S.M.L., K.H.D., J.B.S.); Department of Medical Statistics (S.K.), Department of Convergence Medicine (J.G.L.), and Department of Cardiothoracic Surgery (S.C.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43 Gil, Songpa-gu, Seoul 138-736, Korea
| | - Joon Beom Seo
- From the Department of Radiology and Research Institute of Radiology (S.P., S.M.L., K.H.D., J.B.S.); Department of Medical Statistics (S.K.), Department of Convergence Medicine (J.G.L.), and Department of Cardiothoracic Surgery (S.C.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43 Gil, Songpa-gu, Seoul 138-736, Korea
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Effects of sirolimus in lymphangioleiomyomatosis patients on lung cysts and pulmonary function: long-term follow-up observational study. Eur Radiol 2019; 30:735-743. [DOI: 10.1007/s00330-019-06412-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Revised: 07/12/2019] [Accepted: 08/07/2019] [Indexed: 11/26/2022]
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Kim SK, Kim C, Lee KY, Cha J, Lim HJ, Kang EY, Oh YW. Accuracy of Model-Based Iterative Reconstruction for CT Volumetry of Part-Solid Nodules and Solid Nodules in Comparison with Filtered Back Projection and Hybrid Iterative Reconstruction at Various Dose Settings: An Anthropomorphic Chest Phantom Study. Korean J Radiol 2019; 20:1195-1206. [PMID: 31270983 PMCID: PMC6609437 DOI: 10.3348/kjr.2018.0893] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2018] [Accepted: 05/31/2019] [Indexed: 12/30/2022] Open
Abstract
Objective To investigate the accuracy of model-based iterative reconstruction (MIR) for volume measurement of part-solid nodules (PSNs) and solid nodules (SNs) in comparison with filtered back projection (FBP) or hybrid iterative reconstruction (HIR) at various radiation dose settings. Materials and Methods CT scanning was performed for eight different diameters of PSNs and SNs placed in the phantom at five radiation dose levels (120 kVp/100 mAs, 120 kVp/50 mAs, 120 kVp/20 mAs, 120 kVp/10 mAs, and 80 kVp/10 mAs). Each CT scan was reconstructed using FBP, HIR, or MIR with three different image definitions (body routine level 1 [IMR-R1], body soft tissue level 1 [IMR-ST1], and sharp plus level 1 [IMR-SP1]; Philips Healthcare). The SN and PSN volumes including each solid/ground-glass opacity portion were measured semi-automatically, after which absolute percentage measurement errors (APEs) of the measured volumes were calculated. Image noise was calculated to assess the image quality. Results Across all nodules and dose settings, the APEs were significantly lower in MIR than in FBP and HIR (all p < 0.01). The APEs of the smallest inner solid portion of the PSNs (3 mm) and SNs (3 mm) were the lowest when MIR (IMR-R1 and IMR-ST1) was used for reconstruction for all radiation dose settings. (IMR-R1 and IMR-ST1 at 120 kVp/100 mAs, 1.06 ± 1.36 and 8.75 ± 3.96, p < 0.001; at 120 kVp/50 mAs, 1.95 ± 1.56 and 5.61 ± 0.85, p = 0.002; at 120 kVp/20 mAs, 2.88 ± 3.68 and 5.75 ± 1.95, p = 0.001; at 120 kVp/10 mAs, 5.57 ± 6.26 and 6.32 ± 2.91, p = 0.091; at 80 kVp/10 mAs, 5.84 ± 1.96 and 6.90 ± 3.31, p = 0.632). Image noise was significantly lower in MIR than in FBP and HIR for all radiation dose settings (120 kVp/100 mAs, 3.22 ± 0.66; 120 kVp/50 mAs, 4.19 ± 1.37; 120 kVp/20 mAs, 5.49 ± 1.16; 120 kVp/10 mAs, 6.88 ± 1.91; 80 kVp/10 mAs, 12.49 ± 6.14; all p < 0.001). Conclusion MIR was the most accurate algorithm for volume measurements of both PSNs and SNs in comparison with FBP and HIR at low-dose as well as standard-dose settings. Specifically, MIR was effective in the volume measurement of the smallest PSNs and SNs.
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Affiliation(s)
- Seung Kwan Kim
- Department of Radiology, Ansan Hospital, Korea University College of Medicine, Ansan, Korea
| | - Cherry Kim
- Department of Radiology, Ansan Hospital, Korea University College of Medicine, Ansan, Korea
| | - Ki Yeol Lee
- Department of Radiology, Ansan Hospital, Korea University College of Medicine, Ansan, Korea.
| | - Jaehyung Cha
- Medical Science Research Center, Ansan Hospital, Korea University College of Medicine, Ansan, Korea
| | - Hyun Ju Lim
- Department of Radiology, National Cancer Center, Goyang, Korea
| | - Eun Young Kang
- Department of Radiology, Korea University Guro Hospital, College of Medicine Korea University, Seoul, Korea
| | - Yu Whan Oh
- Department of Radiology, Anam Hospital, Korea University College of Medicine, Seoul, Korea
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