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Shi L, Sheng M, Wei Z, Liu L, Zhao J. CT-Based Radiomics Predicts the Malignancy of Pulmonary Nodules: A Systematic Review and Meta-Analysis. Acad Radiol 2023; 30:3064-3075. [PMID: 37385850 DOI: 10.1016/j.acra.2023.05.026] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 05/22/2023] [Accepted: 05/24/2023] [Indexed: 07/01/2023]
Abstract
RATIONALE AND OBJECTIVES More pulmonary nodules (PNs) have been detected with the wide application of computed tomography (CT) in lung cancer screening. Radiomics is a noninvasive approach to predict the malignancy of PNs. We aimed to systematically evaluate the methodological quality of the eligible studies regarding CT-based radiomics models in predicting the malignancy of PNs and evaluate the model performance of the available studies. MATERIALS AND METHODS PubMed, Embase, and Web of Science were searched to retrieve relevant studies. The methodological quality of the included studies was assessed using the Radiomics Quality Score (RQS) and Prediction model Risk of Bias Assessment Tool. A meta-analysis was conducted to evaluate the performance of CT-based radiomics model. Meta-regression and subgroup analyses were employed to investigate the source of heterogeneity. RESULTS In total, 49 studies were eligible for qualitative analysis and 27 studies were included in quantitative synthesis. The median RQS of 49 studies was 13 (range -2 to 20). The overall risk of bias was found to be high, and the overall applicability was of low concern in all included studies. The pooled sensitivity, specificity, and diagnostic odds ratio were 0.86 95% confidence interval (CI): 0.79-0.91, 0.84 95% CI: 0.78-0.88, and 31.55 95% CI: 21.31-46.70, respectively. The overall area under the curve was 0.91 95% CI: 0.89-0.94. Meta-regression showed the type of PNs on heterogeneity. CT-based radiomics models performed better in studies including only solid PNs. CONCLUSION CT-based radiomics models exhibited excellent diagnostic performance in predicting the malignancy of PNs. Prospective, large sample size, and well-devised studies are desired to verify the prediction capabilities of CT-based radiomics model.
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Affiliation(s)
- Lili Shi
- Medical School, Nantong University, Nantong, China (L.S., Z.W.)
| | - Meihong Sheng
- Department of Radiology, The Second Affiliated Hospital of Nantong University and Nantong First People's Hospital, Nantong, China (M.S.)
| | - Zhichao Wei
- Medical School, Nantong University, Nantong, China (L.S., Z.W.)
| | - Lei Liu
- Institutes of Intelligence Medicine, Fudan University, Shanghai, China (L.L.)
| | - Jinli Zhao
- Department of Radiology, Affiliated Hospital of Nantong University, Nantong, China (J.Z.).
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Lin RY, Zheng YN, Lv FJ, Fu BJ, Li WJ, Liang ZR, Chu ZG. A combined non-enhanced CT radiomics and clinical variable machine learning model for differentiating benign and malignant sub-centimeter pulmonary solid nodules. Med Phys 2023; 50:2835-2843. [PMID: 36810703 DOI: 10.1002/mp.16316] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 02/08/2023] [Accepted: 02/08/2023] [Indexed: 02/24/2023] Open
Abstract
BACKGROUND Radiomics has been used to predict pulmonary nodule (PN) malignancy. However, most of the studies focused on pulmonary ground-glass nodules. The use of computed tomography (CT) radiomics in pulmonary solid nodules, particularly sub-centimeter solid nodules, is rare. PURPOSE This study aims to develop a radiomics model based on non-enhanced CT images that can distinguish between benign and malignant sub-centimeter pulmonary solid nodules (SPSNs, <1 cm). METHODS The clinical and CT data of 180 SPSNs confirmed by pathology were analyzed retrospectively. All SPSNs were divided into two groups: training set (n = 144) and testing set (n = 36). From non-enhanced chest CT images, over 1000 radiomics features were extracted. Radiomics feature selection was performed using the analysis of variance and principal component analysis. The selected radiomics features were fed into a support vector machine (SVM) to develop a radiomics model. The clinical and CT characteristics were used to develop a clinical model. Associating non-enhanced CT radiomics features with clinical factors were used to develop a combined model using SVM. The performance was evaluated using the area under the receiver-operating characteristic curve (AUC). RESULTS The radiomics model performed well in distinguishing between benign and malignant SPSNs, with an AUC of 0.913 (95% confidence interval [CI], 0.862-0.954) in the training set and an AUC of 0.877 (95% CI, 0.817-0.924) in the testing set. The combined model outperformed the clinical and radiomics models with an AUC of 0.940 (95% CI, 0.906-0.969) in the training set and an AUC of 0.903 (95% CI, 0.857-0.944) in the testing set. CONCLUSIONS Radiomics features based on non-enhanced CT images can be used to differentiate SPSNs. The combined model, which included radiomics and clinical factors, had the best discrimination power between benign and malignant SPSNs.
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Affiliation(s)
- Rui-Yu Lin
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yi-Neng Zheng
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Fa-Jin Lv
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Bin-Jie Fu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Wang-Jia Li
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Zhang-Rui Liang
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Zhi-Gang Chu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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Erdogdu E, Ozkan B, Duman S, Agkoc M, Erturk SM, Kara M, Toker A. Predictors of malignancy in patients with solitary pulmonary nodules undergoing pulmonary resection. THE CLINICAL RESPIRATORY JOURNAL 2022; 16:361-368. [PMID: 35474637 PMCID: PMC9366584 DOI: 10.1111/crj.13489] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 09/24/2021] [Accepted: 03/21/2022] [Indexed: 11/28/2022]
Abstract
Background The management of a solitary pulmonary nodule is a challenging issue in pulmonary disease. Although many factors have been defined as predictors for malignancy in solitary pulmonary nodules, the accurate diagnosis can only be established with the permanent histological diagnosis. Objective We tried to clarify the possible predictors of malignancy in solitary pulmonary nodules in patients who had definitive histological diagnosis. Methods We made a retrospective study to collect the data of patients with solitary pulmonary nodules who had histological diagnosis either before or after surgery. We made a statistical analysis of both the clinic and radiological features of these nodules with respect to malignancy both in contingency tables and with logistic regression analysis. Results We had a total of 223 patients with a radiological diagnosis of solitary pulmonary nodule. Age, smoking status and pack years of smoking, maximum standardized uptake value (SUVmax), and radiological features such as solid component, spiculation, pleural tag, lobulation, calcification, and higher density were significant predictors of malignancy in contingency tables. Age, smoking status and smoking (pack/year), SUVmax, and radiological features including spiculation, pleural tag, lobulation, calcification, and higher density were the significant predictors in univariate analysis. However, multivariate analysis revealed only SUVmax greater than 2.5 (p < 0.0001), spiculation (p = 0.009), and age older than 61 years (p = 0.015) as the significant predictors for malignancy. Conclusion Age, SUVmax, and spiculation are the independent predictors of malignancy in patients with solitary pulmonary nodules.
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Affiliation(s)
- Eren Erdogdu
- Department of Thoracic Surgery, Istanbul University Faculty of Medicine, Istanbul, Turkey
| | - Berker Ozkan
- Department of Thoracic Surgery, Istanbul University Faculty of Medicine, Istanbul, Turkey
| | - Salih Duman
- Department of Thoracic Surgery, Istanbul University Faculty of Medicine, Istanbul, Turkey
| | - Melek Agkoc
- Department of Thoracic Surgery, Istanbul University Faculty of Medicine, Istanbul, Turkey
| | - Sukru Mehmet Erturk
- Department of Radiology, Istanbul University Faculty of Medicine, Istanbul, Turkey
| | - Murat Kara
- Department of Thoracic Surgery, Istanbul University Faculty of Medicine, Istanbul, Turkey
| | - Alper Toker
- Department of Cardiovascular and Thoracic Surgery, West Virginia University Heart and Vascular Institute, Morgantown, West Virginia, USA
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Wu S, Zhang N, Wu Z, Ren J, E L. Can Peritumoral Radiomics Improve the Prediction of Malignancy of Solid Pulmonary Nodule Smaller Than 2 cm? Acad Radiol 2022; 29 Suppl 2:S47-S52. [PMID: 33189549 DOI: 10.1016/j.acra.2020.10.029] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 10/21/2020] [Accepted: 10/31/2020] [Indexed: 12/12/2022]
Abstract
RATIONALE AND OBJECTIVES To compare the ability of radiomics models including the perinodular parenchyma and standard nodular radiomics model in lung cancer diagnosis of solid pulmonary nodules smaller than 2 cm. MATERIALS AND METHODS In this retrospective study, the computed tomography (CT) scans of 206 patients with a lung nodule from a single institution in 2012-2019 were collected. For each nodule, four volumes of interest were defined using the gross tumor volume (GTV) and peritumoral volumes (PTVs) of 5, 10, and 15 mm around the tumor. RESULTS Radiomics models created from GTV, GTV plus 5 mm of PTV, GTV plus 10 mm of PTV, and GTV plus 15 mm of PTV achieved AUCs of 0.89, 0.81, 0.81, and 0.73, respectively, in the validation cohort for the diagnostic classification of benign and malignant pulmonary nodules. The performance of the models gradually decreased as the PTV increased. Wavelet features were the primary features identified in optimal radiomics signatures (2/3 in R, 4/5 in GTV plus 5 mm PTV, 3/4 in GTV plus 10 mm PTV, 2/3 in GTV plus 15 mm PTV). CONCLUSION Our study indicated that the radiomics signatures of GTV had a good prediction ability in distinguishing benign and malignant solid pulmonary nodules smaller than 2 cm on CT. However, the radiomics feature of the surrounding parenchyma of the nodule did not enhance the effectiveness of the diagnostic model.
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Affiliation(s)
- Shan Wu
- Department of Radiology, Shanxi Bethune Hospital, 99 Longcheng Street, Taiyuan, Shanxi 030032, China
| | - Na Zhang
- Department of Radiology, Shanxi Bethune Hospital, 99 Longcheng Street, Taiyuan, Shanxi 030032, China
| | - Zhifeng Wu
- Department of Radiology, Shanxi Bethune Hospital, 99 Longcheng Street, Taiyuan, Shanxi 030032, China
| | | | - Linning E
- Department of Radiology, Shanxi Bethune Hospital, 99 Longcheng Street, Taiyuan, Shanxi 030032, China.
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Borghesi A, Michelini S, Scrimieri A, Golemi S, Maroldi R. Solid Indeterminate Pulmonary Nodules of Less Than 300 mm 3: Application of Different Volume Doubling Time Cut-offs in Clinical Practice. Diagnostics (Basel) 2019; 9:diagnostics9020062. [PMID: 31226780 PMCID: PMC6627535 DOI: 10.3390/diagnostics9020062] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2019] [Revised: 06/01/2019] [Accepted: 06/19/2019] [Indexed: 12/26/2022] Open
Abstract
In the British Thoracic Society guidelines for incidental pulmonary nodules, volumetric analysis has become the recommended method for growth assessment in solid indeterminate pulmonary nodules (SIPNs) <300 mm3. In these guidelines, two different volume doubling time (VDT) cut-offs, 400 and 600 days, were proposed to differentiate benign from malignant nodules. The present study aims to evaluate the performance of these VDT cut-offs in a group of SIPNs <300 mm3 which were incidentally detected in a routine clinical setting. During a 7-year period, we retrospectively selected 60 patients with a single SIPN <300 mm3. For each SIPN, the volume and VDT were calculated using semiautomatic software throughout the follow-up period, and the performance of the 400- and 600-day VDT cut-offs was compared. In the selected sample, there were 38 benign and 22 malignant nodules. In this group of nodules, the sensitivity, negative predictive value and accuracy of the 600-day VDT cut-off were higher than those of the 400-day VDT cut-off. Therefore, in the management of SIPNs <300 mm3 which were incidentally detected in a clinical setting, the 600-day VDT cut-off was better at differentiating benign from malignant nodules than the 400-day VDT cut-off, by reducing the number of false negatives.
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Affiliation(s)
- Andrea Borghesi
- Department of Radiology, University and ASST Spedali Civili of Brescia, Piazzale Spedali Civili 1, 25123 Brescia, Italy.
| | - Silvia Michelini
- Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Via Leonida Bissolati, 57, 25124 Brescia, Italy.
| | - Alessandra Scrimieri
- Department of Radiology, University and ASST Spedali Civili of Brescia, Piazzale Spedali Civili 1, 25123 Brescia, Italy.
| | - Salvatore Golemi
- Department of Radiology, University and ASST Spedali Civili of Brescia, Piazzale Spedali Civili 1, 25123 Brescia, Italy.
| | - Roberto Maroldi
- Department of Radiology, University and ASST Spedali Civili of Brescia, Piazzale Spedali Civili 1, 25123 Brescia, Italy.
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Mao L, Chen H, Liang M, Li K, Gao J, Qin P, Ding X, Li X, Liu X. Quantitative radiomic model for predicting malignancy of small solid pulmonary nodules detected by low-dose CT screening. Quant Imaging Med Surg 2019; 9:263-272. [PMID: 30976550 DOI: 10.21037/qims.2019.02.02] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Background It is a permanent challenge to differentiate small solid lung nodules. Massive data, extracted from medical image through radiomics analysis, may help early diagnosis of lung cancer. The aim of this study was to assess the usefulness of a quantitative radiomic model developed from baseline low-dose computed tomography (LDCT) screening for the purpose of predicting malignancy in small solid pulmonary nodules (SSPNs). Methods This retrospective study included malignant and benign SSPNs (6 to 15 mm) detected in baseline low-dose CT screening. The malignancy was confirmed pathologically, and benignity was confirmed by long term follow-up or pathological diagnosis. The non-contrast CT images were reconstructed with a lung kernel of a slice thickness of 1 mm and were processed to extract 385 quantitative radiomic features using Analysis-Kinetic software. A predictive model was established with the training set of 156 benign and 40 malignant nodules, and was tested with the validation set of 77 benign and 21 malignant nodules through the analysis of R square. The performance of the radiomic model in predicting malignancy was compared with that of the ACR Lung Imaging Reporting and Data System (ACR lung-RADS). Results In 294 cases of SSPNs, 61 lung cancers and 24 benign nodules were confirmed pathologically and the remaining 209 nodules were stable with long-term follow-up (4.1±0.9 years). Eleven non-redundant features, including 8 high-order texture features, were extracted from the training data set. The sensitivity and specificity of the prediction model in malignancy differentiation were 81.0% and 92.2% respectively. The accuracy was superior to ACR-lung RADS (89.8% vs. 76.5%). Conclusions A radiomic model based on baseline low-dose CT screening for lung cancer can improve the accuracy in predicting malignancy of SSPNs.
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Affiliation(s)
- Liting Mao
- Department of Radiology, The 5 Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, China.,Department of Radiology, The Second Affiliated Hosptial of Guangzhou University of Traditional Chinese Medicine, Guangzhou 510120, China
| | - Huan Chen
- Department of Radiology, The 5 Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, China
| | - Mingzhu Liang
- Department of Radiology, The 5 Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, China
| | - Kunwei Li
- Department of Radiology, The 5 Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, China
| | - Jiebing Gao
- Department of Radiology, The 5 Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, China
| | - Peixin Qin
- Department of Radiology, The 5 Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, China
| | - Xianglian Ding
- Department of Radiology, The 5 Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, China
| | - Xin Li
- GE Healthcare, Guangzhou 510000, China
| | - Xueguo Liu
- Department of Radiology, The 5 Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, China
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An Update on the European Lung Cancer Screening Trials and Comparison of Lung Cancer Screening Recommendations in Europe. J Thorac Imaging 2019; 34:65-71. [DOI: 10.1097/rti.0000000000000367] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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Devaraj A, van Ginneken B, Nair A, Baldwin D. Use of Volumetry for Lung Nodule Management: Theory and Practice. Radiology 2017; 284:630-644. [DOI: 10.1148/radiol.2017151022] [Citation(s) in RCA: 73] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
- Anand Devaraj
- From the Department of Radiology, Royal Brompton Hospital, Sydney St, London SW3 6NP, England (A.D.); Department of of Radiology and Nuclear Medicine, Radboud UMC, Nijmegen, the Netherlands (B.v.G.); Department of Radiology, Guy’s & St Thomas’ NHS Foundation Trust, London, England (A.N.); and Department of Respiratory Medicine, Nottingham University Hospitals and University of Nottingham, Nottingham, England
| | - Bram van Ginneken
- From the Department of Radiology, Royal Brompton Hospital, Sydney St, London SW3 6NP, England (A.D.); Department of of Radiology and Nuclear Medicine, Radboud UMC, Nijmegen, the Netherlands (B.v.G.); Department of Radiology, Guy’s & St Thomas’ NHS Foundation Trust, London, England (A.N.); and Department of Respiratory Medicine, Nottingham University Hospitals and University of Nottingham, Nottingham, England
| | - Arjun Nair
- From the Department of Radiology, Royal Brompton Hospital, Sydney St, London SW3 6NP, England (A.D.); Department of of Radiology and Nuclear Medicine, Radboud UMC, Nijmegen, the Netherlands (B.v.G.); Department of Radiology, Guy’s & St Thomas’ NHS Foundation Trust, London, England (A.N.); and Department of Respiratory Medicine, Nottingham University Hospitals and University of Nottingham, Nottingham, England
| | - David Baldwin
- From the Department of Radiology, Royal Brompton Hospital, Sydney St, London SW3 6NP, England (A.D.); Department of of Radiology and Nuclear Medicine, Radboud UMC, Nijmegen, the Netherlands (B.v.G.); Department of Radiology, Guy’s & St Thomas’ NHS Foundation Trust, London, England (A.N.); and Department of Respiratory Medicine, Nottingham University Hospitals and University of Nottingham, Nottingham, England
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Bae K, Jeon KN, Lee SJ, Kim HC, Ha JY, Park SE, Baek HJ, Choi BH, Cho SB, Moon JI. Severity of pulmonary emphysema and lung cancer: analysis using quantitative lobar emphysema scoring. Medicine (Baltimore) 2016; 95:e5494. [PMID: 27902611 PMCID: PMC5134818 DOI: 10.1097/md.0000000000005494] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
The aim of this study was to determine the relationship between lobar severity of emphysema and lung cancer using automated lobe segmentation and emphysema quantification methods.This study included 78 patients (74 males and 4 females; mean age of 72 years) with the following conditions: pathologically proven lung cancer, available chest computed tomographic (CT) scans for lobe segmentation, and quantitative scoring of emphysema. The relationship between emphysema and lung cancer was analyzed using quantitative emphysema scoring of each pulmonary lobe.The most common location of cancer was the left upper lobe (LUL) (n = 28), followed by the right upper lobe (RUL) (n = 27), left lower lobe (LLL) (n = 13), right lower lobe (RLL) (n = 9), and right middle lobe (RML) (n = 1). Emphysema ratio was the highest in LUL, followed by that in RUL, LLL, RML, and RLL. Multivariate logistic regression analysis revealed that upper lobes (odds ratio: 1.77; 95% confidence interval: 1.01-3.11, P = 0.048) and lobes with emphysema ratio ranked the 1st or the 2nd (odds ratio: 2.48; 95% confidence interval: 1.48-4.15, P < 0.001) were significantly and independently associated with lung cancer development.In emphysema patients, lung cancer has a tendency to develop in lobes with more severe emphysema.
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Affiliation(s)
- Kyungsoo Bae
- Department of Internal Medicine, Gyeongsang National University Changwon Hospital, Changwon, Korea
- Department of Radiology, Gyeongsang National University Changwon Hospital, Changwon
| | - Kyung Nyeo Jeon
- Department of Internal Medicine, Gyeongsang National University Changwon Hospital, Changwon, Korea
- Department of Radiology, Gyeongsang National University Changwon Hospital, Changwon
| | - Seung Jun Lee
- Department of Internal Medicine, Gyeongsang National University Changwon Hospital, Changwon, Korea
- Department of Internal Medicine, Gyeongsang National University Hospital, Jinju
| | - Ho Cheol Kim
- Department of Internal Medicine, Gyeongsang National University Changwon Hospital, Changwon, Korea
- Department of Internal Medicine, Gyeongsang National University Changwon Hospital, Changwon, Korea
| | - Ji Young Ha
- Department of Internal Medicine, Gyeongsang National University Changwon Hospital, Changwon, Korea
| | - Sung Eun Park
- Department of Internal Medicine, Gyeongsang National University Changwon Hospital, Changwon, Korea
| | - Hye Jin Baek
- Department of Internal Medicine, Gyeongsang National University Changwon Hospital, Changwon, Korea
- Department of Radiology, Gyeongsang National University Changwon Hospital, Changwon
| | - Bo Hwa Choi
- Department of Internal Medicine, Gyeongsang National University Changwon Hospital, Changwon, Korea
- Department of Radiology, Gyeongsang National University Changwon Hospital, Changwon
| | - Soo Buem Cho
- Department of Internal Medicine, Gyeongsang National University Changwon Hospital, Changwon, Korea
- Department of Radiology, Gyeongsang National University Changwon Hospital, Changwon
| | - Jin Il Moon
- Department of Internal Medicine, Gyeongsang National University Changwon Hospital, Changwon, Korea
- Department of Radiology, Gyeongsang National University Changwon Hospital, Changwon
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Abu Saleh WK, Jabbari OA, Lumsden A, Ramchandani MK. Case Report: Simultaneous Localization and Removal of Lung Nodules Through Extended Use of the Hybrid Suite. Methodist Debakey Cardiovasc J 2016; 11:245-6. [PMID: 27057295 DOI: 10.14797/mdcj-11-4-245] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
The ability to attain high-definition imaging for preoperative planning, intraoperative execution, and postoperative evaluation is instrumental in surgical practice. Hybrid room computed tomography (CT) allows for faster, less invasive diagnostic and therapeutic options for patients. We present our diagnostic workup and therapeutic intervention with hybrid CT imaging in a 71-year-old female with a growing lung nodule after previous lobectomy for lung cancer.
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Affiliation(s)
- Walid K Abu Saleh
- Houston Methodist DeBakey Heart & Vascular Center, Houston Methodist Hospital, Houston, Texas
| | - Odeaa Al Jabbari
- Houston Methodist DeBakey Heart & Vascular Center, Houston Methodist Hospital, Houston, Texas
| | - Alan Lumsden
- Houston Methodist DeBakey Heart & Vascular Center, Houston Methodist Hospital, Houston, Texas
| | - Mahesh K Ramchandani
- Houston Methodist DeBakey Heart & Vascular Center, Houston Methodist Hospital, Houston, Texas
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Rouzé S, de Latour B, Flécher E, Guihaire J, Castro M, Corre R, Haigron P, Verhoye JP. Small pulmonary nodule localization with cone beam computed tomography during video-assisted thoracic surgery: a feasibility study. Interact Cardiovasc Thorac Surg 2016; 22:705-11. [DOI: 10.1093/icvts/ivw029] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2015] [Accepted: 01/08/2016] [Indexed: 11/13/2022] Open
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Nakajima T, Cypel M, de Perrot M, Pierre A, Waddell T, Singer L, Roberts H, Keshavjee S, Yasufuku K. Retrospective Analysis of Lung Transplant Recipients Found to Have Unexpected Lung Cancer in Explanted Lungs. Semin Thorac Cardiovasc Surg 2015; 27:9-14. [DOI: 10.1053/j.semtcvs.2015.02.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/23/2015] [Indexed: 12/26/2022]
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13
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Novel and convenient method to evaluate the character of solitary pulmonary nodule-comparison of three mathematical prediction models and further stratification of risk factors. PLoS One 2013; 8:e78271. [PMID: 24205175 PMCID: PMC3812137 DOI: 10.1371/journal.pone.0078271] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2013] [Accepted: 09/10/2013] [Indexed: 01/08/2023] Open
Abstract
Objective To study risk factors that affect the evaluation of malignancy in patients with solitary pulmonary nodules (SPN) and verify different predictive models for malignant probability of SPN. Methods Retrospectively analyzed 107 cases of SPN with definite post-operative histological diagnosis whom underwent surgical procedures in China-Japan Friendship Hospital from November of 2010 to February of 2013. Age, gender, smoking history, malignancy history of patients, imaging features of the nodule including maximum diameter, position, spiculation, lobulation, calcification and serum level of CEA and Cyfra21-1 were assessed as potential risk factors. Univariate analysis model was used to establish statistical correlation between risk factors and post-operative histological diagnosis. Receiver operating characteristic (ROC) curves were drawn using different predictive models for malignant probability of SPN to get areas under the curves (AUC values), sensitivity, specificity, positive predictive values, negative predictive values for each model, respectively. The predictive effectiveness of each model was statistically assessed subsequently. Results In 107 patients, 78 cases were malignant (72.9%), 29 cases were benign (27.1%). Statistical significant difference was found between benign and malignant group in age, maximum diameter, serum level of Cyfra21-1, spiculation, lobulation and calcification of the nodules. The AUC values were 0.786±0.053 (Mayo model), 0.682±0.060 (VA model) and 0.810±0.051 (Peking University People’s Hospital model), respectively. Conclusions Serum level of Cyfra21-1, patient’s age, maximum diameter of the nodule, spiculation, lobulation and calcification of the nodule are independent risk factors associated with the malignant probability of SPN. Peking University People’s Hospital model is of high accuracy and clinical value for patients with SPN. Adding serum index (e.g. Cyfra21-1) into the prediction models as a new risk factor and adjusting the weight of age in the models might improve the accuracy of prediction for SPN.
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Linning E, Wu S, Wang K, Meng H, Sun D, Wu Z. Computed tomography quantitative analysis of components: a new method monitoring the growth of pulmonary nodule. Acta Radiol 2013; 54:904-8. [PMID: 23761548 DOI: 10.1177/0284185113485572] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The estimation of the growth of solitary pulmonary nodules by using non-invasive methods is increasingly gaining clinical importance for performing the timely adequate treatment of these nodules. PURPOSE To evaluate the application value of computed tomography (CT) quantitative analysis of components for dynamic assessment of the growth of solitary pulmonary nodules, and compare this approach with three-dimensional (3D) volumetric measurement of pulmonary nodules. MATERIAL AND METHODS The imaging data of 21 patients who had undergone multiple follow-up CT scans for solitary pulmonary nodules were retrospectively analyzed, and the total volume of pulmonary nodules and the percentage change in the total volume of pulmonary nodules after multiple follow-up CT scans were measured using 3D volume measurement software. The volume of solid components in pulmonary nodules was measured using CT quantitative analysis; the percentage change in the volume of solid components across examinations was calculated; and the percentage change in the total volume of pulmonary nodules was compared and contrasted with the percentage change in the volume of solid components in the pulmonary nodules. RESULTS All 21 cases were malignant adenocarcinomas. In the 21 cases of malignant nodules, the 3D volumes of the nodules and solid components were both increased, with the percentage change in the volume of the solid components (115.78-418.91%, 130.45 ± 119.48) significantly different from the percentage change in the total volume of the nodules (78.56-105.73% , 42.34 ± 32.17) (P = 0.02). CONCLUSION By measuring volume changes in solid components in the nodules, CT quantitative analysis offers more sensitive and earlier evaluation of the dynamic growth of the nodules than measurement of volume changes in the nodules alone.
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Affiliation(s)
- E Linning
- Shanxi Medical University, Shanxi
- Department of Radiology, Shanxi DAYI Hospital, Shanxi, China
| | - Shan Wu
- Shanxi Medical University, Shanxi
- Department of Radiology, Shanxi DAYI Hospital, Shanxi, China
| | - Kai Wang
- Department of Radiology, Shanxi DAYI Hospital, Shanxi, China
| | - Huiqiang Meng
- Department of Radiology, Shanxi DAYI Hospital, Shanxi, China
| | - Dong Sun
- Department of Radiology, Shanxi DAYI Hospital, Shanxi, China
| | - Zhifeng Wu
- Shanxi Medical University, Shanxi
- Department of Radiology, Shanxi DAYI Hospital, Shanxi, China
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15
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Uneri A, Nithiananthan S, Schafer S, Otake Y, Stayman JW, Kleinszig G, Sussman MS, Prince JL, Siewerdsen JH. Deformable registration of the inflated and deflated lung in cone-beam CT-guided thoracic surgery: initial investigation of a combined model- and image-driven approach. Med Phys 2013; 40:017501. [PMID: 23298134 DOI: 10.1118/1.4767757] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Surgical resection is the preferred modality for curative treatment of early stage lung cancer, but localization of small tumors (<10 mm diameter) during surgery presents a major challenge that is likely to increase as more early-stage disease is detected incidentally and in low-dose CT screening. To overcome the difficulty of manual localization (fingers inserted through intercostal ports) and the cost, logistics, and morbidity of preoperative tagging (coil or dye placement under CT-fluoroscopy), the authors propose the use of intraoperative cone-beam CT (CBCT) and deformable image registration to guide targeting of small tumors in video-assisted thoracic surgery (VATS). A novel algorithm is reported for registration of the lung from its inflated state (prior to pleural breach) to the deflated state (during resection) to localize surgical targets and adjacent critical anatomy. METHODS The registration approach geometrically resolves images of the inflated and deflated lung using a coarse model-driven stage followed by a finer image-driven stage. The model-driven stage uses image features derived from the lung surfaces and airways: triangular surface meshes are morphed to capture bulk motion; concurrently, the airways generate graph structures from which corresponding nodes are identified. Interpolation of the sparse motion fields computed from the bounding surface and interior airways provides a 3D motion field that coarsely registers the lung and initializes the subsequent image-driven stage. The image-driven stage employs an intensity-corrected, symmetric form of the Demons method. The algorithm was validated over 12 datasets, obtained from porcine specimen experiments emulating CBCT-guided VATS. Geometric accuracy was quantified in terms of target registration error (TRE) in anatomical targets throughout the lung, and normalized cross-correlation. Variations of the algorithm were investigated to study the behavior of the model- and image-driven stages by modifying individual algorithmic steps and examining the effect in comparison to the nominal process. RESULTS The combined model- and image-driven registration process demonstrated accuracy consistent with the requirements of minimally invasive VATS in both target localization (∼3-5 mm within the target wedge) and critical structure avoidance (∼1-2 mm). The model-driven stage initialized the registration to within a median TRE of 1.9 mm (95% confidence interval (CI) maximum = 5.0 mm), while the subsequent image-driven stage yielded higher accuracy localization with 0.6 mm median TRE (95% CI maximum = 4.1 mm). The variations assessing the individual algorithmic steps elucidated the role of each step and in some cases identified opportunities for further simplification and improvement in computational speed. CONCLUSIONS The initial studies show the proposed registration method to successfully register CBCT images of the inflated and deflated lung. Accuracy appears sufficient to localize the target and adjacent critical anatomy within ∼1-2 mm and guide localization under conditions in which the target cannot be discerned directly in CBCT (e.g., subtle, nonsolid tumors). The ability to directly localize tumors in the operating room could provide a valuable addition to the VATS arsenal, obviate the cost, logistics, and morbidity of preoperative tagging, and improve patient safety. Future work includes in vivo testing, optimization of workflow, and integration with a CBCT image guidance system.
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Affiliation(s)
- Ali Uneri
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
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16
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Grannis FW. Minimizing over-diagnosis in lung cancer screening. J Surg Oncol 2013; 108:289-93. [DOI: 10.1002/jso.23400] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2013] [Accepted: 07/16/2013] [Indexed: 11/06/2022]
Affiliation(s)
- Frederic W. Grannis
- Thoracic Surgery Section; City of Hope National Medical Center; Duarte California
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17
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Heuvelmans MA, Oudkerk M, de Bock GH, de Koning HJ, Xie X, van Ooijen PMA, Greuter MJW, de Jong PA, Groen HJM, Vliegenthart R. Optimisation of volume-doubling time cutoff for fast-growing lung nodules in CT lung cancer screening reduces false-positive referrals. Eur Radiol 2013; 23:1836-45. [PMID: 23508275 DOI: 10.1007/s00330-013-2799-9] [Citation(s) in RCA: 64] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2012] [Revised: 12/31/2012] [Accepted: 01/14/2013] [Indexed: 12/21/2022]
Abstract
OBJECTIVE To retrospectively investigate whether optimisation of volume-doubling time (VDT) cutoff for fast-growing nodules in lung cancer screening can reduce false-positive referrals. METHODS Screening participants of the NELSON study underwent low-dose CT. For indeterminate nodules (volume 50-500 mm(3)), follow-up CT was performed 3 months after baseline. A negative baseline screen resulted in a regular second-round examination 1 year later. Subjects referred to a pulmonologist because of a fast-growing (VDT <400 days) solid nodule in the baseline or regular second round were included in this study. Histology was the reference for diagnosis, or stability on subsequent CTs, confirming benignity. Mean follow-up of non-resected nodules was 4.4 years. Optimisation of the false-positive rate was evaluated at maintained sensitivity for lung cancer diagnosis with VDT <400 days as reference. RESULTS Sixty-eight fast-growing nodules were included; 40 % were malignant. The optimal VDT cutoff for the 3-month follow-up CT after baseline was 232 days. This cutoff reduced false-positive referrals by 33 % (20 versus 30). For the regular second round, VDTs varied more among malignant nodules, precluding lowering of the VDT cutoff of 400 days. CONCLUSION All malignant fast-growing lung nodules referred after the 3-month follow-up CT in the baseline lung cancer screening round had VDT ≤232 days. Lowering the VDT cutoff may reduce false-positive referrals. KEY POINTS • Lung nodules are common in CT lung cancer screening, most being benign • Short-term follow-up CT can identify fast-growing intermediate-size lung nodules • Most fast-growing nodules on short-term follow-up CT still prove to be benign • A new volume-doubling time (VDT) cut-off is proposed for lung screening • The optimised VDT cutoff may decrease false-positive case referrals for lung cancer.
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Affiliation(s)
- Marjolein A Heuvelmans
- Center for Medical Imaging-North East Netherlands, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
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