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Wang X, Shi J, Liu Z. Advancements in the diagnosis and treatment of sub‑centimeter lung cancer in the era of precision medicine (Review). Mol Clin Oncol 2024; 20:28. [PMID: 38414512 PMCID: PMC10895471 DOI: 10.3892/mco.2024.2726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Accepted: 01/10/2024] [Indexed: 02/29/2024] Open
Abstract
Lung cancer is the malignancy with the highest global mortality rate and imposes a substantial burden on society. The increasing popularity of lung cancer screening has led to increasing number of patients being diagnosed with pulmonary nodules due to their potential for malignancy, causing considerable distress in the affected population. However, the diagnosis and treatment of sub-centimeter grade pulmonary nodules remain controversial. The evolution of genetic detection technology and the development of targeted drugs have positioned the diagnosis and treatment of lung cancer in the precision medicine era, leading to a marked improvement in the survival rate of patients with lung cancer. It has been established that lung cancer driver genes serve a key role in the development and progression of sub-centimeter lung cancer. The present review aimed to consolidate the findings on genes associated with sub-centimeter lung cancer, with the intent of serving as a reference for future studies and the personalized management of sub-centimeter lung cancer through genetic testing.
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Affiliation(s)
- Xiao Wang
- Department of Thoracic Surgery, Nanjing Drum Tower Hospital, Clinical College of Nanjing Medical University, Nanjing, Jiangsu 210008, P.R. China
| | - Jingwei Shi
- Department of Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu 210008, P.R. China
| | - Zhengcheng Liu
- Department of Thoracic Surgery, Nanjing Drum Tower Hospital, Clinical College of Nanjing Medical University, Nanjing, Jiangsu 210008, P.R. China
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Borghesi A, Coviello FL, Scrimieri A, Ciolli P, Ravanelli M, Farina D. Software-based quantitative CT analysis to predict the growth trend of persistent nonsolid pulmonary nodules: a retrospective study. Radiol Med 2023:10.1007/s11547-023-01648-z. [PMID: 37227661 DOI: 10.1007/s11547-023-01648-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 05/10/2023] [Indexed: 05/26/2023]
Abstract
PURPOSE Persistent nonsolid nodules (NSNs) usually exhibit an indolent course and may remain stable for several years; however, some NSNs grow quickly and require surgical excision. Therefore, identifying quantitative features capable of early discrimination between growing and nongrowing NSNs is becoming a crucial aspect of radiological analysis. The main purpose of this study was to evaluate the performance of an open-source software (ImageJ) to predict the future growth of NSNs detected in a Caucasian (Italian) population. MATERIAL AND METHODS We retrospectively selected 60 NSNs with an axial diameter of 6-30 mm scanned with the same acquisition-reconstruction parameters and the same computed tomography (CT) scanner. Software-based analysis was performed on thin-section CT images using ImageJ. For each NSNs, several quantitative features were extracted from the baseline CT images. The relationships of NSN growth with quantitative CT features and other categorical variables were analyzed using univariate and multivariable logistic regression analyses. RESULTS In multivariable analysis, only the skewness and linear mass density (LMD) were significantly associated with NSN growth, and the skewness was the strongest predictor of growth. In receiver operating characteristic curve analyses, the optimal cutoff values of skewness and LMD were 0.90 and 19.16 mg/mm, respectively. The two predictive models that included the skewness, with or without LMD, exhibited an excellent power for predicting NSN growth. CONCLUSION According to our results, NSNs with a skewness value > 0.90, specifically those with a LMD > 19.16 mg/mm, should require closer follow-up due to their higher growth potential, and higher risk of becoming an active cancer.
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Affiliation(s)
- Andrea Borghesi
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, ASST Spedali Civili of Brescia, Piazzale Spedali Civili, 1, 25123, Brescia, Italy.
| | - Felice Leopoldo Coviello
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, ASST Spedali Civili of Brescia, Piazzale Spedali Civili, 1, 25123, Brescia, Italy
| | - Alessandra Scrimieri
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, ASST Spedali Civili of Brescia, Piazzale Spedali Civili, 1, 25123, Brescia, Italy
| | - Pietro Ciolli
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, ASST Spedali Civili of Brescia, Piazzale Spedali Civili, 1, 25123, Brescia, Italy
| | - Marco Ravanelli
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, ASST Spedali Civili of Brescia, Piazzale Spedali Civili, 1, 25123, Brescia, Italy
| | - Davide Farina
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, ASST Spedali Civili of Brescia, Piazzale Spedali Civili, 1, 25123, Brescia, Italy
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Yan G, Li H, Fan X, Deng J, Yan J, Qiao F, Yan G, Liu T, Chen J, Wang L, Yang Y, Li Y, Zhao L, Bhetuwal A, McClure MA, Li N, Peng C. Multimodality CT imaging contributes to improving the diagnostic accuracy of solitary pulmonary nodules: a multi-institutional and prospective study. Radiol Oncol 2023; 57:20-34. [PMID: 36795007 PMCID: PMC10039475 DOI: 10.2478/raon-2023-0008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 12/05/2022] [Indexed: 02/17/2023] Open
Abstract
BACKGROUND Solitary pulmonary nodules (SPNs) are one of the most common chest computed tomography (CT) abnormalities clinically. We aimed to investigate the value of non-contrast enhanced CT (NECT), contrast enhanced CT (CECT), CT perfusion imaging (CTPI), and dual- energy CT (DECT) used for differentiating benign and malignant SPNs with a multi-institutional and prospective study. PATIENTS AND METHODS Patients with 285 SPNs were scanned with NECT, CECT, CTPI and DECT. Differences between the benign and malignant SPNs on NECT, CECT, CTPI, and DECT used separately (NECT combined with CECT, DECT, and CTPI were methods of A, B, and C) or in combination (Method A + B, A + C, B + C, and A + B + C) were compared by receiver operating characteristic curve analysis. RESULTS Multimodality CT imaging showed higher performances (sensitivities of 92.81% to 97.60%, specificities of 74.58% to 88.14%, and accuracies of 86.32% to 93.68%) than those of single modality CT imaging (sensitivities of 83.23% to 85.63%, specificities of 63.56% to 67.80%, and accuracies of 75.09% to 78.25%, all p < 0.05). CONCLUSIONS SPNs evaluated with multimodality CT imaging contributes to improving the diagnostic accuracy of benign and malignant SPNs. NECT helps to locate and evaluate the morphological characteristics of SPNs. CECT helps to evaluate the vascularity of SPNs. CTPI using parameter of permeability surface and DECT using parameter of normalized iodine concentration at the venous phase both are helpful for improving the diagnostic performance.
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Affiliation(s)
- Gaowu Yan
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Hongwei Li
- Department of Radiology, The Third Hospital of Mianyang and Sichuan Mental Health Center, Mianyang, China
| | - Xiaoping Fan
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Jiantao Deng
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Jing Yan
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Fei Qiao
- Department of CT and MRI, The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, China
| | - Gaowen Yan
- Department of Radiology, The First People's Hospital of Suining, Suining, China
| | - Tao Liu
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Jiankang Chen
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Lei Wang
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Yang Yang
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Yong Li
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Linwei Zhao
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Anup Bhetuwal
- Sichuan Key Laboratory of Medical Imaging and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Morgan A McClure
- Department of Radiology and Imaging; Institute of Rehabilitation and Development of Brain Function, The Second Clinical Medical College of North Sichuan Medical College Nanchong Central Hospital, Nanchong, China
| | - Na Li
- Department of Oncology, Suining Central Hospital, Suining, China
| | - Chen Peng
- Department of Gastroenterology, The First People's Hospital of Suining, Suining, China
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Shen C, Wu Q, Xia Q, Cao C, Wang F, Li Z, Fan L. Establishment of a malignancy and benignancy prediction model of sub-centimeter pulmonary ground-glass nodules based on the inflammation-cancer transformation theory. Front Med (Lausanne) 2022; 9:1007589. [PMID: 36275807 PMCID: PMC9581285 DOI: 10.3389/fmed.2022.1007589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 09/20/2022] [Indexed: 12/04/2022] Open
Abstract
Background In recent years, Chinese clinicians are frequently encountered by patients with multiple lung nodules and these intensity ground-glass nodules (GGNs) are usually small in size and some of them have no spicule sign. In addition, early lung cancer is diagnosed in large numbers of non-heavy smokers and individuals with no caner history. Obviously, the Mayo model is not applicable to these patients. The aim of the present study is to develop a new and more applicable model that can predict malignancy or benignancy of pulmonary GGNs based on the inflammation-cancer transformation theory. Materials and methods Included in this study were patients who underwent surgical resection or lung puncture biopsy of GGNs in Shanghai 10th People’s Hospital between January 1, 2018 and May 31, 2021 with the inclusion criterion of the maximum diameter of GGN < 1.0 cm. All the included patients had their pulmonary GGNs diagnosed by postoperative pathology. The patient data were analyzed to establish a prediction model and the predictive value of the model was verified. Results Altogether 100 GGN patients who met the inclusion criteria were included for analysis. Based on the results of logistic stepwise regression analysis, a mathematical predication equation was established to calculate the malignancy probability as follows: Malignancy probability rate (p) = ex/(1 + ex); p > 0.5 was considered as malignant and p ≤ 0.5 as benign, where x = 0.9650 + [0.1791 × T helper (Th) cell] + [0.2921 × mixed GGN (mGGN)] + (0.4909 × vascular convergence sign) + (0.1058 × chronic inflammation). According to this prediction model, the positive prediction rate was 73.3% and the negative prediction rate was 100% versus the positive prediction rate of 0% for the Mayo model. Conclusion By focusing on four major factors (chronic inflammation history, human Th cell, imaging vascular convergence sign and mGGNs), the present prediction model greatly improves the accuracy of malignancy or benignancy prediction of sub-centimeter pulmonary GGNs. This is a breakthrough innovation in this field.
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Affiliation(s)
- Changxing Shen
- Department of Integrated Traditional Chinese and Western Medicine, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
| | - Qiong Wu
- Liangcheng Xincun Community Health Services Center, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Qing Xia
- Department of Integrated Traditional Chinese and Western Medicine, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
| | - Chuanwu Cao
- Department of Integrated Traditional Chinese and Western Medicine, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
| | - Fei Wang
- Department of Integrated Traditional Chinese and Western Medicine, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
| | - Zhuang Li
- Department of Integrated Traditional Chinese and Western Medicine, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
| | - Lihong Fan
- Department of Integrated Traditional Chinese and Western Medicine, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China,*Correspondence: Lihong Fan,
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Rundo L, Ledda RE, di Noia C, Sala E, Mauri G, Milanese G, Sverzellati N, Apolone G, Gilardi MC, Messa MC, Castiglioni I, Pastorino U. A Low-Dose CT-Based Radiomic Model to Improve Characterization and Screening Recall Intervals of Indeterminate Prevalent Pulmonary Nodules. Diagnostics (Basel) 2021; 11:1610. [PMID: 34573951 PMCID: PMC8471292 DOI: 10.3390/diagnostics11091610] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 08/25/2021] [Accepted: 08/30/2021] [Indexed: 12/25/2022] Open
Abstract
Lung cancer (LC) is currently one of the main causes of cancer-related deaths worldwide. Low-dose computed tomography (LDCT) of the chest has been proven effective in secondary prevention (i.e., early detection) of LC by several trials. In this work, we investigated the potential impact of radiomics on indeterminate prevalent pulmonary nodule (PN) characterization and risk stratification in subjects undergoing LDCT-based LC screening. As a proof-of-concept for radiomic analyses, the first aim of our study was to assess whether indeterminate PNs could be automatically classified by an LDCT radiomic classifier as solid or sub-solid (first-level classification), and in particular for sub-solid lesions, as non-solid versus part-solid (second-level classification). The second aim of the study was to assess whether an LCDT radiomic classifier could automatically predict PN risk of malignancy, and thus optimize LDCT recall timing in screening programs. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, positive predictive value, negative predictive value, sensitivity, and specificity. The experimental results showed that an LDCT radiomic machine learning classifier can achieve excellent performance for characterization of screen-detected PNs (mean AUC of 0.89 ± 0.02 and 0.80 ± 0.18 on the blinded test dataset for the first-level and second-level classifiers, respectively), providing quantitative information to support clinical management. Our study showed that a radiomic classifier could be used to optimize LDCT recall for indeterminate PNs. According to the performance of such a classifier on the blinded test dataset, within the first 6 months, 46% of the malignant PNs and 38% of the benign ones were identified, improving early detection of LC by doubling the current detection rate of malignant nodules from 23% to 46% at a low cost of false positives. In conclusion, we showed the high potential of LDCT-based radiomics for improving the characterization and optimizing screening recall intervals of indeterminate PNs.
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Affiliation(s)
- Leonardo Rundo
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK;
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0RE, UK
| | - Roberta Eufrasia Ledda
- Unit of Radiological Sciences, Department of Medicine and Surgery (DiMeC), University of Parma, 43126 Parma, Italy; (R.E.L.); (G.M.); (N.S.)
- Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, 20133 Milan, Italy; (G.A.); (U.P.)
| | - Christian di Noia
- Department of Physics “Giuseppe Occhialini”, University of Milano-Bicocca, 20126 Milan, Italy;
| | - Evis Sala
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK;
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0RE, UK
| | - Giancarlo Mauri
- Department of Informatics, Systems and Communication, University of Milano-Bicocca, 20126 Milan, Italy;
| | - Gianluca Milanese
- Unit of Radiological Sciences, Department of Medicine and Surgery (DiMeC), University of Parma, 43126 Parma, Italy; (R.E.L.); (G.M.); (N.S.)
| | - Nicola Sverzellati
- Unit of Radiological Sciences, Department of Medicine and Surgery (DiMeC), University of Parma, 43126 Parma, Italy; (R.E.L.); (G.M.); (N.S.)
| | - Giovanni Apolone
- Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, 20133 Milan, Italy; (G.A.); (U.P.)
| | - Maria Carla Gilardi
- School of Medicine and Surgery, University of Milano-Bicocca, 20126 Milan, Italy; (M.C.G.); (M.C.M.)
| | - Maria Cristina Messa
- School of Medicine and Surgery, University of Milano-Bicocca, 20126 Milan, Italy; (M.C.G.); (M.C.M.)
- Institute of Biomedical Imaging and Physiology, Italian National Research Council (IBFM-CNR), Segrate, 20090 Milan, Italy
- Fondazione Tecnomed, University of Milano-Bicocca, 20900 Monza, Italy
| | - Isabella Castiglioni
- Department of Physics “Giuseppe Occhialini”, University of Milano-Bicocca, 20126 Milan, Italy;
- Institute of Biomedical Imaging and Physiology, Italian National Research Council (IBFM-CNR), Segrate, 20090 Milan, Italy
| | - Ugo Pastorino
- Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, 20133 Milan, Italy; (G.A.); (U.P.)
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van den Broek JJ, van Gestel T, Kol SQ, van Geel AM, Geenen RWF, Schreurs WH. Dealing with indeterminate pulmonary nodules in colorectal cancer patients; a systematic review. Eur J Surg Oncol 2021; 47:2749-2756. [PMID: 34119380 DOI: 10.1016/j.ejso.2021.05.043] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 04/29/2021] [Accepted: 05/28/2021] [Indexed: 02/07/2023] Open
Abstract
INTRODUCTION Indeterminate pulmonary nodules (IPNs) are frequently encountered on staging computed tomography (CT) in colorectal cancer (CRC) patients and they create diagnostic dilemmas. This systematic review and pooled analysis aims to estimate the incidence and risk of malignancy of IPNs and provide an overview of the existing literature on IPNs in CRC patients. MATERIALS AND METHODS EMBASE, Pubmed and the Cochrane database were searched for papers published between January 2005 and April 2020. Studies describing the incidence of IPNs and the risk of malignancy in CRC patients and where the full text was available in the English language were considered for inclusion. Exclusion criteria included studies that used chest X-ray instead of CT, liver metastasis cohorts, studies with less than 60 CRC patients and reviews. RESULTS A total of 18 studies met the inclusion criteria, involving 8637 patients. Pooled analysis revealed IPNs on staging chest CT in 1327 (15%) of the CRC patients. IPNs appeared to be metastatic disease during follow up in 16% of these patients. Regional lymph node metastases, liver metastases, location of the primary tumour in the rectum, larger IPN size and multiple IPNs are the five most frequently reported parameters predicting the risk of malignancy of IPNs. CONCLUSION A risk stratification model for CRC patients with IPNs is warranted to enable an adequate selection of high risk patients for IPN follow up and to diminish the use of unnecessary repetitive chest CT-scans in the many low risk patients.
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Affiliation(s)
- Joris J van den Broek
- Department of Surgery, Northwest Clinics, PO Box 501, 1815 JD, Alkmaar, the Netherlands.
| | - Tess van Gestel
- Department of Surgery, Northwest Clinics, PO Box 501, 1815 JD, Alkmaar, the Netherlands
| | - Sabrine Q Kol
- Department of Radiology, AUMC, De Boelelaan 1117, 1081 HV, Amsterdam, the Netherlands
| | - Anne M van Geel
- Department of Radiology, Northwest Clinics, PO Box 501, 1815 JD, Alkmaar, the Netherlands
| | - Remy W F Geenen
- Department of Radiology, Northwest Clinics, PO Box 501, 1815 JD, Alkmaar, the Netherlands
| | - Wilhelmina H Schreurs
- Department of Surgery, Northwest Clinics, PO Box 501, 1815 JD, Alkmaar, the Netherlands
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Stadelmann SA, Blüthgen C, Milanese G, Nguyen-Kim TDL, Maul JT, Dummer R, Frauenfelder T, Eberhard M. Lung Nodules in Melanoma Patients: Morphologic Criteria to Differentiate Non-Metastatic and Metastatic Lesions. Diagnostics (Basel) 2021; 11:diagnostics11050837. [PMID: 34066913 PMCID: PMC8148527 DOI: 10.3390/diagnostics11050837] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 04/28/2021] [Accepted: 05/05/2021] [Indexed: 12/01/2022] Open
Abstract
Lung nodules are frequent findings in chest computed tomography (CT) in patients with metastatic melanoma. In this study, we assessed the frequency and compared morphologic differences of metastases and benign nodules. We retrospectively evaluated 85 patients with melanoma (AJCC stage III or IV). Inclusion criteria were ≤20 lung nodules and follow-up using CT ≥183 days after baseline. Lung nodules were evaluated for size and morphology. Nodules with significant growth, nodule regression in line with RECIST assessment or histologic confirmation were judged to be metastases. A total of 438 lung nodules were evaluated, of which 68% were metastases. At least one metastasis was found in 78% of patients. A 10 mm diameter cut-off (used for RECIST) showed a specificity of 95% and a sensitivity of 20% for diagnosing metastases. Central location (n = 122) was more common in metastatic nodules (p = 0.009). Subsolid morphology (n = 53) was more frequent (p < 0.001), and calcifications (n = 13) were solely found in non-metastatic lung nodules (p < 0.001). Our data show that lung nodules are prevalent in about two-thirds of melanoma patients (AJCC stage III/IV) and the majority are metastases. Even though we found a few morphologic indicators for metastatic or non-metastatic lung nodules, morphology has limited value to predict the presence of lung metastases.
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Affiliation(s)
- Simone Alexandra Stadelmann
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich, Switzerland; (S.A.S.); (C.B.); (T.D.L.N.-K.); (T.F.)
| | - Christian Blüthgen
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich, Switzerland; (S.A.S.); (C.B.); (T.D.L.N.-K.); (T.F.)
| | - Gianluca Milanese
- Department of Medicine and Surgery (DiMeC), University of Parma, 43126 Parma, Italy;
| | - Thi Dan Linh Nguyen-Kim
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich, Switzerland; (S.A.S.); (C.B.); (T.D.L.N.-K.); (T.F.)
| | - Julia-Tatjana Maul
- Department of Dermatology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich, Switzerland; (J.-T.M.); (R.D.)
| | - Reinhard Dummer
- Department of Dermatology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich, Switzerland; (J.-T.M.); (R.D.)
| | - Thomas Frauenfelder
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich, Switzerland; (S.A.S.); (C.B.); (T.D.L.N.-K.); (T.F.)
| | - Matthias Eberhard
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich, Switzerland; (S.A.S.); (C.B.); (T.D.L.N.-K.); (T.F.)
- Correspondence: ; Tel.: +41-(0)44-255-9139; Fax: +41-(0)44-255-4443
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Borghesi A, Michelini S, Golemi S, Scrimieri A, Maroldi R. What's New on Quantitative CT Analysis as a Tool to Predict Growth in Persistent Pulmonary Subsolid Nodules? A Literature Review. Diagnostics (Basel) 2020; 10:E55. [PMID: 31973010 PMCID: PMC7168253 DOI: 10.3390/diagnostics10020055] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Revised: 01/16/2020] [Accepted: 01/19/2020] [Indexed: 12/23/2022] Open
Abstract
Pulmonary subsolid nodules (SSNs) are observed not infrequently on thin-section chest computed tomography (CT) images. SSNs persisting after a follow-up period of three to six months have a high likelihood of being pre-malignant or malignant lesions. Malignant SSNs usually represent the histologic spectrum of pulmonary adenocarcinomas, and pulmonary adenocarcinomas presenting as SSNs exhibit quite heterogeneous behavior. In fact, while most lesions show an indolent course and may grow very slowly or remain stable for many years, others may exhibit significant growth in a relatively short time. Therefore, it is not yet clear which persistent SSNs should be surgically removed and for how many years stable SSNs should be monitored. In order to solve these two open issues, the use of quantitative analysis has been proposed to define the "tailored" management of persistent SSNs. The main purpose of this review was to summarize recent results about quantitative CT analysis as a diagnostic tool for predicting the behavior of persistent SSNs. Thus, a literature search was conducted in PubMed/MEDLINE, Scopus, and Web of Science databases to find original articles published from January 2014 to October 2019. The results of the selected studies are presented and compared in a narrative way.
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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; (S.G.); (A.S.); (R.M.)
| | - Silvia Michelini
- Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Via Leonida Bissolati, 57, 25124 Brescia, Italy;
| | - Salvatore Golemi
- Department of Radiology, University and ASST Spedali Civili of Brescia, Piazzale Spedali Civili 1, 25123 Brescia, Italy; (S.G.); (A.S.); (R.M.)
| | - Alessandra Scrimieri
- Department of Radiology, University and ASST Spedali Civili of Brescia, Piazzale Spedali Civili 1, 25123 Brescia, Italy; (S.G.); (A.S.); (R.M.)
| | - Roberto Maroldi
- Department of Radiology, University and ASST Spedali Civili of Brescia, Piazzale Spedali Civili 1, 25123 Brescia, Italy; (S.G.); (A.S.); (R.M.)
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Borghesi A, Scrimieri A, Michelini S, Calandra G, Golemi S, Tironi A, Maroldi R. Quantitative CT Analysis for Predicting the Behavior of Part-Solid Nodules with Solid Components Less than 6 mm: Size, Density and Shape Descriptors. Applied Sciences 2019; 9:3428. [DOI: 10.3390/app9163428] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Persistent part-solid nodules (PSNs) with a solid component <6 mm usually represent minimally invasive adenocarcinomas and are significantly less aggressive than PSNs with a solid component ≥6 mm. However, not all PSNs with a small solid component behave in the same way: some nodules exhibit an indolent course, whereas others exhibit more aggressive behavior. Thus, predicting the future behavior of this subtype of PSN remains a complex and fascinating diagnostic challenge. The main purpose of this study was to apply open-source software to investigate which quantitative computed tomography (CT) features may be useful for predicting the behavior of a select group of PSNs. We retrospectively selected 50 patients with a single PSN with a solid component <6 mm and diameter <15 mm. Computerized analysis was performed using ImageJ software for each PSN and various quantitative features were calculated from the baseline CT images. The area, perimeter, mean Feret diameter, linear mass density, circularity and solidity were significantly related to nodule growth (p ≤ 0.031). Therefore, quantitative CT analysis was helpful for predicting the future behavior of a select group of PSNs with a solid component <6 mm and diameter <15 mm.
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