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Items: 1 to 20 of 66

1.

Limited value of logistic regression analysis in solid solitary pulmonary nodules characterization: a single-center experience on 288 consecutive cases.

Perandini S, Soardi GA, Motton M, Dallaserra C, Montemezzi S.

J Surg Oncol. 2014 Dec;110(7):883-7. doi: 10.1002/jso.23730. Epub 2014 Aug 2.

PMID:
25088475
2.

Novel and convenient method to evaluate the character of solitary pulmonary nodule-comparison of three mathematical prediction models and further stratification of risk factors.

Xiao F, Liu D, Guo Y, Shi B, Song Z, Tian Y, Liang C.

PLoS One. 2013 Oct 29;8(10):e78271. doi: 10.1371/journal.pone.0078271. eCollection 2013.

3.

[Risk factor analysis of the patients with solitary pulmonary nodules and establishment of a prediction model for the probability of malignancy].

Wang X, Xu YH, Du ZY, Qian YJ, Xu ZH, Chen R, Shi MH.

Zhonghua Zhong Liu Za Zhi. 2018 Feb 23;40(2):115-120. doi: 10.3760/cma.j.issn.0253-3766.2018.02.007. Chinese.

PMID:
29502371
4.

Solid pulmonary nodule risk assessment and decision analysis: comparison of four prediction models in 285 cases.

Perandini S, Soardi GA, Motton M, Rossi A, Signorini M, Montemezzi S.

Eur Radiol. 2016 Sep;26(9):3071-6. doi: 10.1007/s00330-015-4138-9. Epub 2015 Dec 8.

PMID:
26645862
5.

A Modified Model for Preoperatively Predicting Malignancy of Solitary Pulmonary Nodules: An Asia Cohort Study.

Zheng B, Zhou X, Chen J, Zheng W, Duan Q, Chen C.

Ann Thorac Surg. 2015 Jul;100(1):288-94. doi: 10.1016/j.athoracsur.2015.03.071. Epub 2015 May 30.

PMID:
26037540
6.

Development and validation of a clinical prediction model to estimate the probability of malignancy in solitary pulmonary nodules in Chinese people.

Li Y, Chen KZ, Wang J.

Clin Lung Cancer. 2011 Sep;12(5):313-9. doi: 10.1016/j.cllc.2011.06.005.

PMID:
21889113
7.

Indeterminate lung nodules in cancer patients: pretest probability of malignancy and the role of 18F-FDG PET/CT.

Evangelista L, Panunzio A, Polverosi R, Pomerri F, Rubello D.

AJR Am J Roentgenol. 2014 Mar;202(3):507-14. doi: 10.2214/AJR.13.11728.

PMID:
24555586
8.

Mini-invasive diagnosis and synchronous treatment of solitary pulmonary nodule.

Lin Y, Liu L, Pu Q.

Asian Cardiovasc Thorac Ann. 2013 Jun;21(3):306-12. doi: 10.1177/0218492312452268.

PMID:
24570497
9.

Validation of two models to estimate the probability of malignancy in patients with solitary pulmonary nodules.

Schultz EM, Sanders GD, Trotter PR, Patz EF Jr, Silvestri GA, Owens DK, Gould MK.

Thorax. 2008 Apr;63(4):335-41. Epub 2007 Oct 26.

10.

[Development of a predicting model to estimate the probability of malignancy of solitary pulmonary nodules].

Tian R, Su MG, Tian Y, Li FL, Kuang AR.

Sichuan Da Xue Xue Bao Yi Xue Ban. 2012 May;43(3):404-8. Chinese.

PMID:
22812247
11.

Assessing probability of malignancy in solid solitary pulmonary nodules with a new Bayesian calculator: improving diagnostic accuracy by means of expanded and updated features.

Soardi GA, Perandini S, Motton M, Montemezzi S.

Eur Radiol. 2015 Jan;25(1):155-62. doi: 10.1007/s00330-014-3396-2. Epub 2014 Sep 3.

PMID:
25182626
12.

Significance of non-calcified pulmonary nodules in patients with extrapulmonary cancers.

Khokhar S, Vickers A, Moore MS, Mironov S, Stover DE, Feinstein MB.

Thorax. 2006 Apr;61(4):331-6. Epub 2006 Feb 7.

13.

[Establishment of A Clinical Prediction Model of Solid Solitary Pulmonary Nodules].

Yu W, Ye B, Xu L, Wang Z, Le H, Wang S, Cao H, Chai Z, Chen Z, Luo Q, Zhang Y.

Zhongguo Fei Ai Za Zhi. 2016 Oct 20;19(10):705-710. Chinese.

14.

Noninvasive characterization of the histopathologic features of pulmonary nodules of the lung adenocarcinoma spectrum using computer-aided nodule assessment and risk yield (CANARY)--a pilot study.

Maldonado F, Boland JM, Raghunath S, Aubry MC, Bartholmai BJ, Deandrade M, Hartman TE, Karwoski RA, Rajagopalan S, Sykes AM, Yang P, Yi ES, Robb RA, Peikert T.

J Thorac Oncol. 2013 Apr;8(4):452-60. doi: 10.1097/JTO.0b013e3182843721.

15.

Solitary pulmonary nodules: dynamic contrast-enhanced MR imaging--perfusion differences in malignant and benign lesions.

Schaefer JF, Vollmar J, Schick F, Vonthein R, Seemann MD, Aebert H, Dierkesmann R, Friedel G, Claussen CD.

Radiology. 2004 Aug;232(2):544-53. Epub 2004 Jun 23.

PMID:
15215548
16.

Coexisting pulmonary nodules in operable lung cancer: prevalence and probability of malignancy.

Ruppert AM, Lerolle U, Carette MF, Lavole A, Khalil A, Bazelly B, Antoine M, Cadranel J, Milleron B.

Lung Cancer. 2011 Nov;74(2):233-8. doi: 10.1016/j.lungcan.2011.03.012. Epub 2011 Apr 20.

PMID:
21511355
17.

Overestimated value of (18)F-FDG PET/CT to diagnose pulmonary nodules: Analysis of 298 patients.

Li S, Zhao B, Wang X, Yu J, Yan S, Lv C, Yang Y.

Clin Radiol. 2014 Aug;69(8):e352-7. doi: 10.1016/j.crad.2014.04.007. Epub 2014 May 27.

PMID:
24877581
18.

Simultaneous computed tomography-guided biopsy and radiofrequency ablation of solitary pulmonary malignancy in high-risk patients.

Schneider T, Puderbach M, Kunz J, Bischof A, Giesel FL, Dienemann H, Herth FJ, Schnabel PA, Safi S, Hoffmann H, Heussel CP.

Respiration. 2012;84(6):501-8. doi: 10.1159/000342874. Epub 2012 Oct 2.

19.

Morphological characteristics of malignant solitary pulmonary nodules.

Pasławski M, Krzyzanowski K, Złomaniec J, Gwizdak J.

Ann Univ Mariae Curie Sklodowska Med. 2004;59(1):6-13.

PMID:
16145947
20.

Efficacy of PET/CT in the characterization of solid or partly solid solitary pulmonary nodules.

Jeong SY, Lee KS, Shin KM, Bae YA, Kim BT, Choe BK, Kim TS, Chung MJ.

Lung Cancer. 2008 Aug;61(2):186-94. doi: 10.1016/j.lungcan.2007.12.021. Epub 2008 Feb 15.

PMID:
18280613

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