Literature DB >> 18373824

Evaluation of chest wall invasion by lung cancer using respiratory dynamic MRI.

S Akata1, N Kajiwara, J Park, M Yoshimura, D Kakizaki, K Abe, T Hirano, T Ohira, M Tsuboi, H Kato.   

Abstract

Conventional CT or MRI has low accuracy in assessing chest wall invasion in patients with peripheral lung cancer. For preoperative evaluation of chest wall invasion by peripheral lung cancer, respiratory dynamic (RD) MRI was carried out in 98 patients in whom conventional CT scan showed that the tumour was abutting the pleural surface, but there was no evidence of definite tumour invasion. We used 1.5-T MR equipment. RD MR images were acquired by snapshot fast field echo sequence (repetition time = 8, echo time = 3, flip angle = 100) and 25 consecutive images were taken while the patient took deep breaths. These images were evaluated in cine mode to assess tumour movement along the chest wall. Sixty-one patients underwent surgical resection of the tumour and RD MR findings were compared with those in pathological specimens. RD MR showed free tumour movement along the chest wall in 34 patients. At pathological examination, the RD MR findings were proved correct in all patients. Pathologically, 20 patients had chest wall invasion and their RD MR was positive (sensitivity 100%). There were seven false-positive results among the 41 patients without chest wall invasion (specificity 82.9%). RD MR may improve the accuracy of conventional CT scan or MRI in the prediction of chest wall invasion of lung cancer, especially in patients in whom the results of conventional CT scan or MRI appear equivocal in the presence of a peripheral mass abutting the chest wall surface without obvious chest wall invasion.

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Year:  2008        PMID: 18373824     DOI: 10.1111/j.1440-1673.2007.01908.x

Source DB:  PubMed          Journal:  J Med Imaging Radiat Oncol        ISSN: 1754-9477            Impact factor:   1.735


  18 in total

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Review 2.  Prediction of pleural invasion using different imaging tools in non-small cell lung cancer.

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3.  Chest wall resection and reconstruction for lung cancer: surgical techniques and example of integrated multimodality approach.

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Journal:  J Thorac Dis       Date:  2020-01       Impact factor: 2.895

Review 4.  Diagnostic imaging in the preoperative management of lung cancer.

Authors:  Kazuhiro Imai; Yoshihiro Minamiya; Hajime Saito; Satoru Motoyama; Yusuke Sato; Aki Ito; Kei Yoshino; Satoshi Kudo; Shinogu Takashima; Yasushi Kawaharada; Nobuyasu Kurihara; Kimito Orino; Jun-Ichi Ogawa
Journal:  Surg Today       Date:  2013-07-10       Impact factor: 2.549

5.  Preoperative assessment of parietal pleural invasion/adhesion of subpleural lung cancer: advantage of software-assisted analysis of 4-dimensional dynamic-ventilation computed tomography.

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Journal:  Eur Radiol       Date:  2019-03-26       Impact factor: 5.315

Review 6.  Primary lung tumors invading the chest wall.

Authors:  Pier Luigi Filosso; Alberto Sandri; Francesco Guerrera; Paolo Solidoro; Giulia Bora; Paraskevas Lyberis; Enrico Ruffini; Alberto Oliaro
Journal:  J Thorac Dis       Date:  2016-11       Impact factor: 2.895

7.  Video-assisted thoracoscopic surgery lobectomy with chest wall resection.

Authors:  Guilherme Dal Agnol; Ricardo Oliveira; Paula A Ugalde
Journal:  J Thorac Dis       Date:  2018-08       Impact factor: 2.895

8.  MRI of the lung (3/3)-current applications and future perspectives.

Authors:  Jürgen Biederer; S Mirsadraee; M Beer; F Molinari; C Hintze; G Bauman; M Both; E J R Van Beek; J Wild; M Puderbach
Journal:  Insights Imaging       Date:  2012-01-15

9.  Magnetic resonance imaging of the chest in the evaluation of cancer patients: state of the art.

Authors:  Marcos Duarte Guimaraes; Bruno Hochhegger; Marcel Koenigkam Santos; Pablo Rydz Pinheiro Santana; Arthur Soares Sousa; Luciana Soares Souza; Edson Marchiori
Journal:  Radiol Bras       Date:  2015 Jan-Feb

Review 10.  Imaging of anterior mediastinal tumours.

Authors:  Ching Ching Ong; Lynette L S Teo
Journal:  Cancer Imaging       Date:  2012-11-02       Impact factor: 3.909

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