Arguments for a magnetic resonance imaging-assisted FIGO staging system for cervical cancer

2005 ◽  
Vol 15 (4) ◽  
pp. 573-582 ◽  
Author(s):  
K. NARAYAN
2005 ◽  
Vol 15 (4) ◽  
pp. 573-582 ◽  
Author(s):  
K. Narayan

FIGO staging of cervical cancer is based on anatomic compartmental spread of cervical cancer. This was necessary in the evaluation of surgical resectability in each patient. Even if the surgical resection was not deemed satisfactory, surgical findings and subsequent accurate anatomic pathology findings could be used to prescribe tailored adjuvant therapies. Recently, the management of cervical cancer has been influenced by the evidence from several surgical-pathologic studies and phase II and III combined modality treatment trials. However, the patient selection criteria used in these clinical studies were almost always refined by modern medical imaging and surgical techniques not prescribed in the FIGO staging system. The results obtained from these studies would not correlate with those from the patient population similarly treated but selected strictly along the FIGO staging criteria. This selective, heterogenous, and arbitrary refinement of FIGO staging has certainly given insight into cervical cancer biology but in the process has rendered the current FIGO staging of this disease quite inadequate. Prior knowledge of these factors through modern imaging in these patients could be used in staging and selecting the optimum treatment modality while minimizing the treatment-related morbidity. A magnetic resonance imaging-assisted FIGO staging system for cervical cancer as proposed here could be used for selecting patients appropriately for a given treatment package


2013 ◽  
Vol 128 (3) ◽  
pp. 449-453 ◽  
Author(s):  
Elisabeth Epstein ◽  
Antonia Testa ◽  
Adrius Gaurilcikas ◽  
Alessia Di Legge ◽  
Liveke Ameye ◽  
...  

Author(s):  
Sahar Mahmoud Abd elsalam ◽  
Omnia Mokhtar ◽  
Lamia Adel ◽  
Reda Hassan ◽  
Manal Ibraheim ◽  
...  

Radiotherapy ◽  
10.5772/67382 ◽  
2017 ◽  
Author(s):  
Kenji Yoshida ◽  
Ryo Nishikawa ◽  
Daisuke Miyawaki ◽  
Yasuhiko Ebina ◽  
Ryohei Sasaki

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