Tumor volume: An independent predictor of outcome for laryngeal cancer

Citation
Sk. Mukherji et al., Tumor volume: An independent predictor of outcome for laryngeal cancer, J COMPUT AS, 23(1), 1999, pp. 50-54
Citations number
23
Categorie Soggetti
Radiology ,Nuclear Medicine & Imaging","Medical Research Diagnosis & Treatment
Journal title
JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY
ISSN journal
03638715 → ACNP
Volume
23
Issue
1
Year of publication
1999
Pages
50 - 54
Database
ISI
SICI code
0363-8715(199901/02)23:1<50:TVAIPO>2.0.ZU;2-R
Abstract
Purpose: Other studies have shown a relationship between the Volume of lary ngeal tumors and local control when treated with radiation therapy. Our pur pose was to determine the relationship between tumor volume, clinical stagi ng, and several histologic abnormalities to local control in patients treat ed with initial surgery. Method: Tumor Volume was calculated from pretreatment CT scans in 52 patien ts with squamous cell carcinoma treated surgically. The presence of perineu ral and lymphatic spread as well as cartilage and vessel invasion were obta ined from histology. All cases had at least a 2 year clinical follow-up aft er initial surgery. Statistical analysis consisted of ManteI-Haneszel chi(2 )-tests and Fisher exact test. Results: Local control rate was 92%. Tumor volume and cartilage invasion we re associated with local control (p < 0.05). Local control rate for tumors with volumes of <16 cm(3) was 98% compared with 40% for tumors with Volumes of >16 cm(3) (p < 0.05). Evidence of cartilage invasion was associated wit h increased likelihood of local recurrence. There was no significant associ ation between local control and perineural, vascular, or lymphatic tumor sp read, We found a marginally significant association between clinical T-stag e and local control (p = 0.05). Conclusion: Pretreatment CT volumes are useful in predicting local control in laryngeal carcinoma treated with surgery. Of the histologic features stu died, only cartilage invasion was significant in predicting tumor control.