Suppr超能文献

The use of 201Tl SPET to predict the response to radiotherapy in patients with head and neck cancer.

作者信息

Nagamachi S, Jinnouchi S, Flores L G, Nakahara H, Ono S, Ohnishi T, Futami S, Watanabe K

机构信息

Department of Radiology, Miyazaki Medical College, Japan.

出版信息

Nucl Med Commun. 1996 Nov;17(11):935-42. doi: 10.1097/00006231-199611000-00003.

Abstract

Thallium-201 (201Tl) is widely used in the diagnosis of malignant tumours. However, its use in predicting the response to radiation therapy for head and neck cancer has not been established. Nineteen patients with histologically proven head and neck cancer were studied. 201Tl single photon emission tomographic (SPET) images were obtained 15 min (early) and 4 h (delayed) post-injection of the radionuclide. For a semi-quantitative assessment, regions of interest were drawn over the lesions and normal soft tissue. Lesion-to-normal tissue uptake ratios of 201Tl activity were measured from mean counts-per-voxel obtained on both the early and delayed scans, representing the early index (EI) and delayed index (DI) respectively. Subsequently, a retention index (RI) was calculated using the formula: RI = (DI - EI) x 100/(EI). The patients were classified into two groups according to the effect of radiotherapy: a partial response or complete response group (PR-CR group) and a no change group (NC group). In the analysis of primary lesions, both the delayed and retention indexes of the PR-CR group were significantly higher than those of the NC group. However, the early index was not significantly different between the two groups. In the metastatic lymph nodes, only the retention index was significantly different between the two groups. Our results demonstrate that 201Tl SPET and a 201Tl index can be used to predict the response to radiotherapy for primary head and neck cancer and lymph node metastases. The retention index is a useful parameter for estimating the effects of radiotherapy.

摘要

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验