El-Sayed Samy, Bezabeh Tedros, Odlum Olva, Patel Rakesh, Ahing Stephen, MacDonald Kelly, Somorjai Ray L, Smith Ian C P
CancerCare Manitoba, Winnipeg, Canada.
Head Neck. 2002 Aug;24(8):766-72. doi: 10.1002/hed.10125.
Definitive diagnosis of head and neck cancer is generally made by histopathologic evaluation. Management and prognosis largely depend on accurate and timely diagnosis. We have explored the use of (1)H magnetic resonance spectroscopy in search of a better or complementary diagnostic technique.
Tumor and adjacent normal tissue specimens (n = 135) from untreated head and neck cancer patients (n = 40) were obtained and subjected to spectroscopic evaluation followed by histopathologic analysis. Data were partitioned into training and test sets and subjected to multivariate analysis.
The resonances from taurine, choline, glutamic acid, lactic acid, and lipid were found to have diagnostic potential by our optimal region selection algorithm. Multivariate analysis of the spectral data differentiated between normal and malignant tissues, with an overall accuracy of 92.6% (training set, 97.3%; test set, 87.3%), an overall sensitivity of 93% (test set, 90%), and an overall specificity of 92% (test set, 82.6%).
(1)H magnetic resonance spectroscopy combined with multivariate methods of analysis can distinguish between normal and malignant squamous cell tissue, and this may lead to the development of an objective and noninvasive diagnostic procedure.
头颈部癌症的确诊通常依靠组织病理学评估。治疗和预后很大程度上取决于准确及时的诊断。我们探索了利用氢磁共振波谱寻找更好的或辅助性诊断技术。
从未经治疗的头颈部癌症患者（n = 40）获取肿瘤及相邻正常组织标本（n = 135），进行波谱评估，随后进行组织病理学分析。数据被分为训练集和测试集并进行多变量分析。
通过我们的最佳区域选择算法发现，牛磺酸、胆碱、谷氨酸、乳酸和脂质的共振具有诊断潜力。光谱数据的多变量分析区分了正常组织和恶性组织，总体准确率为92.6%（训练集为97.3%；测试集为87.3%），总体敏感度为93%（测试集为90%），总体特异度为92%（测试集为82.6%）。
氢磁共振波谱结合多变量分析方法能够区分正常和恶性鳞状细胞组织，这可能会促成一种客观、无创的诊断程序的开发。
