From the Departments of Radiation Oncology.
Medical Imaging.
Invest Radiol. 2022 Dec 1;57(12):810-818. doi: 10.1097/RLI.0000000000000902. Epub 2022 Jul 1.
Ultrasmall superparamagnetic iron oxide (USPIO)-enhanced magnetic resonance imaging (MRI) is a potential diagnostic tool for lymph node assessment in patients with head and neck cancer. Validation by radiologic-pathologic correlation is essential before the method is evaluated in clinical studies. In this study, MRI signal intensity patterns of lymph nodes are correlated to their histopathology to develop a new USPIO-enhanced MRI reading algorithm that can be used for nodal assessment in head and neck cancer patients.
Ten head and neck cancer patients underwent in vivo USPIO-enhanced MRI before neck dissection. An ex vivo MRI of the neck dissection specimen was performed for precise coregistration of in vivo MRI with histopathology. Normal clinical histopathological workup was extended with meticulous matching of all lymph nodes regarded as potentially metastatic based on their in vivo MRI signal intensity pattern. On the basis of histopathology of resected nodes, in vivo MRI signal characteristics were defined separating benign from malignant lymph nodes.
Fifteen of 34 node-to-node correlated lymph nodes with remaining signal intensity on T2*-weighted MRI were histopathologically metastatic and 19 were benign. Radiological analysis revealed that metastatic lymph nodes showed equal or higher MRI signal intensity when compared with lipid tissue on T2*-weighted MGRE sequence (15/16 lymph nodes; 94%), whereas healthy lymph nodes showed lower (17/19 lymph nodes; 89%) or complete attenuation of signal intensity (273/279; 98%) when compared with lipid tissue on T2*-weighted MGRE. Histopathology of all resected specimens identified 392 lymph nodes. Six lymph nodes with (micro)metastases were missed with in vivo MRI. Whether these 6 lymph nodes were correlated to a nonmalignant lymph node on in vivo MRI or could not be detected at all is unclear.
We developed a new reading algorithm to differentiate benign from malignant lymph nodes in head and neck cancer patients on the basis of their appearance on high-resolution T2*-weighted USPIO-enhanced MRI. Next steps involve validation of our reading algorithm to further improve the accuracy of neck lymph node staging with USPIO-enhanced MRI in prospective clinical studies with larger number of patients.
超顺磁性氧化铁（USPIO）增强磁共振成像（MRI）是一种用于评估头颈部癌症患者淋巴结的潜在诊断工具。在该方法在临床研究中进行评估之前，通过放射病理相关性验证至关重要。在这项研究中，我们将 MRI 信号强度模式与淋巴结的组织病理学相关联，以开发一种新的 USPIO 增强 MRI 阅读算法，该算法可用于头颈部癌症患者的淋巴结评估。
十名头颈部癌症患者在颈部解剖前行体内 USPIO 增强 MRI。对颈部解剖标本进行离体 MRI 检查，以便将体内 MRI 与组织病理学进行精确配准。在体内 MRI 信号强度模式的基础上，对所有被认为具有潜在转移可能性的淋巴结进行了细致的匹配，从而对正常的临床组织病理学检查进行了扩展。基于切除淋巴结的组织病理学，定义了体内 MRI 信号特征，将良性和恶性淋巴结区分开来。
在与残留信号强度相关的 34 个淋巴结中，15 个淋巴结在 T2*-加权 MRI 上呈阳性，组织病理学检查为转移性，19 个淋巴结为良性。放射学分析显示，与 T2*-加权 MGRE 序列中的脂质组织相比，转移性淋巴结的 MRI 信号强度相等或更高（15/16 个淋巴结；94%），而健康淋巴结的信号强度较低（17/19 个淋巴结；89%）或完全衰减（273/279 个淋巴结；98%）。所有切除标本的组织病理学检查均识别出 392 个淋巴结。6 个有（微）转移的淋巴结在体内 MRI 中漏诊。这些淋巴结是否与体内 MRI 上的非恶性淋巴结相关，或者根本无法检测到，尚不清楚。
我们开发了一种新的阅读算法，根据头颈部癌症患者高分辨率 T2*-加权 USPIO 增强 MRI 上的表现，将良性和恶性淋巴结区分开来。下一步是验证我们的阅读算法，以进一步提高前瞻性临床研究中 USPIO 增强 MRI 对头颈部癌症患者颈部淋巴结分期的准确性，这些研究需要纳入更多患者。
