RESUMEN
Whether used as a single modality or as part of a combined approach, radiation therapy (RT) plays an essential role in the treatment of several head and neck malignancies. Despite the improvement in radiation delivery techniques, normal structures in the vicinity of the target area remain susceptible to a wide range of adverse effects. Given their high incidence, some of these effects are referred to as expected postradiation changes (eg, mucositis, sialadenitis, and edema), while others are considered true complications, meaning they should not be expected and can even represent life-threatening conditions (eg, radionecrosis, fistulas, and radiation-induced neoplasms). Also, according to their timing of onset, these deleterious effects can be divided into four groups: acute (during RT), subacute (within weeks to months), delayed onset (within months to years), and very delayed onset (after several years).The authors provide a comprehensive review of the most important radiation-induced changes related to distinct head and neck sites, focusing on their typical cross-sectional imaging features and correlating them with the time elapsed after treatment. Radiologists should not only be familiar with these imaging findings but also actively seek essential clinical data at the time of interpretation (including knowledge of the RT dose and time, target site, and manifesting symptoms) to better recognize imaging findings, avoid pitfalls and help guide appropriate management. © RSNA, 2022.
Asunto(s)
Neoplasias de Cabeza y Cuello , Traumatismos por Radiación , Neoplasias de Cabeza y Cuello/diagnóstico por imagen , Neoplasias de Cabeza y Cuello/radioterapia , Humanos , Cuello , Traumatismos por Radiación/diagnóstico por imagen , Traumatismos por Radiación/etiologíaRESUMEN
The external ear (EE) is an osseous-cartilaginous structure that extends from the auricle to the tympanic membrane. It is divided into two parts: the auricle (or pinna) and the external auditory canal (EAC). Given the ease of access to the EE, imaging studies are not always needed to make a diagnosis. However, when lesions block visual access to areas deep to the EE abnormality, complications are suspected, or there is lack of response to treatment, imaging becomes essential. A basic understanding of the embryologic development and knowledge of the anatomy of the auricle and EAC are useful for accurate diagnosis of EE lesions. Congenital, traumatic, inflammatory, neoplastic, and vascular conditions can affect the EE. An overview of the anatomy and embryologic development of the EE is presented, with discussion and illustrations of common and uncommon conditions that affect EE structures and a focus on the CT and MRI features that are of interest to radiologists. CT is usually the first diagnostic modality used to evaluate the EAC and is the superior method for demonstrating bone changes. MRI provides excellent tissue characterization and enables one to better define lesion extension and perineural tumor spread. In addition, a flowchart to facilitate the differential diagnosis of EE abnormalities is provided. Online supplemental material is available for this article. ©RSNA, 2022.
Asunto(s)
Conducto Auditivo Externo , Imagen por Resonancia Magnética , Diagnóstico Diferencial , Conducto Auditivo Externo/anomalías , Conducto Auditivo Externo/diagnóstico por imagen , Conducto Auditivo Externo/patología , HumanosRESUMEN
PURPOSE: The aim of this study was to prospectively compare the detection rate of 68Ga-DOTATATE PET-CT with 111In-octreotide SPECT-CT and conventional imaging (CI) in medullary thyroid carcinoma (MTC) patients with increased calcitonin (Ctn) levels but negative CI after thyroidectomy. METHODS: Fifteen patients with raised Ctn levels and/or CI evidence of recurrence underwent 68Ga-DOTATATE PET-CT, 111In-octreotide SPECT-CT and CI. Histopathology, CI and biochemical/clinical/imaging follow-up were used as the reference standard. PET/CT, SPECT/CT and CI were compared in a lesion-based and organ-based analysis. RESULTS: PET/CT evidenced recurrence in 14 of 15 patients. There were 13 true positive (TP), 1 true negative (TN), 1 false positive (FP) and no false negative (FN) cases, resulting in a sensitivity and accuracy of 100% and 93%. SPECT/CT was positive in 6 of 15 cases. There were 6 TP, 2 TN, 7 FN and no FP cases, resulting in a sensitivity of 46% and accuracy of 53%. CI procedures detected tumor lesions in 14 of 15 patients. There were 13 TP, 1TN, 1 FP and no FN cases with a sensitivity of 100% and accuracy of 93%. A significantly higher number of lesions was detected by PET/CT (112 lesions, p = 0.005) and CI (109 lesions, p = 0.005) in comparison to SPECT/CT (16 lesions). There was no significant difference between PET/CT and CI for the total number of detected lesions (p = 0.734). PET/CT detected more lesions than SPECT/CT regardless of the organ. PET/CT detected more bone lesions but missed some neck nodal metastases evidenced by CI. The number of lesions per region demonstrated by PET/CT and CI were similar in the other sites. CONCLUSION: 68Ga-DOTATATE PET/CT is superior to 111In-octreotide SPECT/CT for the detection of recurrent MTC demonstrating a significantly higher number of lesions. 68Ga-DOTATATE PET/CT showed a superior detection rate compared to CI in demonstrating bone metastases.
Asunto(s)
Carcinoma Neuroendocrino/tratamiento farmacológico , Octreótido/análogos & derivados , Compuestos Organometálicos , Tomografía Computarizada por Tomografía Computarizada de Emisión de Fotón Único/métodos , Neoplasias de la Tiroides/tratamiento farmacológico , Adulto , Anciano , Femenino , Humanos , Masculino , Persona de Mediana Edad , Recurrencia , Adulto JovenRESUMEN
The oral cavity and oropharynx are common locations of neoplastic lesions; neoplasms at these sites are often treated with surgery. The goal of this surgical treatment is to achieve tumor control while preserving, whenever possible, the function of local structures. The procedure used depends largely on the location and extension of the tumor and the disease stage. Follow-up evaluation of patients is done with computed tomography (CT) and magnetic resonance (MR) imaging. The ability to interpret characteristic features at CT and MR imaging is particularly important because normal anatomic structures are altered in specific patterns according to the distinct surgical technique applied. Anatomic changes resulting from the most commonly performed procedures (eg, glossectomy, pelvectomy, and mandibulectomy) will be presented with CT and MR images, multiplanar reconstructions, and schematic illustrations. Understanding of postsurgical CT and MR imaging findings is important to avoid misinterpretation and confusion. Familiarity with the typical postsurgical imaging appearance of the oral cavity and oropharynx is crucial for differentiating normal postsurgical changes from persistent or recurrent disease and for diagnosis of associated second primary malignancies. Knowledge of postsurgical findings is essential for analysis of the oral cavity and oropharynx and allows early diagnosis of tumor recurrence or typical complications after surgical reconstruction.
Asunto(s)
Imagen por Resonancia Magnética , Neoplasias de la Boca/patología , Neoplasias de la Boca/cirugía , Recurrencia Local de Neoplasia/diagnóstico , Neoplasia Residual/diagnóstico , Neoplasias Orofaríngeas/patología , Neoplasias Orofaríngeas/cirugía , Tomografía Computarizada por Rayos X , Humanos , Interpretación de Imagen Asistida por Computador , Complicaciones Posoperatorias/diagnósticoRESUMEN
PURPOSE: To develop a deep learning model for detecting brain abnormalities on MR images. MATERIALS AND METHODS: In this retrospective study, a deep learning approach using T2-weighted fluid-attenuated inversion recovery images was developed to classify brain MRI findings as "likely normal" or "likely abnormal." A convolutional neural network model was trained on a large, heterogeneous dataset collected from two different continents and covering a broad panel of pathologic conditions, including neoplasms, hemorrhages, infarcts, and others. Three datasets were used. Dataset A consisted of 2839 patients, dataset B consisted of 6442 patients, and dataset C consisted of 1489 patients and was only used for testing. Datasets A and B were split into training, validation, and test sets. A total of three models were trained: model A (using only dataset A), model B (using only dataset B), and model A + B (using training datasets from A and B). All three models were tested on subsets from dataset A, dataset B, and dataset C separately. The evaluation was performed by using annotations based on the images, as well as labels based on the radiology reports. RESULTS: Model A trained on dataset A from one institution and tested on dataset C from another institution reached an F1 score of 0.72 (95% CI: 0.70, 0.74) and an area under the receiver operating characteristic curve of 0.78 (95% CI: 0.75, 0.80) when compared with findings from the radiology reports. CONCLUSION: The model shows relatively good performance for differentiating between likely normal and likely abnormal brain examination findings by using data from different institutions.Keywords: MR-Imaging, Head/Neck, Computer Applications-General (Informatics), Convolutional Neural Network (CNN), Deep Learning Algorithms, Machine Learning Algorithms© RSNA, 2021Supplemental material is available for this article.