MR Imaging of Vascular Malformations and Tumors of Head and Neck

Optimizing T2* imaging for adolescent and young adult patients at 7 T

BACKGROUND

T2*-weighted imaging at 7 T offers detailed visualization of brain structures, but image quality and artifacts depend on echo time (TE) adjustments. Optimizing TE is crucial for tissue contrast and artifact minimization.

OBJECTIVE

To evaluate the impact of TE on tissue contrast and image quality in T2*-weighted sequences at 7 T in adolescents and young adults.

MATERIALS AND METHODS

Ten adolescent and young adult patients underwent 7-T MRI with multi-echo T2*-weighted sequences. Six TEs (8.1 ms to 36 ms) were acquired. Signal contrast ratios (CR) for seven brain regions-caudate nuclei, corpus callosum genu, frontal cortex, cortical veins, globi pallidi, medullary veins, and left optic radiation-were analyzed. Two blinded neuroradiologists assessed image quality and artifact severity using a 4-point Likert scale (IQS). Statistical trends were analyzed using the Jonckheere-Terpstra test. A P-value < 0.05 was considered statistically significant.

RESULTS

The study cohort consisted of 4 male and 6 females; the median age of the patients was 16 years (range 15-23 years). CR increased significantly with higher TEs for most regions except the caudate, where CR decreased (P < 0.05). Longer TEs led to greater artifact severity in the brainstem, temporal, occipital, and frontal lobes (P < 0.02), but not in parietal lobes (P > 0.05). Kappa agreement for IQS was 0.76.

CONCLUSION

TE significantly affects contrast and artifacts in 7-T T2*-weighted imaging. TEs between 20 and 30 ms offer the best balance between tissue contrast and artifact severity, optimizing image quality for clinical and research applications.

Image-based Artificial Intelligence models in the diagnosis and classification of vascular anomalies of the soft tissue in the head and neck

BACKGROUND

The International Society for the Study of Vascular Anomalies (ISSVA) provides a detailed classification system to facilitate accurate diagnosis and management of these conditions based on clinical criteria, imaging, and histopathological findings. This review aims to systematically present the state of the art in Artificial Intelligence (AI) applications for the diagnosis, classification, and treatment planning of vascular anomalies affecting the soft tissues of the head and neck region.

METHODS

The PubMed research identified 86 articles. After the initial screening of titles and abstracts, 75 studies were excluded due to the following reasons: irrelevance to the review's scope, unsuitable patient population, or inappropriate study design. 11 pertinent papers were included for the full-text screening. At the end of the full-text evaluation, 3 studies were considered eligible to be revised.

RESULTS

Concerning the clinical, radiological, and histological diagnosis of vascular malformations, the three models reviewed seem to be promising in the classification of the different subtypes and the lesion's segmentation. The applications of AI achieved in the fields of radiology and dermatology are very promising. Any study did not provide a prospective validation cohort to verify the diagnostic performance but also to assess the usefulness of the model in clinical practice.

CONCLUSION

We can also affirm that a hybrid model, combining dermatological images, MRI or US images, and histological images, can be developed as a reliable AI tool, useful for clinicians from diagnosis to treatment decision-making and to supervise interventional procedures.

Lymphatic Malformation Initially Presenting as Snoring: A Case Report

We describe a case of lymphatic malformation (LM) with snoring as the primary symptom. The patient, an 11-year-old boy, sought medical attention due to "snoring that had worsened over 3 years, accompanied by shortness of breath for 1 month." The preoperative examination showed that the apnea-hypopnea index during sleep was 33.4. The average overnight blood oxygen saturation was 95.3%, reaching a lowest level of 79.9%. Magnetic resonance imaging identified a space-occupying lesion in the postpharyngeal space, leading to significant compression and narrowing of the pharyngeal cavity. This suggested the possibility of a vascular malformation, with a higher proportion of vascular components. The patient underwent resection of the pharyngeal mass and temporary tracheostomy under general anesthesia, and intraoperative freeze and postoperative pathological diagnoses confirmed LM. Postoperative prognosis was favorable.