@article {Heikkinen, author = {J. Heikkinen and J. Nurminen and J. Velhonoja and H. Irjala and T. Soukka and T. Happonen and M. Nyman and K. Mattila and J. Hirvonen}, title = {MRI Findings in Acute Tonsillar Infections}, year = {2021}, doi = {10.3174/ajnr.A7368}, publisher = {American Journal of Neuroradiology}, abstract = {BACKGROUND AND PURPOSE: Previous literature is vague on the prevalence and exact nature of abscesses in tonsillar infections, ranging from intratonsillar and peritonsillar collections to deep extension involving the parapharyngeal and retropharyngeal spaces. MR imaging has excellent diagnostic accuracy in detecting neck infections and can potentially clarify this issue. We sought to characterize the spectrum of MR imaging findings regarding tonsillar infections.MATERIALS AND METHODS: We conducted a retrospective cohort study of emergency neck MR imaging scans of patients with tonsillar infections. Imaging data were assessed in terms of signs of infection and the location of abscesses and were compared with clinical findings, final diagnoses, and surgical findings as reference standards.RESULTS: The study included 132 patients with tonsillar infection. Of these, 110 patients (83\%) had >=1 abscess (99 unilateral, 11 bilateral; average volume, 3.2 mL). Most abscesses were peritonsillar, and we found no evidence of intratonsillar abscess. Imaging showed evidence of parapharyngeal and retropharyngeal extension in 36\% and 10\% of patients, respectively. MR imaging had a high positive predictive value for both abscesses (0.98) and deep extension (0.86). Patients with large abscesses and widespread edema patterns had a more severe course of illness.CONCLUSIONS: Emergency neck MR imaging can accurately describe the extent and nature of abscess formation in tonsillar infections.CRPC-reactive proteinGdgadoliniumITAintratonsillar abscessLOSlength of the hospital stayPPVpositive predictive valuePTAperitonsillar abscessSLSsublingual spaceSMSsubmandibular spaceT2SIT2-signal intensityVSvisceral space}, issn = {0195-6108}, URL = {https://www.ajnr.org/content/early/2022/01/06/ajnr.A7368}, eprint = {https://www.ajnr.org/content/early/2022/01/06/ajnr.A7368.full.pdf}, journal = {American Journal of Neuroradiology} }