Original contributionPredicting deep neck space abscess using computed tomography
Introduction
The occurrence of deep neck space infections (DNSIs) have been declining since the advent of antibiotics; however, they still occur and represent challenging diagnostic and treatment problems. Traditionally, only infections that have progressed to abscesses have required surgical intervention. The diagnostic dilemma has been separating patients with abscesses from those with phlegmons, thereby eliminating unnecessary surgical procedures on certain patients.
Authors have investigated the use of computed tomography (CT) in predicting abscess from phlegmon in prior studies. These studies have reported a positive correlation between CT scans and intraoperative findings ranging from 40% to 100% [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]. Larger and broader studies, however, place the correlation between CT findings and intraoperative findings in a much narrower range. Choi et al [2] in a study with 70 patients found the positive predictive value to be 76%. Lazor et al [5] had a 10-year retrospective study found a positive predictive rate of 76.3%. Stone et al [7] reviewed the charts for a 8-year period and reported a 73.5% positive predictive value. Ungkanont et al [8] reviewed the records of 117 children for more than 6 years and found that CT scans correlate with surgical findings 83% of the time. Likewise, Vural et al [9] reported a 68% positive predictive value after reviewing 80 patient charts. None of these studies, however, have relied on objective findings in interpreting the CT scans. Rather, these studies have relied on radiologists' interpretations of CT findings, such as rim enhancement around an area of low attenuation and irregular or scalloping of the border [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]. Even these are subjective findings, and often it is hard to distinguish between abscess and phlegmon (Fig. 1, Fig. 2).
We undertook this study to investigate possible objective findings that would increase the predictive value of CT scans in differentiating phlegmon from abscess.
Section snippets
Methods and materials
We retrospectively reviewed the charts of patients treated at a tertiary care center for DNSIs for the years 2002 and 2003. Subjects were included if they had had a CT scan with contrast interpreted as an abscess within 24 hours before surgical exploration of the abscess. Based on our criteria, 32 patients were identified: 20 children (under the age of 18 years) and 12 adults. We recorded demographics such as age, length of preoperative intravenous antibiotic administration therapy, white blood
Results
We included a total of 32 patients in the study: 20 children and 12 adults. The ages ranged from 8 months to 89 years old. Of these patients, 24 had abscesses confirmed by surgery (14 children). The positive predictive value of CT scan in our study was 75% overall, 83% for adults, and 70% for children only. The organisms isolated from our cultures are displayed in Table 1. Multiple pathogens were isolated in 25% of all cultures. The average lengths of preoperative intravenous antibiotic
Discussion
A recent study found that CT scan with contrast was the preferred diagnostic method for DNSI [12] and its utility in diagnosing DNSI has previously been described [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]. In all of these studies, however, the diagnosis was based on subjective findings such as rim enhancement around a hypodense area. Despite this limitation, studies with large patient numbers have reported a positive correlation with surgical findings ranging from 68% to 83% [2], [5],
Conclusion
CT scans are an important tool in the diagnosis and management of DNSI. We believe that the differentiation between deep neck space phlegmons and abscesses is a clinical diagnosis to which CT scan can add valued information. CT scanning alone, however, cannot reliably distinguish abscess from phlegmon (Fig. 1, Fig. 2). Because of the potentially devastating outcome associated with this disease, treatment needs to be aggressive. Therefore, in the management of DNSI, it is expected and
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