Role of ultrasound in the diagnosis of cervical tuberculous lymphadenitis in children

The value of multimodal ultrasonography in evaluating therapeutic response of cervical tuberculous lymphadenitis to anti-tuberculosis drugs

Purpose

In order to research the value of multimodal ultrasonography in evaluating therapeutic response of cervical tuberculous lymphadenitis to anti-tuberculosis drugs.

Materials and methods

Sixty-one patients with cervical tuberculous lymphadenitis were enrolled in this study. Ultrasound examination was performed before systemic standard anti-tuberculosis treatment and within 1-2 months after treatment, and the patients were divided into effective group and ineffective group according to the follow-up at the sixth month. The multimodal ultrasound signs of the two groups were compared and analyzed.

Results

In the effective group, there were significant differences in the maximum diameter of lymph nodes, the echo of the surrounding tissue and the enlargement of the contrast area before and after treatment (p < 0.05). At 1-2 months after treatment, there were significant differences in the maximum diameter, pus changes, CDFI, elasticity scores, echo of surrounding tissues, changes in enlarged and non-enhanced areas after contrast enhancement between the effective group and the ineffective group (p < 0.05).

Conclusion

The multimodal ultrasound signs of the appearance of internal pus or non-enhancement area enlargement, enhanced echo of the surrounding tissue and enlargement after CEUS are related to poor prognosis, and may be used to evaluate the response of anti-tuberculosis chemotherapy when the size change of lymph node is not obvious in individual treatment.

Artificially intelligent differential diagnosis of enlarged lymph nodes with random vector functional link network plus

Differential diagnosis of enlarged lymph nodes (ELNs) is essential for the treatment of related patients. Though multi-modal ultrasound including B-mode, Doppler ultrasound, elastography and contrast-enhanced ultrasound (CEUS) can enhance diagnostic performance for ELNs, the scenario of having only single or dual modal data is often encountered. In this study, an artificially intelligent diagnosis model based on the learning using privileged information was proposed to aid in differential diagnosis of ELNs in the case of single or dual modal images. In our model, B-mode, or combined with another modality, was used as the standard information (SI) and other modalities were used as the privileged information (PI). The model was constructed through the combination of the SI and PI in the training stage. By learning from the training samples, a random vector functional link network with privileged information (RVFL+) was obtained, which was used to classify the testing samples of solely the SI. Results showed that the accuracy, precision and Youden's index of the RVFL+ model, using B-mode with elastography as the SI and CEUS as the PI, reached 78.4%, 92.4% and 54.9%, increased by 14.0%, 8.4% and 24.5% compared with the model using B-mode as the SI without the PI. The method based on the LUPI can improve the diagnostic performance for ELNs.

Heterotopic squamous epithelial inclusion cyst in a cervical lymph node in a child: a case report and literature review

BACKGROUND

A squamous epithelial inclusion cyst in a lymph node is a rare heterotopic phenomenon. Heterotopic squamous inclusion cysts in cervical lymph nodes are even rarer, and to date, only 3 such cases have been reported in the literature, none of which have described the ultrasound features. Here, we report a pediatric case, focusing on the ultrasonographic manifestations of the disease and the differential diagnosis of cervical space-occupying lesions in children.

CASE DESCRIPTION

We report the case of a 6-year-old boy in good health, who presented with a non-tender mass on the right side of the neck 1 month earlier. Some 7 days before admission, the mass gradually increased in size and became tender. Laboratory tests showed an increase in C-reactive protein of 17 mg/L (normal range: 0-8 mg/L). The physical examination revealed a palpable 3.0 cm × 2.0 cm mass with tenderness and poor mobility in the right submandibular region. Doppler ultrasonography showed an oval, ill-defined mass in the right submandibular area, consisting of a peripheral homogeneous hypoechoic component with hilar-like vascularity and an internal heterogeneous very hypoechoic component with patchy hyperechoic areas. The computed tomography (CT) scan showed a heterogeneously hypodense mass with irregular annular enhancement in the right submandibular region. Lymph node tuberculosis or space-occupying lesions were suspected based on the clinical and imaging findings. The mass was completely excised by surgery. The pathological diagnosis was a secondary infection of squamous epithelial inclusion cysts in the right cervical lymph node. The peripheral homogeneous hypoechoic component was normal lymph node tissue, and the internal heterogeneous very hypoechoic component was a squamous inclusion cyst with keratin debris. The patient was followed up for a total of 3 times after surgery, and no recurrence of the tumor was found.

CONCLUSIONS

Ultrasonography can help in the early diagnosis of heterotopic squamous inclusion cysts in children's cervical lymph nodes, and can be used to differentiate other cervical lesions. We reviewed the literature and found that this heterotopic phenomenon was more likely to occur in the submandibular region of the neck in younger patients. Surgery may be an effective treatment for this disease.

Tuberculosis conundrum - current and future scenarios: A proposed comprehensive approach combining laboratory, imaging, and computing advances

Tuberculosis (TB) remains a global threat, with the rise of multiple and extensively drug resistant TB posing additional challenges. The International health community has set various 5-yearly targets for TB elimination: mathematical modelling suggests that a 2050 target is feasible with a strategy combining better diagnostics, drugs, and vaccines to detect and treat both latent and active infection. The availability of rapid and highly sensitive diagnostic tools (Gene-Xpert, TB-Quick) will vastly facilitate population-level identification of TB (including rifampicin resistance and through it, multi-drug-resistant TB). Basic-research advances have illuminated molecular mechanisms in TB, including the protective role of Vitamin D. Also, Mycobacterium tuberculosis impairs the host immune response through epigenetic mechanisms (histone-binding modulation). Imaging will continue to be key, both for initial diagnosis and follow-up. We discuss advances in multiple imaging modalities to evaluate TB tissue changes, such as molecular imaging techniques (including pathogen-specific positron emission tomography imaging agents), non-invasive temporal monitoring, and computing enhancements to improve data acquisition and reduce scan times. Big data analysis and Artificial Intelligence (AI) algorithms, notably in the AI sub-field called “Deep Learning”, can potentially increase the speed and accuracy of diagnosis. Additionally, Federated learning makes multi-institutional/multi-city AI-based collaborations possible without sharing identifiable patient data. More powerful hardware designs - e.g., Edge and Quantum Computing- will facilitate the role of computing applications in TB. However, “Artificial Intelligence needs real Intelligence to guide it!” To have maximal impact, AI must use a holistic approach that incorporates time tested human wisdom gained over decades from the full gamut of TB, i.e., key imaging and clinical parameters, including prognostic indicators, plus bacterial and epidemiologic data. We propose a similar holistic approach at the level of national/international policy formulation and implementation, to enable effective culmination of TB’s endgame, summarizing it with the acronym “TB - REVISITED”.