RESUMEN
Background: Fallopian tubal tuberculosis (FTTB), which typically presents with non-specific clinical symptoms and mimics ovarian malignancies clinically and radiologically, often affects young reproductive females and can lead to infertility if not promptly managed. Early diagnosis by imaging modalities is crucial for initiating timely anti-tuberculosis (anti-TB) treatment. Currently, comprehensive radiological descriptions of this relatively rare disease are limited. We aimed to comprehensively investigate the computed tomography (CT) and magnetic resonance imaging (MRI) characteristics of FTTB in patients from the Kashi area, which has the highest incidence of TB in China, to extend radiologists' understanding of this disease. Methods: We conducted a retrospective cross-sectional study of 26 patients diagnosed with FTTB at the First People's Hospital of Kashi Area. All the patients underwent abdominal and pelvic contrast-enhanced CT examinations and/or pelvic contrast-enhanced MRI from January 2017 to June 2022. The imaging findings were evaluated in consensus by two experienced radiologists specialized in abdominal and pelvic imaging. The evaluated sites included the fallopian tubes, ovaries, peritoneum, mesentery, retroperitoneal nodes, and parailiac nodes. The patient characteristics are reported using descriptive statistics. The patient imaging results are presented as percentages. The normally distributed continuous variables are reported as the mean ± standard deviation (SD), and otherwise as the median with the interquartile range (IQR). Results: The median age of the patients was 27 years (IQR: 25-34 years). Bilateral involvement of the fallopian tubes was observed in all patients. The tubal wall appeared coarse with tiny intraductal nodules in 96% (25 of 26) of the patients. The mean CT value of the tubal contents was 34 Hounsfield units (HUs; SD: 3.3 HUs). Ascites was present in 92% (24 of 26) of the patients, with 20 patients showing encapsulated effusion. Among these patients, 20 exhibited the highest CT values of ascites (>20 HUs). Linear enhancement of the parietal peritoneum was observed in 88% (23 of 26) of the patients, of whom 22 had peritoneal nodules measuring a median diameter of 0.4 cm (IQR: 0.3-0.6 cm). Eight patients had retroperitoneal and parailiac nodal enlargement, of whom two showed nodal necrosis, and none displayed nodal calcification. Conclusions: FTTB is consistently accompanied by tuberculous peritonitis. FTTB typically presents with tubal dilation, and coarseness and nodules in the lumen, as well as intraductal caseous material and calcification. Tuberculous peritonitis exhibits high-density ascites, peritoneal adhesion, linear enhancement of the parietal peritoneum, and tiny peritoneal nodules. The co-occurrence of these features strongly suggests a diagnosis of FTTB.
RESUMEN
Background: There is a wealth of poorly utilized unstructured data on lymphoma metabolism, and scientometrics and visualization study could serve as a robust tool to address this issue. Hence, it was implemented. Methods: After strict quality control, numerous data regarding the lymphoma metabolism were mined, quantified, cleaned, fused, and visualized from documents (n = 2925) limited from 2013 to 2022 using R packages, VOSviewer, and GraphPad Prism. Results: The linear fitting analysis generated functions predicting the annual publication number (y = 31.685x - 63628, R² = 0.93614, Prediction in 2027: 598) and citation number (y = 1363.7x - 2746019, R² = 0.94956, Prediction in 2027: 18201). In the last decade, the most academically performing author, journal, country, and affiliation were Meignan Michel (n = 35), European Journal of Nuclear Medicine and Molecular Imaging (n = 1653), USA (n = 3114), and University of Pennsylvania (n = 86), respectively. The hierarchical clustering based on unsupervised learning further divided research signatures into five clusters, including the basic study cluster (Cluster 1, Total Link Strength [TLS] = 1670, Total Occurrence [TO] = 832) and clinical study cluster (Cluster 3, TLS = 3496, TO = 1328). The timeline distribution indicated that radiomics and artificial intelligence (Cluster 4, Average Publication Year = 2019.39 ± 0.21) is a relatively new research cluster, and more endeavors deserve. Research signature burst and linear regression analysis further confirmed the findings above and revealed additional important results, such as tumor microenvironment (a = 0.6848, R² = 0.5194, p = 0.019) and immunotherapy (a = 1.036, R² = 0.6687, p = 0.004). More interestingly, by performing a "Walktrap" algorithm, the community map indicated that the "apoptosis, metabolism, chemotherapy" (Centrality = 12, Density = 6), "lymphoma, pet/ct, prognosis" (Centrality = 11, Density = 1), and "genotoxicity, mutagenicity" (Centrality = 9, Density = 4) are crucial but still under-explored, illustrating the potentiality of these research signatures in the field of the lymphoma metabolism. Conclusion: This study comprehensively mines valuable information and offers significant predictions about lymphoma metabolism for its clinical and experimental practice.
