Search

Introduction: FIGO 2018 IIIC remains controversial for the heterogeneity of its prognoses. To ensure a better management of cervical cancer patients in Stage IIIC, a revision of the FIGO IIIC version classification is required according to local tumor size. Material and methods: We retrospectively enrolled cervical cancer patients of FIGO 2018 Stages I–IIIC who had undergone radical surgery or chemoradiotherapy. Based on the tumor factors from the Tumor Node Metastasis staging system, IIIC cases were divided into IIIC‐T1, IIIC‐T2a, IIIC‐T2b, and IIIC‐(T3a+T3b). Oncologcial outcomes of all stages were compared. Results: A total of 63 926 cervical cancer cases were identified, among which 9452 fulfilled the inclusion criteria and were included in this study. Kaplan–Meier pairwise analysis showed that: the oncology outcomes of I and IIA were significantly better than of IIB, IIIA+IIIB, and IIIC; the oncology outcome of IIIC‐(T1‐T2b) was significantly better than of IIIA+IIIB and IIIC‐(T3a+T3b); no significant difference was noted between IIB and IIIC‐(T1‐T2b), or IIIC‐(T3a+T3b) and IIIA+IIIB. Multivariate analysis indicated that, compared with IIIC‐T1, Stages T2a, T2b, IIIA+IIIB and IIIC‐(T3a+T3b) were associated with a higher risk of death and recurrence/death. There was no significant difference in the risk of death or recurrence/death between patients with IIIC‐(T1‐T2b) and IIB. Also, compared with IIB, IIIC‐(T3a+T3b) was associated with a higher risk of death and recurrence/death. No significant differences in the risk of death and recurrence/death were noted between IIIC‐(T3a+T3b) and IIIA+IIIB. Conclusions: In terms of oncology outcomes of the study, FIGO 2018 Stage IIIC of cervical cancer is unreasonable. Stages IIIC‐T1, T2a, and T2b may be integrated as IIC, and it might be unnecessary for T3a/T3b cases to be subdivided by lymph node status. [ABSTRACT FROM AUTHOR]

Development of a deep learning-based nomogram for predicting lymph node metastasis in cervical cancer: A multicenter study Oversampling methods were used to balance the ratio of LNM-positive patients and LNM-negative patients in the training cohort. (A) A lymph node metastasis (LNM)-positive patient correctly diagnosed by both DLN and gynecologists; (B) An LNM-positive patient only correctly diagnosed by DLN; (C) An LNM-negative patient only correctly diagnosed by DLN; (D) An LNM-positive patient correctly diagnosed by both DLN and gynecologists gl Subgroup analysis was performed on the data of the enrolled patients, including their clinical characteristics, the CT manufacturers, and the centers. Dear Editor, Cervical cancer is one of the most frequently diagnosed cancers in women and has a high mortality rate worldwide.1 Lymph node metastasis (LNM) is an important prognostic factor in patients with cervical cancer.2-4 The assessment of LNM before treatment is essential to guide and tailor the treatment.5,6 The morphological examination of lymph nodes via medical images is commonly used for diagnosing LNM. [Extracted from the article]

Objective: This study aimed to explore the best treatment strategy for International Federation of Gynecology and Obstetrics (FIGO) 2018 stage IIA1 cervical cancer patients by comparing the survival outcomes of two treatment methods: abdominal radical hysterectomy (ARH) with standard postoperative therapy and radio-chemotherapy (R-CT). Methods: Patients with FIGO2018 stage IIA1 cervical cancer who underwent ARH or received R-CT were screened from the clinical diagnosis and treatment for cervical cancer in China (Four C) database. The recurrence cases between the two groups were analyzed. The 5-year overall survival (OS) and disease-free survival (DFS) of patients diagnosed with stage IIA1 cervical cancer in 47 hospitals in mainland China between 2004 and 2018 were compared by using propensity score matching (PSM). Results: A total of 724 patients met the inclusion criteria. In the total study population, The R-CT group had higher recurrence (22.8% for the R-CT group and 11.2% for the ARH group, P <0.001) rates compared to the ARH group.The 5-year OS and DFS of the ARH group (n=658) were significantly higher than those of the R-CT group (n=66) (OS: 85.9% vs. 71.2%, P =0.009; DFS: 79.2% vs. 70.5%, P =0.027). R-CT was associated with worse 5-year OS (HR=3.19, 95% CI: 1.592-6.956, P =0.001) and DFS (HR=2.089, 95% CI: 1.194-3.656, P =0.01). After 1:2 PSM, the 5-year OS and DFS of the ARH group (n=126) were significantly higher than those of the R-CT group (n=64) (OS:88.9% vs. 70.1%, P =0.04; DFS:82.8% vs. 69.8%, P =0.019). R-CT was still associated with worse 5-year OS (HR=2.391, 95% CI: 1.051-5.633, P =0.046) and DFS (HR=2.6, 95% CI: 1.25-5.409, P =0.011). Conclusion: Our study demonstrated that for stage FIGO2018 stage IIA1 cervical cancer patients, ARH offers better oncological outcomes than R-CT. [ABSTRACT FROM AUTHOR]

Objective: To investigate whether pre-treatment CT-derived radiomic features could be applied for prediction of clinical response to neoadjuvant chemotherapy (NACT) in locally advanced cervical cancer (LACC). Patients and Methods: Two hundred and seventy-seven LACC patients treated with NACT followed by surgery/radiotherapy were included in this multi-institution retrospective study. One thousand and ninety-four radiomic features were extracted from venous contrast enhanced and non-enhanced CT imaging for each patient. Five combined methods of feature selection were used to reduce dimension of features. Radiomics signature was constructed by Random Forest (RF) method in a primary cohort of 221 patients. A combined model incorporating radiomics signature with clinical factors was developed using multivariable logistic regression. Prediction performance was then tested in a validation cohort of 56 patients. Results: Radiomics signature containing pre- and post-contrast imaging features can adequately distinguish chemotherapeutic responders from non-responders in both primary and validation cohorts [AUCs: 0.773 (95% CI, 0.701–0.845) and 0.816 (95% CI, 0.690-0.942), respectively] and remain relatively stable across centers. The combined model has a better predictive performance with an AUC of 0.803 (95% CI, 0.734–0.872) in the primary set and an AUC of 0.821 (95% CI, 0.697–0.946) in the validation set, compared to radiomics signature alone. Both models showed good discrimination, calibration. Conclusion: Newly developed radiomic model provided an easy-to-use predictor of chemotherapeutic response with improved predictive ability, which might facilitate optimal treatment strategies tailored for individual LACC patients. [ABSTRACT FROM AUTHOR]

Introduction: A three-dimensional (3D) model of the pelvic vessels was reconstructed before surgery to aid in the understanding of the individual anatomy and help guide lymphadenectomy performance. Material and methods: Thirty patients with early-stage cervical cancer who were scheduled for lymphadenectomy at Nanfang Hospital, Southern Medical University from January 2017 to June 2017 were included. Three-dimensional models of the pelvic vessels were obtained. Results: All 3D models of the 30 patients were reconstructed successfully and were consistent with the operative findings.The most common structural types posterior to the common iliac artery (CIA) and CIA bifurcation (CIAB) were non-vessel structures (23/30 patients) and the common iliac vein (CIV) (27/30); these were observed separately on the left pelvic vein. The confluence of common iliac vein (CCIV) (29/30) and CIV (20/30) were most commonly observed posterior to the CIA and CIAB; these were observed separately on the right pelvic vein. Venous abnormalities were identified in 15 patients. There were variants in venous confluence shown to be homolateral to the CIV (2/15) and contralateral to the CIV (2/15) and CCIV (4/15). Conclusions: Three-dimensional models of the pelvic vessels can provide information on individual anatomy features that can help guide lymphadenectomy performance. [ABSTRACT FROM AUTHOR]

Abstract: Objective: To analyze the distribution of autonomic nerves and blood and lymphatic vessels in the uterosacral ligament, elucidate detailed anatomy at a surgical level and provide pathobiological evidence for improvement of nerve-sparing radical hysterectomy. Study design: : Surgical samples were collected from 15 patients who underwent radical hysterectomy for early stage cervical cancer (FIGO Ib1-IIa). Twenty-nine fresh specimens were divided into cervical, intermediate and sacral sections, and then subdivided into superficial and deep portions from the middle: the medial surface and lateral surface were also subdivided in order to analyze lymphatic vessels. The numbers of nerve branches in each section or portion of the section were analyzed. The lengths of the uterosacral ligaments were measured and immunohistochemistry staining was studied. Autonomic nerves, blood vessels and lymphatic vessels were quantitatively analyzed using image analysis software and biological stereology. Results: The volume density of sympathetic nerves in the deep portion was significantly higher than in the superficial portion (p <0.05), and the number of nerves was greatest in the cervical section (p <0.05). The volume density of blood vessels was not significantly different between the two portions (p >0.05) or among the three sections (p >0.05), and the volume density of the lymphatic vessels was greater in the medial surface (p <0.05), with most of them in the cervical section (p <0.05). Conclusions: Our study provides systematic mapping of the location and distribution of autonomic nerve branches, blood vessels and lymphatic vessels in the uterosacral ligament. [Copyright &y& Elsevier]