Predicting intraoperative hemorrhage during curettage treatment of cesarean scar pregnancy using free-breathing GRASP DCE-MRI.

OBJECTIVE: To explore the feasibility of the golden-angle radial sparse parallel (GRASP) dynamic magnetic resonance imaging (MRI) technique in predicting the intraoperative bleeding risk of scar pregnancy. METHODS: A total of 49 patients with cesarean scar pregnancy (CSP) who underwent curettage and GRASP-MRI imaging were retrospectively selected between January 2021 and July 2022. The pharmacokinetic parameters, including Wash-in, Wash-out, time to peck (TTP), initial area under the curve (iAUC), the transfer rate constant (Ktrans), constant flow rate (Kep), and volume of extracellular space (Ve), were calculated. The amount of intraoperative bleeding was recorded by a gynecologist who performed surgery, after which patients were divided into non-hemorrhage (blood loss ≤ 200 mL) and hemorrhage (blood loss > 200 mL) groups. The measured pharmacokinetic parameters were statistically compared using the t-test or Mann-Whitney U test with a significant level set to be p < 0.05. The receiver operating characteristic (ROC) curve was constructed, and the area under the curve (AUC) was calculated to evaluate each parameter's capability in intraoperative hemorrhage subgroup classification. RESULTS: Twenty patients had intraoperative hemorrhage (blood loss > 200 mL) during curettage. The hemorrhage group had larger Wash-in, iAUC, Ktrans, Ve, and shorter TTP than the non-hemorrhage group (all P > 0.05). Wash-in had the highest AUC value (0.90), while Ktrans had the lowest value (0.67). Wash-out and Kep were not significantly different between the two groups. CONCLUSION: GRASP DCE-MRI has the potential to forecast intraoperative hemorrhage during curettage treatment of CSP, with Wash-in exhibiting the highest predictive performance. This data holds promise for advancing personalized treatment. However, further study is required to compare its effectiveness with other risk factors identified through anatomical MRI and ultrasound.

A Scoring System to Select the Candidates for Adjuvant Chemotherapy Alone in High-Risk Early-Stage Cervical Cancer Patients With Pelvic Lymph Node Metastases After Surgery.

BACKGROUND: The aim was to build a risk scoring system to guide the adjuvant treatment for early-stage cervical cancer patients with pelvic lymph node (LN) metastases after surgery. METHODS: A cohort of 1213 early-stage cervical cancer patients with pelvic LN metastases (T1-2aN1M0) were selected from the NCI SEER database, of which 1040 patients received adjuvant external beam radiotherapy concurrent with chemotherapy (EBRT+Chemo) and 173 patients received adjuvant chemotherapy alone. The Cox regression analysis was applied to identify the risk factors associated with worse survival. The exp (ß) of each independent risk factors from multivariate analysis was assigned to develop the risk scoring system. The total cohort was divided into different risk subgroups accordingly and the efficacy of different adjuvant modalities in each risk subgroups was compared. RESULTS: The patients were divided into 3 risk subgroups (Low-risk: total score <7.20, Middle-risk:7.20≤ total score≤ 8.40, High-risk: total score<8.40) based on the scoring system incorporating 5 independent risk factors. The survival analysis suggested that low-risk (hazard ratio [HR]=1.046, 95% CI: 0.586-1.867; P= 0.879) and middle-risk patients (HR=0.709, 95% CI: 0.459-1.096; P =0.122) could not benefit more from EBRT+Chemo than Chemo alone. However, EBRT+Chemo remained the superiority to Chemo alone in the high-risk subgroup (HR=0.482, 95% CI: 0.294-0.791; P =0.003). CONCLUSION: A risk scoring system has been built to direct the adjuvant treatment for early-stage cervical cancer patients with pelvic LN metastases after surgery, where Chemo alone was totally enough for low-risk and middle-risk patients stratified by the model while EBRT+Chemo was still recommended for patients in the high-risk subgroup.

A population-based risk scoring system to individualize adjuvant treatment for stage IIIC endometrial cancer patients after surgery.

BACKGROUND: To develop a risk scoring system to tailor the adjuvant treatment for stage IIIC EC patients after surgery. METHODS: Data source was from the Surveillance, Epidemiology, and End Results (SEER) registry, where 3251 post-operative stage IIIC EC patients with different adjuvant treatment were included. Cox regression analysis was used to identify risk factors. The exp (ß) of each independent risk factors generating from the cox analysis was used to construct the risk scoring system, which was further utilized to divide the patients into different risk subgroups and the efficacy of different adjuvant modalities in each risk subgroups would be compared accordingly. RESULTS: Six independent risk factors were identified to develop the scoring system, which further divided the patients into three risk subgroups based on the total risk score (Low-risk≤8.46, 8.47 ≤ Middle-risk≤9.94, High-risk≥9.95). This study revealed that CRT was not superior to RT alone (HR:1.208, 95%CI: 0.852-1.741; P = 0.289) or CT alone (HR:1.260, 95%CI: 0.750-2.116; P = 0.382) in Low-risk subgroup. We also observed that CRT had a survival advantage over other treatment modalities in the Middle-risk subgroup (All P < 0.001), but CRT and CT alone to be superimposable in the High-risk subgroup (HR: 1.395, 95%CI: 0.878-2.216; P = 0.159). CONCLUSION: A risk scoring system has been developed to tailor the adjuvant treatment for stage IIIC EC patients after surgery, where RT or CT alone could be a substitute for CRT in Low-risk patients and CT alone was a potential alternative for High-risk patients while CRT remained to be the optimal choice for the Middle-risk patients.

Prognostic model for the exemption of adjuvant chemotherapy in stage IIIC endometrial cancer patients.

Background: This study aimed to develop a nomogram to predict the survival for stage IIIC endometrial cancer (EC) patients with adjuvant radiotherapy (ART) alone and personalize recommendations for the following adjuvant chemotherapy (ACT). Methods: In total, 746 stage IIIC EC patients with ART alone were selected from the Surveillance, Epidemiology, and End Results (SEER) registry. Cox regression analysis was performed to identify independent risk factors. A nomogram was developed accordingly, and the area under the receiver operating characteristic curve (AUC) and C-index were implemented to assess the predictive power. The patients were divided into different risk strata based on the total points derived from the nomogram, and survival probability was compared between each risk stratus and another SEER-based cohort of stage IIIC EC patients receiving ART+ACT (cohort ART+ACT). Results: Five independent predictors were included in the model, which had favorable discriminative power both in the training (C-index: 0.732; 95% CI: 0.704-0.760) and validation cohorts (C-index: 0.731; 95% CI: 0.709-0.753). The patients were divided into three risk strata (low risk <135, 135 ≤ middle risk ≤205, and high risk >205), where low-risk patients had survival advantages over patients from cohort ART+ACT (HR: 0.45, 95% CI: 0.33-0.61, P < 0.001). However, the middle- and high-risk patients were inferior to patients from cohort ART+ACT in survival (P < 0.001). Conclusion: A nomogram was developed to exclusively predict the survival for stage IIIC EC patients with ART alone, based on which the low-risk patients might be perfect candidates to omit the following ACT. However, the middle- and high-risk patients would benefit from the following ACT.