We aimed to investigate whether pre-therapeutic radiomic features based on magnetic resonance imaging (MRI) can predict the clinical response to neoadjuvant chemotherapy (NACT) in patients with locally advanced cervical cancer (LACC). A total of 275 patients with LACC receiving NACT were enrolled in this study from eight hospitals, and allocated to training and testing sets (2:1 ratio). Three radiomic feature sets were extracted from the intratumoural region of T1-weighted images, intratumoural region of T2-weighted images, and peritumoural region of T2-weighted images before NACT for each patient. With a feature selection strategy, three single sequence radiomic models were constructed, and three additional combined models were constructed by combining the features of different regions or sequences. The performance of all models was assessed using receiver operating characteristic curve. The combined model of the intratumoural zone of T1-weighted images, intratumoural zone of T2-weighted images,and peritumoural zone of T2-weighted images achieved an AUC of 0.998 in training set and 0.999 in testing set, which was significantly better (p < .05) than the other radiomic models. Moreover, no significant variation in performance was found if different training sets were used. This study demonstrated that MRI-based radiomic features hold potential in the pretreatment prediction of response to NACT in LACC, which could be used to identify rightful patients for receiving NACT avoiding unnecessary treatment.

Objective: To investigate whether pretreatment 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: 277 LACC patients treated with NACT followed by surgery/radiotherapy were included in this multi-institution retrospective study. 1294 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]. 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 to 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

Purpose: Radical hysterectomy combined with pelvic lymphadenectomy is the standard treatment for early-stage cervical cancer, but unrecognized pelvic nerves are vulnerable to irreversible damage during surgery. This early clinical trial investigated the feasibility and safety of intraoperative near-infrared (NIR) fluorescence imaging (NIR-FI) with indocyanine green (ICG) for identifying pelvic nerves during radical hysterectomy for cervical cancer. Methods: Sixty-six adults with cervical cancer were enrolled in this prospective, open-label, single-arm, single-center clinical trial. NIR-FI was performed in vivo to identify genitofemoral (GN), obturator (ON), and hypogastric (HN) nerves intraoperatively. The primary endpoint was the presence of fluorescence in pelvic nerves. Secondary endpoints were the ICG distribution in a nerve specimen and potential underlying causes of fluorescence emission in pelvic nerves. Results: In total, 63 patients were analyzed. The ON was visualized bilaterally in 100% (63/63) of patients, with a mean fluorescence signal-to-background ratio (SBR) of 5.3±2.1. The GN was identified bilaterally in 93.7% (59/63) of patients and unilaterally in the remaining 4 patients, with a mean SBR of 4.1±1.9. The HN was identified bilaterally in 81.0% (51/63) of patients and unilaterally in 7.9% (5/63) of patients, with a mean SBR of 3.5±1.3. ICG fluorescence was detected in frozen sections of a nerve specimen, and was mainly distributed in axons. No ICG-related complications were observed. Conclusion: This early clinical trial demonstrated the feasibility and safety of NIR-FI to visualize pelvic nerves intraoperatively. Thus, NIR-FI may help surgeons adjust surgical decision-making, avoid nerve damage, and improve surgical outcomes. Trial registration: ClinicalTrials.gov NCT04224467

Microsatellite markers from a transcriptome sequence library were initially isolated, and their genetic variation was characterized in a wild population of the mud crab (Scylla paramamosain). We then tested the association between these microsatellite markers and the growth performance of S. paramamosain. A total of 129 polymorphic microsatellite markers were identified, with an observed heterozygosity ranging from 0.19 to 1.00 per locus, an expected heterozygosity ranging from 0.23 to 0.96 per locus, and a polymorphism information content (PIC) ranging from 0.21 to 0.95 per locus. Of these microsatellite markers, 30 showed polymorphism in 96 full-sib individuals of a first generation family. Statistical analysis indicated that three microsatellite markers were significantly associated with 12 growth traits of S. paramamosain. Of these three markers, locus Scpa36 was significantly associated with eight growth traits, namely, carapace length, abdomen width (AW), body height (BH), fixed finger length of the claw, fixed finger width of the claw, fixed finger height of the claw, meropodite length of pereiopod 2, and meropodite length of pereiopod 3 (MLP3) (P<0.05). Locus Scpa75 was significantly associated with five growth traits, namely, internal carapace width, AW, carapace width at spine 8, distance between lateral spine 2 (DLS2), and MLP3 (P<0.05). Locus Spm30 was significantly associated with BH, DLS2, and body weight (P<0.05). Further analysis suggested a set of genotypes (BC at Scpa36, BC and BD at Scpa75, and AC at Spm30) that have great potential in the selection of S. paramamosain for growth traits. These findings will facilitate the development of population conservation genetics and molecular marker-assisted selective breeding of S. paramamosain and other closely related species.

Li P, et al. J Gynecol Oncol. 2020 Oct;32:e17. https://doi.org/10.3802/jgo.2021.32.e17