Acute hematologic toxicity prediction using dosimetric and radiomics features in patients with cervical cancer: does the treatment regimen matter?

BackgroundAcute hematologic toxicity (HT) is a prevalent adverse tissue reaction observed in cervical cancer patients undergoing chemoradiotherapy (CRT), which may lead to various negative effects such as compromised therapeutic efficacy and prolonged treatment duration. Accurate prediction of HT occurrence prior to CRT remains challenging.MethodsA discovery dataset comprising 478 continuous cervical cancer patients (140 HT patients) and a validation dataset consisting of 205 patients (52 HT patients) were retrospectively enrolled. Both datasets were categorized into the CRT group and radiotherapy (RT)-alone group based on the treatment regimen, i.e., whether chemotherapy was administered within the focused RT duration. Radiomics features were derived by contouring three regions of interest (ROIs)—bone marrow (BM), femoral head (FH), and clinical target volume (CTV)—on the treatment planning CT images before RT. A comprehensive model combining the radiomics features as well as the demographic, clinical, and dosimetric features was constructed to classify patients exhibiting acute HT symptoms in the CRT group, RT group, and combination group. Furthermore, the time-to-event analysis of the discriminative ROI was performed on all patients with acute HT to understand the HT temporal progression.ResultsAmong three ROIs, BM exhibited the best performance in classifying acute HT, which was verified across all patient groups in both discovery and validation datasets. Among different patient groups in the discovery dataset, acute HT was more precisely predicted in the CRT group [area under the curve (AUC) = 0.779, 95% CI: 0.657–0.874] than that in the RT-alone (AUC = 0.686, 95% CI: 0.529–0.817) or combination group (AUC = 0.748, 95% CI: 0.655–0.827). The predictive results in the validation dataset similarly coincided with those in the discovery dataset: CRT group (AUC = 0.802, 95% CI: 0.669–0.914), RT-alone group (AUC = 0.737, 95% CI: 0.612–0.862), and combination group (AUC = 0.793, 95% CI: 0.713–0.874). In addition, distinct feature sets were adopted for different patient groups. Moreover, the predicted HT risk of BM was also indicative of the HT temporal progression.ConclusionsHT prediction in cervical patients is dependent on both the treatment regimen and ROI selection, and BM is closely related to the occurrence and progression of HT, especially for CRT patients

High-dimensional Automated Radiation Therapy Treatment Planning via Bayesian Optimization

Radiation therapy treatment planning can be viewed as an iterative hyperparameter tuning process to balance conflicting clinical goals. In this work, we investigated the performance of modern Bayesian Optimization (BO) methods on automated treatment planning problems in high-dimensional settings. 20 locally advanced rectal cancer patients treated with intensity-modulated radiation therapy (IMRT) were retrospectively selected as test cases. We implemented an automated treatment planning framework that adjusts dose objectives and weights simultaneously, and tested the performance of two BO methods on the treatment planning task: one standard BO method (GPEI) and one BO method dedicated to high-dimensional problems (SAAS-BO). A random tuning method was also included as the baseline. We compared and analyzed the three automated methods' plan quality and planning efficiency and the different search patterns of the two BO methods. For the target structures, the SAAS-BO plans achieved comparable hot spot control ($p=0.43$) and homogeneity ($p=0.96$) with the clinical plans, significantly better than the GPEI and random plans ($p<0.05$). Both SAAS-BO and GPEI plans significantly outperformed the clinical plans in conformity and dose spillage ($p<0.05$). Compared with clinical plans, the treatment plans generated by the three automated methods all made reductions in evaluated dosimetric indices for the femoral head and the bladder. The analysis of the underlying predictive models has shown that both BO procedures have identified similar important planning parameters. This work implemented a BO-based hyperparameter tuning framework for automated treatment planning. Both tested BO methods were able to produce high-quality treatment plans and the model analysis also confirmed the intrinsic low dimensionality of the tested treatment planning problems

Nicotinamide mononucleotide maintains cytoskeletal stability and fortifies mitochondrial function to mitigate oocyte damage induced by Triocresyl phosphate

Triocresyl phosphate (TOCP) was commonly used as flame retardant, plasticizer, lubricant, and jet fuel additive. Studies have shown adverse effects of TOCP on the reproductive system. However, the potential harm brought by TOCP, especially to mammalian female reproductive cells, remains a mystery. In this study, we employed an in vitro model for the first time to investigate the effects of TOCP on the maturation process of mouse oocytes. TOCP exposure hampered the meiotic division process, as evidenced by a reduction in the extrusion of the first polar body from oocytes. Subsequent research revealed the disruption of the oocyte cell cytoskeleton induced by TOCP, resulting in abnormalities in spindle organization, chromosome alignment, and actin filament distribution. This disturbance further extended to the rearrangement of organelles within oocytes, particularly affecting the mitochondria. Importantly, after TOCP treatment, mitochondrial function in oocytes was impaired, leading to oxidative stress, DNA damage, cell apoptosis, and subsequent changes of epigenetic modifications. Supplementation with nicotinamide mononucleotide (NMN) alleviated the harmful effects of TOCP. NMN exerted its mitigating effects through two fundamental mechanisms. On one hand, NMN conferred stability to the cell cytoskeleton, thereby supporting nuclear maturation. On the other hand, NMN enhanced mitochondrial function within oocytes, reducing the excess reactive oxygen species (ROS), restoring meiotic division abnormalities caused by TOCP, preventing oocyte DNA damage, and suppressing epigenetic changes. These findings not only enhance our understanding of the molecular basis of TOCP induced oocyte damage but also offer a promising avenue for the potential application of NMN in optimizing reproductive treatment strategies