BlastAssist: a deep learning pipeline to measure interpretable features of human embryos.

Can the BlastAssist deep learning pipeline perform comparably to or outperform human experts and embryologists at measuring interpretable, clinically relevant features of human embryos in IVF? The BlastAssist pipeline can measure a comprehensive set of interpretable features of human embryos and either outperform or perform comparably to embryologists and human experts in measuring these features. Some studies have applied deep learning and developed 'black-box' algorithms to predict embryo viability directly from microscope images and videos but these lack interpretability and generalizability. Other studies have developed deep learning networks to measure individual features of embryos but fail to conduct careful comparisons to embryologists' performance, which are fundamental to demonstrate the network's effectiveness. We applied the BlastAssist pipeline to 67 043 973 images (32 939 embryos) recorded in the IVF lab from 2012 to 2017 in Tel Aviv Sourasky Medical Center. We first compared the pipeline measurements of individual images/embryos to manual measurements by human experts for sets of features, including: (i) fertilization status (n = 207 embryos), (ii) cell symmetry (n = 109 embryos), (iii) degree of fragmentation (n = 6664 images), and (iv) developmental timing (n = 21 036 images). We then conducted detailed comparisons between pipeline outputs and annotations made by embryologists during routine treatments for features, including: (i) fertilization status (n = 18 922 embryos), (ii) pronuclei (PN) fade time (n = 13 781 embryos), (iii) degree of fragmentation on Day 2 (n = 11 582 embryos), and (iv) time of blastulation (n = 3266 embryos). In addition, we compared the pipeline outputs to the implantation results of 723 single embryo transfer (SET) cycles, and to the live birth results of 3421 embryos transferred in 1801 cycles. In addition to EmbryoScope™ image data, manual embryo grading and annotations, and electronic health record (EHR) data on treatment outcomes were also included. We integrated the deep learning networks we developed for individual features to construct the BlastAssist pipeline. Pearson's χ2 test was used to evaluate the statistical independence of individual features and implantation success. Bayesian statistics was used to evaluate the association of the probability of an embryo resulting in live birth to BlastAssist inputs. The BlastAssist pipeline integrates five deep learning networks and measures comprehensive, interpretable, and quantitative features in clinical IVF. The pipeline performs similarly or better than manual measurements. For fertilization status, the network performs with very good parameters of specificity and sensitivity (area under the receiver operating characteristics (AUROC) 0.84-0.94). For symmetry score, the pipeline performs comparably to the human expert at both 2-cell (r = 0.71 ± 0.06) and 4-cell stages (r = 0.77 ± 0.07). For degree of fragmentation, the pipeline (acc = 69.4%) slightly under-performs compared to human experts (acc = 73.8%). For developmental timing, the pipeline (acc = 90.0%) performs similarly to human experts (acc = 91.4%). There is also strong agreement between pipeline outputs and annotations made by embryologists during routine treatments. For fertilization status, the pipeline and embryologists strongly agree (acc = 79.6%), and there is strong correlation between the two measurements (r = 0.683). For degree of fragmentation, the pipeline and embryologists mostly agree (acc = 55.4%), and there is also strong correlation between the two measurements (r = 0.648). For both PN fade time (r = 0.787) and time of blastulation (r = 0.887), there's strong correlation between the pipeline and embryologists. For SET cycles, 2-cell time (P < 0.01) and 2-cell symmetry (P < 0.03) are significantly correlated with implantation success rate, while other features showed correlations with implantation success without statistical significance. In addition, 2-cell time (P < 5 × 10-11), PN fade time (P < 5 × 10-10), degree of fragmentation on Day 3 (P < 5 × 10-4), and 2-cell symmetry (P < 5 × 10-3) showed statistically significant correlation with the probability of the transferred embryo resulting in live birth. We have not tested the BlastAssist pipeline on data from other clinics or other time-lapse microscopy (TLM) systems. The association study we conducted with live birth results do not take into account confounding variables, which will be necessary to construct an embryo selection algorithm. Randomized controlled trials (RCT) will be necessary to determine whether the pipeline can improve success rates in clinical IVF. BlastAssist provides a comprehensive and holistic means of evaluating human embryos. Instead of using a black-box algorithm, BlastAssist outputs meaningful measurements of embryos that can be interpreted and corroborated by embryologists, which is crucial in clinical decision making. Furthermore, the unprecedentedly large dataset generated by BlastAssist measurements can be used as a powerful resource for further research in human embryology and IVF. This work was supported by Harvard Quantitative Biology Initiative, the NSF-Simons Center for Mathematical and Statistical Analysis of Biology at Harvard (award number 1764269), the National Institute of Heath (award number R01HD104969), the Perelson Fund, and the Sagol fund for embryos and stem cells as part of the Sagol Network. The authors declare no competing interests. Not applicable.

Yang HY ，Leahy BD ，Jang WD ，Wei D ，Kalma Y ，Rahav R ，Carmon A ，Kopel R ，Azem F ，Venturas M ，Kelleher CP ，Cam L ，Pfister H ，Needleman DJ ，Ben-Yosef D ... -  《-》

Defining the optimum strategy for identifying adults and children with coeliac disease: systematic review and economic modelling.

Elwenspoek MM ，Thom H ，Sheppard AL ，Keeney E ，O'Donnell R ，Jackson J ，Roadevin C ，Dawson S ，Lane D ，Stubbs J ，Everitt H ，Watson JC ，Hay AD ，Gillett P ，Robins G ，Jones HE ，Mallett S ，Whiting PF ... -  《-》

Multi-omics PGT: re-evaluation of euploid blastocysts for implantation potential based on RNA sequencing.

In addition to chromosomal euploidy, can the transcriptome of blastocysts be used as a novel predictor of embryo implantation potential? This retrospective analysis showed that based on differentially expressed genes (DEGs) between euploid blastocysts which resulted and did not result in a clinical pregnancy, machine learning models could help improve implantation rates by blastocyst optimization. Embryo implantation is a multifaceted process, with implantation loss and pregnancy failure related not only to blastocyst euploidy but also to the intricate dialog between blastocyst and endometrium. Although in vitro studies have revealed the characteristics of trophectoderm (TE) differentiation in implanted blastocysts and the function of TE placentation at the implantation site, the precise molecular mechanisms of embryo implantation and their clinical application remain to be fully elucidated. This study involved 102 patients who underwent 111 cycles for preimplantation genetic testing for aneuploidies (PGT-A) between March 2022 and July 2023. The study included 412 blastocysts biopsied at Day 5 [D5] or Day 6 [D6] for patients who underwent PGT-A. The biopsy lysates were split and subjected to DNA and RNA sequencing (DNA- and RNA-seq). One part was used for PGT-A to detect DNA copy number variations, whereas the other part was assessed simultaneously by RNA-seq to determine the transcriptome characteristics. To validate the reliability and accuracy of RNA-seq obtained from this strategy, we initially analyzed the transcriptome of blastocysts with chromosomal aneuploidies. Subsequently, we compared the transcriptomic features of blastocysts with different rates of formation (D5 vs D6) and investigated the network of interactions between key blastulation genes and the receptive endometrium. Then to evaluate the implantation potential of euploid blastocysts, we identified DEGs between euploid blastocysts that resulted in clinical pregnancy (defined as the presence of a gestational sac detected by ultrasound after 5 weeks) and those that did not. These DEGs were then employed to construct a predictive model for optimizing blastocyst selection. The successful detection rate of PGT-A was remarkably high at 99.8%. The RNA data may infer aneuploidy for both trisomy and monosomy. Between the euploid blastocysts that formed on D5 and D6, 187 DEGs were predominantly involved in cell differentiation for embryonic placenta development, the PPAR signaling pathway, and the Notch signaling pathway. These D5/D6 DEGs also exhibited a functional dialog with the receptive phase endometrium-specific genes through protein-protein interaction networks, indicating that the embryo undergoes further differentiation for post-implantation development. Furthermore, a modeling strategy using 280 DEGs between blastocysts leading to successful clinical pregnancies or failing to produce clinical pregnancies was implemented to refine the euploid embryo optimization, achieving areas under the curves of 0.88, 0.71, and 0.84 for the random forest (RF), support vector machine, and linear discriminant analysis models, respectively. Finally, a retrospective analysis of 83 transferred euploid blastocysts using the RF model identified three types of euploid embryos with a decreasing trend in implantation potential. Notably, the implantation rate of the good group was significantly higher than that of the moderate group (88.6% vs 50.0% P = 0.001) and that of the moderate group was higher than that of the poor group (50.0% vs 20.8%, P = 0.035). The sample size was insufficient; thus, a prospective study is needed to verify the clinical effectiveness of the above model. Because we did not analyze blastocysts that led only to biochemical pregnancies but failed clinical pregnancies separately, our classification system still must be modified to screen these embryos. Transcriptomic analysis of blastocysts offers a novel approach for predicting embryo implantation potential, which can be utilized to optimize clinical embryo selection. The ranking system may be effective in reducing the times and costs involved in achieving a clinical pregnancy. This study was funded by the "Pioneer" and "Leading Goose" R&D Program of Zhejiang (No. 2023C03034), the National Natural Science Foundation of China (82101709), and the National Key Research and Development Program for Young Scientists of China (No. 2022YFC2702300). The authors state no competing interests. N/A.

Jin J ，Ma J ，Wang X ，Hong F ，Zhang Y ，Zhou F ，Wan C ，Zou Y ，Yang J ，Lu S ，Tong X ... -  《-》

Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.

Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided. (1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS? Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses. Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS. Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments. Level III, diagnostic study.

Lee CC ，Chen CW ，Yen HK ，Lin YP ，Lai CY ，Wang JL ，Groot OQ ，Janssen SJ ，Schwab JH ，Hsu FM ，Lin WH ... -  《-》

Antioxidants for female subfertility.

M.G. Showell, R. Mackenzie‐Proctor, V. Jordan, and R.J. Hart, “Antioxidants for Female Subfertility,” Cochrane Database of Systematic Reviews, no. 8 (2020): CD007807, https://doi.org/10.1002/14651858.CD007807.pub4 This Editorial Note is for the above article, published online on August 27, 2020, in Cochrane Library (cochranelibrary.com), and has been issued by the Publisher, John Wiley & Sons Ltd, in agreement with Cochrane. The Editorial note has been agreed due to concerns discovered by the Cochrane managing editor regarding the retraction of six studies in the Review (Badawy et al. 2006, 10.1016/j.fertnstert.2006.02.097; El Refaeey et al. 2014, 10.1016/j.rbmo.2014.03.011; El Sharkwy & Abd El Aziz 2019a, https://doi.org/10.1002/ijgo.12902; Gerli et al. 2007, https://doi.org/10.26355/eurrev_202309_33752, full text: https://europepmc.org/article/MED/18074942; Ismail et al. 2014, http://dx.doi.org/10.1016/j.ejogrb.2014.06.008; Hashemi et al. 2017, https://doi.org/10.1080/14767058.2017.1372413). In addition, expressions of concern have been published for two studies (Jamilian et al. 2018, https://doi.org/10.1007/s12011-017-1236-3; Zadeh Modarres 2018, https://doi.org/10.1007/s12011-017-1148-2). The retracted studies will be moved to the Excluded Studies table, and their impact on the review findings will be investigated and acted on accordingly in a future update. Initial checks indicate that removal of the six retracted studies did not make an appreciable difference to the results. Likewise, the studies for which Expressions of Concern were issued will be moved to the Awaiting classification table; they did not report any review outcomes, so removal will have no impact on the review findings. A couple may be considered to have fertility problems if they have been trying to conceive for over a year with no success. This may affect up to a quarter of all couples planning a child. It is estimated that for 40% to 50% of couples, subfertility may result from factors affecting women. Antioxidants are thought to reduce the oxidative stress brought on by these conditions. Currently, limited evidence suggests that antioxidants improve fertility, and trials have explored this area with varied results. This review assesses the evidence for the effectiveness of different antioxidants in female subfertility. To determine whether supplementary oral antioxidants compared with placebo, no treatment/standard treatment or another antioxidant improve fertility outcomes for subfertile women. We searched the following databases (from their inception to September 2019), with no language or date restriction: Cochrane Gynaecology and Fertility Group (CGFG) specialised register, CENTRAL, MEDLINE, Embase, PsycINFO, CINAHL and AMED. We checked reference lists of relevant studies and searched the trial registers. We included randomised controlled trials (RCTs) that compared any type, dose or combination of oral antioxidant supplement with placebo, no treatment or treatment with another antioxidant, among women attending a reproductive clinic. We excluded trials comparing antioxidants with fertility drugs alone and trials that only included fertile women attending a fertility clinic because of male partner infertility. We used standard methodological procedures expected by Cochrane. The primary review outcome was live birth; secondary outcomes included clinical pregnancy rates and adverse events. We included 63 trials involving 7760 women. Investigators compared oral antioxidants, including: combinations of antioxidants, N-acetylcysteine, melatonin, L-arginine, myo-inositol, carnitine, selenium, vitamin E, vitamin B complex, vitamin C, vitamin D+calcium, CoQ10, and omega-3-polyunsaturated fatty acids versus placebo, no treatment/standard treatment or another antioxidant. Only 27 of the 63 included trials reported funding sources. Due to the very low-quality of the evidence we are uncertain whether antioxidants improve live birth rate compared with placebo or no treatment/standard treatment (odds ratio (OR) 1.81, 95% confidence interval (CI) 1.36 to 2.43; P < 0.001, I2 = 29%; 13 RCTs, 1227 women). This suggests that among subfertile women with an expected live birth rate of 19%, the rate among women using antioxidants would be between 24% and 36%. Low-quality evidence suggests that antioxidants may improve clinical pregnancy rate compared with placebo or no treatment/standard treatment (OR 1.65, 95% CI 1.43 to 1.89; P < 0.001, I2 = 63%; 35 RCTs, 5165 women). This suggests that among subfertile women with an expected clinical pregnancy rate of 19%, the rate among women using antioxidants would be between 25% and 30%. Heterogeneity was moderately high. Overall 28 trials reported on various adverse events in the meta-analysis. The evidence suggests that the use of antioxidants makes no difference between the groups in rates of miscarriage (OR 1.13, 95% CI 0.82 to 1.55; P = 0.46, I2 = 0%; 24 RCTs, 3229 women; low-quality evidence). There was also no evidence of a difference between the groups in rates of multiple pregnancy (OR 1.00, 95% CI 0.63 to 1.56; P = 0.99, I2 = 0%; 9 RCTs, 1886 women; low-quality evidence). There was also no evidence of a difference between the groups in rates of gastrointestinal disturbances (OR 1.55, 95% CI 0.47 to 5.10; P = 0.47, I2 = 0%; 3 RCTs, 343 women; low-quality evidence). Low-quality evidence showed that there was also no difference between the groups in rates of ectopic pregnancy (OR 1.40, 95% CI 0.27 to 7.20; P = 0.69, I2 = 0%; 4 RCTs, 404 women). In the antioxidant versus antioxidant comparison, low-quality evidence shows no difference in a lower dose of melatonin being associated with an increased live-birth rate compared with higher-dose melatonin (OR 0.94, 95% CI 0.41 to 2.15; P = 0.89, I2 = 0%; 2 RCTs, 140 women). This suggests that among subfertile women with an expected live-birth rate of 24%, the rate among women using a lower dose of melatonin compared to a higher dose would be between 12% and 40%. Similarly with clinical pregnancy, there was no evidence of a difference between the groups in rates between a lower and a higher dose of melatonin (OR 0.94, 95% CI 0.41 to 2.15; P = 0.89, I2 = 0%; 2 RCTs, 140 women). Three trials reported on miscarriage in the antioxidant versus antioxidant comparison (two used doses of melatonin and one compared N-acetylcysteine versus L-carnitine). There were no miscarriages in either melatonin trial. Multiple pregnancy and gastrointestinal disturbances were not reported, and ectopic pregnancy was reported by only one trial, with no events. The study comparing N-acetylcysteine with L-carnitine did not report live birth rate. Very low-quality evidence shows no evidence of a difference in clinical pregnancy (OR 0.81, 95% CI 0.33 to 2.00; 1 RCT, 164 women; low-quality evidence). Low quality evidence shows no difference in miscarriage (OR 1.54, 95% CI 0.42 to 5.67; 1 RCT, 164 women; low-quality evidence). The study did not report multiple pregnancy, gastrointestinal disturbances or ectopic pregnancy. The overall quality of evidence was limited by serious risk of bias associated with poor reporting of methods, imprecision and inconsistency. In this review, there was low- to very low-quality evidence to show that taking an antioxidant may benefit subfertile women. Overall, there is no evidence of increased risk of miscarriage, multiple births, gastrointestinal effects or ectopic pregnancies, but evidence was of very low quality. At this time, there is limited evidence in support of supplemental oral antioxidants for subfertile women.

Showell MG ，Mackenzie-Proctor R ，Jordan V ，Hart RJ ... -  《Cochrane Database of Systematic Reviews》