BACKGROUND: Türkiye is a country in the world ranking in terms of sheep breeding. Hamdani crossbred sheep breed is one of the sheep breeds that can adapt to the difficult conditions in our country. In addition, the sentence may be corrected as \'Especially in the southeastern part of the Türkiye, crossbreeding is preferred by breeders to increase the yield characteristics of sheep\'.
OBJECTIVE: In our study, it was aimed to perform a pelvimetric analysis of Hamdani crossbred sheep fetuses in the second and third trimesters by three-dimensional modelling method.
METHODS: For this purpose, a total of 40 second-trimester (10 females, 10 males) and third-trimester (10 females, 10 males) fetuses were used. The pelvises of the fetuses were imaged with CT and 3D models were created. Sixteen pelvimetric measurements were performed from the models. The results obtained were evaluated statistically.
RESULTS: The study found statistically significant differences between male and female fetuses in terms of vertical diameter (VD) and foramen obturatum width (FOW) measurement parameters in the second trimester. In the third trimester, there were statistically significant differences between genders in acetabulum (AC) (p < 0.01), medial ischial tuberosities (MIT), and ischiatic arch (IA) (p < 0.05) parameters. As a result of the correlation analysis, it was determined that the pelvis length (PL) measurement parameter was positively correlated with different parameters in varying degrees in both periods, while the IA parameter did not show significant correlations with the other parameter in the last two periods of pregnancy.
CONCLUSIONS: In conclusion, the data obtained will be useful in pelvimetric evaluations of human and animal fetuses, anatomy education, zooarchaeology and taxonomy studies.

Few studies have examined the relationship between pelvic size and the success or failure of trial of labor after cesarean delivery (TOLAC). Here we aimed to determine whether pelvic size and morphological data obtained from radiography contribute to the first successful TOLAC. This retrospective single-center observational study enrolled pregnant women who underwent TOLAC between 2010 and 2021. The results of X-ray pelvimetry data, including obstetric conjugate (OC), transverse diameter of the pelvic inlet (TD), anteroposterior diameter of the pelvic inlet (APD), shape of the pelvic inlet, and other obstetrical clinical data, were compared between the success and failure groups. Seventy-five patients in successful group after excluding 35 patients with previous successful TOLAC, and 21 patients in failure group were eligible. The failure group had a higher rate of previous cesarean sections due to failed labor trials (p = 0.042) and heavier newborns (p = 0.014). OC, TD, and APD on X-ray pelvimetry did not differ significantly between the two groups nor did the shape of the pelvic inlet affect the success rate for TOLAC. The generalized linear model identified a history of failed trials of labor as a significant predictor of failed TOLAC (odds ratio, 0.26; 95% confidence interval 0.071-0.923; p = 0.037), whereas no pelvimetric parameters were found. Pelvic size and morphological findings have no discernible impact on the outcomes of TOLAC. The universal application of X-ray pelvimetry in all women attempting TOLAC may not have significant clinical relevance.

OBJECTIVE: The aim of this study is to investigate whether the results of pelvimetry using original radiographic Martius images and the same images with high-pass filtering applied (\"edge images\") would be consistent.
METHODS: A total of 30 primagravidas were included in this study. Three obstetricians independently measured the anteroposterior and transverse diameters of the pelvic inlet in the original and the edge images, recording the x- and y-coordinates of the four endpoints. A Wilcoxon signed rank sum test was performed on the coordinate data to evaluate differences between the original and edge images.
RESULTS: In the analysis of all coordinate data, statistically significant differences were found in both x- and y-coordinates of the sacral promontory point (SPP). In the y-coordinate of the SPP, a statistically significant difference was found in 9 of 30 pairs of images, and in all 9 the anteroposterior diameter was shorter in the edge images compared to the original images due to the more caudal placement of the SPP.
CONCLUSIONS: The coordinates of the SPP on original radiographs and their edge images were not consistent in pelvimetry using Martius images. Our results suggest that improved image contrast will allow obstetricians to better assess pelvic narrowing and cephalopelvic disproportion and even reduce radiographic dose, thereby reducing risks for pregnant women and their fetuses.

Human adolescent and adult skeletons exhibit sexual dimorphism in the pelvis. However, the degree of sexual dimorphism of the human pelvis during prenatal development remains unclear. Here, we performed high-resolution magnetic resonance imaging-assisted pelvimetry on 72 human fetuses (males [M]: females [F], 34:38; 21 sites) with crown-rump lengths (CRL) of 50-225 mm (the onset of primary ossification). We used multiple regression analysis to examine sexual dimorphism with CRL as a covariate. Females exhibit significantly smaller pelvic inlet anteroposterior diameters (least squares mean, [F] 8.4 mm vs. [M] 8.8 mm, P = 0.036), larger subpubic angle ([F] 68.1° vs. [M] 64.0°, P = 0.034), and larger distance between the ischial spines relative to the transverse diameters of the greater pelvis than males. Furthermore, the sacral measurements indicate significant sex-CRL interactions. Our study suggests that sexual dimorphism of the human fetal pelvis is already apparent at the onset of primary ossification.

BACKGROUND: Laparoscopic rectal cancer radical surgery is a complex procedure affected by various factors. However, the existing literature lacks standardized parameters for the pelvic region and soft tissues, which hampers the establishment of consistent conclusions.
OBJECTIVE: To comprehensively assess 16 pelvic and 7 soft tissue parameters through computerized tomography (CT)-based three-dimensional (3D) reconstruction, providing a strong theoretical basis to address challenges in laparoscopic rectal cancer radical surgery.
METHODS: We analyzed data from 218 patients who underwent radical laparoscopic surgery for rectal cancer, and utilized CT data for 3D pelvic reconstruction. Specific anatomical points were carefully marked and measured using advanced 3D modeling software. To analyze the pelvic and soft tissue parameters, we employed statistical methods including paired sample t-tests, Wilcoxon rank-sum tests, and correlation analysis.
RESULTS: The investigation highlighted significant sex disparities in 14 pelvic bone parameters and 3 soft tissue parameters. Males demonstrated larger measurements in pelvic depth and overall curvature, smaller measurements in pelvic width, a larger mesorectal fat area, and a larger anterior-posterior abdominal diameter. By contrast, females exhibited wider pelvises, shallower depth, smaller overall curvature, and an increased amount of subcutaneous fat tissue. However, there were no significant sex differences observed in certain parameters such as sacral curvature height, superior pubococcygeal diameter, rectal area, visceral fat area, waist circumference, and transverse abdominal diameter.
CONCLUSIONS: The reconstruction of 3D CT data enabled accurate pelvic measurements, revealing significant sex differences in both pelvic and soft tissue parameters. This study design offer potential in predicting surgical difficulties and creating personalized surgical plans for male rectal cancer patients with a potentially \"difficult pelvis\", ultimately improving surgical outcomes. Further research and utilization of these parameters could lead to enhanced surgical methods and patient care in laparoscopic rectal cancer radical surgery.

OBJECTIVE: This study explored the difficulty factors in robot-assisted low and ultra-low anterior resection, focusing on simple measurements of the pelvic anatomy.
METHODS: This was a retrospective analysis of the clinical data of 61 patients who underwent robot-assisted low and ultra-low anterior resection for rectal cancer between October 2018 and April 2023. The relationship between the operative time in the pelvic phase and clinicopathological data, especially pelvic anatomical parameters measured on X-ray and computed tomography (CT), was evaluated. The operative time in the pelvic phase was defined as the time between mobilization from the sacral promontory and rectal resection.
RESULTS: Robot-assisted low and ultra-low anterior resections were performed in 32 and 29 patients, respectively. The median operative time in the pelvic phase was 126 (range, 31-332) min. A multiple linear regression analysis showed that a short distance from the anal verge to the lower edge of the cancer, a narrow area comprising the iliopectineal line, short anteroposterior and transverse pelvic diameters, and a small angle of the pelvic mesorectum were associated with a prolonged operative time in the pelvic phase.
CONCLUSIONS: Simple pelvic anatomical measurements using abdominal radiography and CT may predict the pelvic manipulation time in robot-assisted surgery for rectal cancer.

BACKGROUND: A complete total mesorectal excision is the criterion standard in curative rectal cancer surgery. Ensuring quality is challenging in a narrow pelvis, and obesity amplifies technical difficulties. Pelvimetry is the measurement of pelvic dimensions, but its role in gauging preoperatively the difficulty of proctectomy is largely unexplored.
OBJECTIVE: To determine pelvic structural factors associated with incomplete total mesorectal excision after curative proctectomy and build a predictive model for total mesorectal excision quality.
METHODS: Retrospective cohort study.
METHODS: A quaternary referral center database of patients diagnosed with rectal adenocarcinoma (2009-2017).
METHODS: Curative-intent proctectomy for rectal adenocarcinoma.
METHODS: All radiological measurements were obtained from preoperative CT images using validated imaging processing software tools. Completeness of total mesorectal excision was obtained from histology reports.
METHODS: Ability of radiological pelvimetry and obesity measurements to predict total mesorectal excision quality.
RESULTS: Of the 410 cases meeting inclusion criteria, 362 underwent a complete total mesorectal excision (88%). Multivariable regression identified a deeper sacral curve (per 100 mm 2 [OR: 1.14; 95% CI, 1.06-1.23; p < 0.001]) and a greater transverse distance of the pelvic outlet (per 10 mm [OR:1.41, 95% CI, 1.08-1.84; p = 0.012]) to be independently associated with incomplete total mesorectal excision. An increased area of the pelvic inlet (per 10 cm 2 [OR: 0.85; 95% CI, 0.75-0.97; p = 0.02) was associated with a higher rate of complete mesorectal excision. No difference in visceral obesity ratio and visceral obesity (ratio >0.4 vs <0.4) between BMI (<30 vs ≥30) and sex was identified. A model was built to predict mesorectal quality using the following variables: depth of sacral curve, area of pelvic inlet, and transverse distance of the pelvic outlet.
CONCLUSIONS: Retrospective analysis is not controlled for the choice of surgical approach.
CONCLUSIONS: Pelvimetry predicts total mesorectal excision quality in rectal cancer surgery and can alert surgeons preoperatively to cases of unusual difficulty. This predictive model may contribute to treatment strategy and aid in the comparison of outcomes between traditional and novel techniques of total mesorectal excision. See Video Abstract .
UNASSIGNED: ANTECEDENTES:Una escisión mesorrectal total y completa es el estándar de oro en la cirugía curativa del cáncer de recto. Garantizar la calidad es un desafío en una pelvis estrecha y la obesidad amplifica las dificultades técnicas. La pelvimetría es la medición de las dimensiones pélvicas, pero su papel para medir la dificultad preoperatoria de la proctectomía está en gran medida inexplorado.OBJETIVO:Determinar los factores estructurales pélvicos asociados con la escisión mesorrectal total incompleta después de una proctectomía curativa y construir un modelo predictivo para la calidad de la escisión mesorrectal total.DISEÑO:Estudio de cohorte retrospectivo.ÁMBITO:Base de datos de un centro de referencia cuaternario de pacientes diagnosticados con adenocarcinoma de recto (2009-2017).PACIENTES:Proctectomía con intención curativa para adenocarcinoma de recto.INTERVENCIONES:Todas las mediciones radiológicas se obtuvieron a partir de imágenes de TC preoperatorias utilizando herramientas de software de procesamiento de imágenes validadas. La integridad de la escisión mesorrectal total se obtuvo a partir de informes histológicos.PRINCIPALES MEDIDAS DE VALORACIÓN:Capacidad de la pelvimetría radiológica y las mediciones de obesidad para predecir la calidad total de la escisión mesorrectal.RESULTADOS:De los 410 casos que cumplieron los criterios de inclusión, 362 tuvieron una escisión mesorrectal total completa (88%). Una regresión multivariable identificó una curva sacra más profunda (por 100 mm2); OR:1,14,[IC95%:1,06-1,23,p<0,001], y mayor distancia transversal de salida pélvica (por 10mm); OR:1,41, [IC 95%:1,08-1,84,p=0,012] como asociación independiente con escisión mesorrectal total incompleta. Un área aumentada de entrada pélvica (por 10 cm2); OR:0,85, [IC95%:0,75-0,97,p=0,02] se asoció con una mayor tasa de escisión mesorrectal completa. No se identificaron diferencias en la proporción de obesidad visceral y la obesidad visceral (proporción>0,4 vs.<0,4) entre el índice de masa corporal (<30 vs.>=30) o el sexo. Se construyó un modelo para predecir la calidad mesorrectal utilizando variables: profundidad de la curva sacra, área de la entrada pélvica y distancia transversal de la salida pélvica.LIMITACIONES:Análisis retrospectivo no controlado por la elección del abordaje quirúrgico.CONCLUSIONES:La pelvimetría predice la calidad de la escisión mesorrectal total en la cirugía del cáncer de recto y puede alertar a los cirujanos preoperatoriamente sobre casos de dificultad inusual. Este modelo predictivo puede contribuir a la estrategia de tratamiento y ayudar en la comparación de resultados entre técnicas tradicionales y novedosas de escisión mesorrectal total. (Traducción- Dr. Ingrid Melo).

OBJECTIVE: To compare 3D models based on magnetic resonance imaging (MRI) and 3D models based on computed tomography (CT) in pelvimetry.
METHODS: A retrospective analysis of 141 patients who underwent both pelvic 3D MRI and 3D CT pelvimetry for gynecological diseases from December 2009 to October 2020 was performed. The two pelvimetry methods were compared by paired Student\'s t test, Pearson\'s correlation coefficient, Bland-Altman analysis and intraclass correlation coefficient (ICC).
RESULTS: The differences between methods for each diameter were statistically significant, except for those of the posterior sagittal diameter of the pelvic inlet (t:-0.71, P = 0.5) and the anteroposterior pelvic outlet diameter (t:0.02, P = 0.98). 3D MRI and 3D CT pelvimetry strongly correlated with each other (r: min 0.7, max: 0.96, P < 0.01). The Bland-Altman results indicate that the difference points of each pelvic diameter line greater than 95 % are within the 95 % limits of agreement. The ICC was good to very good for all pelvimetric measurements using either MRI-3D (ICC: 0.64-0.98) or CT-3D (ICC: 0.72-0.98) between the two readers.
CONCLUSIONS: 3D MRI and 3D CT pelvimetry have good agreement and reproducibility, indicating that 3D MRI is reliable for pelvimetry.

UNASSIGNED: Laparoscopic total mesorectal excision (LaTME) is standard surgical methods for rectal cancer, and LaTME operation is a challenging procedure. This study is intended to use machine learning to develop and validate prediction models for surgical difficulty of LaTME in patients with rectal cancer and compare these models\' performance.
UNASSIGNED: We retrospectively collected the preoperative clinical and MRI pelvimetry parameter of rectal cancer patients who underwent laparoscopic total mesorectal resection from 2017 to 2022. The difficulty of LaTME was defined according to the scoring criteria reported by Escal. Patients were randomly divided into training group (80%) and test group (20%). We selected independent influencing features using the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression method. Adopt synthetic minority oversampling technique (SMOTE) to alleviate the class imbalance problem. Six machine learning model were developed: light gradient boosting machine (LGBM); categorical boosting (CatBoost); extreme gradient boost (XGBoost), logistic regression (LR); random forests (RF); multilayer perceptron (MLP). The area under receiver operating characteristic curve (AUROC), accuracy, sensitivity, specificity and F1 score were used to evaluate the performance of the model. The Shapley Additive Explanations (SHAP) analysis provided interpretation for the best machine learning model. Further decision curve analysis (DCA) was used to evaluate the clinical manifestations of the model.
UNASSIGNED: A total of 626 patients were included. LASSO regression analysis shows that tumor height, prognostic nutrition index (PNI), pelvic inlet, pelvic outlet, sacrococcygeal distance, mesorectal fat area and angle 5 (the angle between the apex of the sacral angle and the lower edge of the pubic bone) are the predictor variables of the machine learning model. In addition, the correlation heatmap shows that there is no significant correlation between these seven variables. When predicting the difficulty of LaTME surgery, the XGBoost model performed best among the six machine learning models (AUROC=0.855). Based on the decision curve analysis (DCA) results, the XGBoost model is also superior, and feature importance analysis shows that tumor height is the most important variable among the seven factors.
UNASSIGNED: This study developed an XGBoost model to predict the difficulty of LaTME surgery. This model can help clinicians quickly and accurately predict the difficulty of surgery and adopt individualized surgical methods.

(1) Background: The morphology of the pelvic cavity is important for decision-making in obstetrics. This study aimed to estimate the accuracy and reliability of pelvimetry measures obtained when radiologists manually label anatomical landmarks on three-dimensional (3D) pelvic models. A second objective was to design an automatic labeling method. (2) Methods: Three operators segmented 10 computed tomography scans each. Three radiologists then labeled 12 anatomical landmarks on the pelvic models, which allowed for the calculation of 15 pelvimetry measures. Additionally, an automatic labeling method was developed based on a reference pelvic model, including reference anatomical landmarks, matching the individual pelvic models. (3) Results: Heterogeneity among landmarks in radiologists\' labeling accuracy was observed, with some landmarks being rarely mislabeled by more than 4 mm and others being frequently mislabeled by 10 mm or more. The propagation to the pelvimetry measures was limited; only one out of the 15 measures reported a median error above 5 mm or 5°, and all measures showed moderate to excellent inter-radiologist reliability. The automatic method outperformed manual labeling. (4) Conclusions: This study confirmed the suitability of pelvimetry measures based on manual labeling of 3D pelvic models. Automatic labeling offers promising perspectives to decrease the demand on radiologists, standardize the labeling, and describe the pelvic cavity in more detail.