Comparison of first versus second line sacrocolpopexies in terms of morbidity and mid-term efficacy.

To compare pelvic organ prolapse (POP) recurrence and morbidity between first and second line sacrocolpopexies. We conducted a retrospective chart review of all laparoscopic or robotic sacrocolpopexies for POP-Q stage ≥ 2, with or without a history of previous prolapse repair, performed with a similar technique between January 2012 and June 2019 in 3 European Gynecologic Surgery Departments. Patients were separated into two groups: first line sacrocolpopexy (FLS) and second line sacrocolpopexy (SLS). Each patient from the SLS group was age-matched with a patient from the FLS group. The primary outcome measure was reoperation procedures for recurrent POP defined as a symptomatic POP-Q stage ≥ 2 POP in at least one vaginal compartment. Secondary outcomes included operative time, intraoperative organ trauma, intraoperative blood loss, postoperative POP recurrence (operated on or not), global reoperation and mesh-related complications. During this period, 332 patients were included. After age-matching, 170 patients were analyzed: 85 patients in the FLS and SLS groups, respectively. After a mean follow-up of 3 years, there was no statistically significant difference between the two groups in terms of recurrent POP (9.4% versus 10.6%, p = 0.7), recurrent POP reoperation (3.5% versus 5.9% p = 0.7), mesh-related reoperation (0% versus 2.4%, p = 0.5), global reoperation (3.5 versus 8.2%, p = 0.3), operative time (198 ± 67 min versus 193 ± 60 min, p = 0.5), intraoperative complications such as organ injury (4.7% versus 7.1%, p = 0.7) and blood loss > 500 mL (2.4% versus 0%, p = 0.5). Patients who underwent a first or a second line sacrocolpopexy seemed to have similar rates of prolapse recurrence and complications.

Automatic identification and segmentation of slice of minimal hiatal dimensions in transperineal ultrasound volumes.

OBJECTIVE: To develop and validate a tool for automatic selection of the slice of minimal hiatal dimensions (SMHD) and segmentation of the urogenital hiatus (UH) in transperineal ultrasound (TPUS) volumes. METHODS: Manual selection of the SMHD and segmentation of the UH was performed in TPUS volumes of 116 women with symptomatic pelvic organ prolapse (POP). These data were used to train two deep-learning algorithms. The first algorithm was trained to provide an estimation of the position of the SMHD. Based on this estimation, a slice was selected and fed into the second algorithm, which performed automatic segmentation of the UH. From this segmentation, measurements of the UH area (UHA), anteroposterior diameter (APD) and coronal diameter (CD) were computed automatically. The mean absolute distance between manually and automatically selected SMHD, the overlap (dice similarity index (DSI)) between manual and automatic UH segmentation and the intraclass correlation coefficient (ICC) between manual and automatic UH measurements were assessed on a test set of 30 TPUS volumes. RESULTS: The mean absolute distance between manually and automatically selected SMHD was 0.20 cm. All DSI values between manual and automatic UH segmentations were above 0.85. The ICC values between manual and automatic UH measurements were 0.94 (95% CI, 0.87-0.97) for UHA, 0.92 (95% CI, 0.78-0.97) for APD and 0.82 (95% CI, 0.66-0.91) for CD, demonstrating excellent agreement. CONCLUSIONS: Our deep-learning algorithms allowed reliable automatic selection of the SMHD and UH segmentation in TPUS volumes of women with symptomatic POP. These algorithms can be implemented in the software of TPUS machines, thus reducing clinical analysis time and simplifying the examination of TPUS data for research and clinical purposes. © 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Deep learning enables automatic quantitative assessment of puborectalis muscle and urogenital hiatus in plane of minimal hiatal dimensions.

OBJECTIVES: To measure the length, width and area of the urogenital hiatus (UH), and the length and mean echogenicity (MEP) of the puborectalis muscle (PRM), automatically and observer-independently, in the plane of minimal hiatal dimensions on transperineal ultrasound (TPUS) images, by automatic segmentation of the UH and the PRM using deep learning. METHODS: In 1318 three- and four-dimensional (3D/4D) TPUS volume datasets from 253 nulliparae at 12 and 36 weeks' gestation, two-dimensional (2D) images in the plane of minimal hiatal dimensions with the PRM at rest, on maximum contraction and on maximum Valsalva maneuver, were obtained manually and the UH and PRM were segmented manually. In total, 713 of the images were used to train a convolutional neural network (CNN) to segment automatically the UH and PRM in the plane of minimal hiatal dimensions. In the remainder of the dataset (test set 1 (TS1); 601 images, four having been excluded), the performance of the CNN was evaluated by comparing automatic and manual segmentations. The performance of the CNN was also tested on 117 images from an independent dataset (test set 2 (TS2); two images having been excluded) from 40 nulliparae at 12 weeks' gestation, which were acquired and segmented manually by a different observer. The success of automatic segmentation was assessed visually. Based on the CNN segmentations, the following clinically relevant parameters were measured: the length, width and area of the UH, the length of the PRM and MEP. The overlap (Dice similarity index (DSI)) and surface distance (mean absolute distance (MAD) and Hausdorff distance (HDD)) between manual and CNN segmentations were measured to investigate their similarity. For the measured clinically relevant parameters, the intraclass correlation coefficients (ICCs) between manual and CNN results were determined. RESULTS: Fully automatic CNN segmentation was successful in 99.0% and 93.2% of images in TS1 and TS2, respectively. DSI, MAD and HDD showed good overlap and distance between manual and CNN segmentations in both test sets. This was reflected in the respective ICC values in TS1 and TS2 for the length (0.96 and 0.95), width (0.77 and 0.87) and area (0.96 and 0.91) of the UH, the length of the PRM (0.87 and 0.73) and MEP (0.95 and 0.97), which showed good to very good agreement. CONCLUSION: Deep learning can be used to segment automatically and reliably the PRM and UH on 2D ultrasound images of the nulliparous pelvic floor in the plane of minimal hiatal dimensions. These segmentations can be used to measure reliably UH dimensions as well as PRM length and MEP. © 2018 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

Automatic segmentation of puborectalis muscle on three-dimensional transperineal ultrasound.

OBJECTIVES: The introduction of three-dimensional (3D) analysis of the puborectalis muscle (PRM) for diagnostic purposes into daily practice is hindered by the need for appropriate training of observers. Automatic segmentation of the PRM on 3D transperineal ultrasound may aid its integration into clinical practice. The aims of this study were to present and assess a protocol for manual 3D segmentation of the PRM on 3D transperineal ultrasound, and to use this for training of automatic 3D segmentation method of the PRM. METHODS: The data used in this study were derived from 3D transperineal ultrasound sequences of the pelvic floor acquired at 12 weeks' gestation from nulliparous women with a singleton pregnancy. A manual 3D segmentation protocol was developed for the PRM based on a validated two-dimensional segmentation protocol. For automatic segmentation, active appearance models of the PRM were developed, trained using manual segmentation data from 50 women. The performances of both manual and automatic segmentation were analyzed by measuring the overlap and distance between the segmentations. Intraclass correlation coefficients (ICCs) and their 95% CIs were determined for mean echogenicity and volume of the puborectalis muscle, in order to assess inter- and intraobserver reliabilities of the manual method using data from 20 women, as well as to compare the manual and automatic methods. RESULTS: Interobserver reliabilities for mean echogenicity and volume were very good for manual segmentation (ICCs 0.987 and 0.910, respectively), as were intraobserver reliabilities (ICCs 0.991 and 0.877, respectively). ICCs for mean echogenicity and volume were very good and good, respectively, for the comparison of manual vs automatic segmentation (0.968 and 0.626, respectively). The overlap and distance results for manual segmentation were as expected, showing an average mismatch of only 2-3 pixels and reasonable overlap. Based on overlap and distance, five mismatches were detected for automatic segmentation, resulting in an automatic segmentation success rate of 90%. CONCLUSIONS: This study presents a reliable manual segmentation protocol and automatic 3D segmentation method for the PRM, which will facilitate future investigation of the PRM, allowing for the reliable measurement of potentially clinically valuable parameters such as mean echogenicity. © 2017 The Authors. Ultrasound in Obstetrics & Gynecology Published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

Changes in global strain of puborectalis muscle during pregnancy and postpartum.

OBJECTIVE: One of the functional parameters that can be assessed by ultrasound is muscle strain, which represents the extent of deformation of the muscle from its original shape when forces are applied to the tissue under study. The aim of this study was to evaluate the effect of pregnancy and delivery on the puborectalis muscle, by assessing changes in global strain of the muscle during and after pregnancy. METHODS: This was a secondary analysis of a prospective observational study on the association between stress urinary incontinence and levator ani muscle avulsion after delivery. Two-hundred and eighty nulliparous pregnant women underwent four-dimensional transperineal ultrasound assessments at 12 and 36 weeks of gestation, and 6 months postpartum. Tomographic ultrasound images were constructed and the puborectalis muscle was delineated by hand using programming software. After delineation, the length of the midline of the puborectalis muscle was measured at rest and during maximum pelvic floor muscle contraction, and global strain was expressed as percentile difference. Postpartum results were analyzed separately for vaginal, operative (vacuum) vaginal and Cesarean delivery. Differences in global strain of the puborectalis muscle according to mode of delivery were compared using a paired-sample t-test. The effect of partial or complete avulsion of the puborectalis muscle on postpartum strain was evaluated by ANOVA. RESULTS: In total, 254 datasets were analyzed. Global strain of the puborectalis muscle did not change during pregnancy, but after spontaneous or operative vaginal delivery the global strain diminished significantly. No significant change was observed in strain of the puborectalis muscle after Cesarean delivery. Women who suffered complete bilateral avulsion had significantly lower strain compared with women with an intact puborectalis muscle. CONCLUSION: Spontaneous or operative vacuum vaginal birth and complete bilateral avulsion of the puborectalis muscle influence negatively the strain of the puborectalis muscle. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

Quality of reporting of diagnostic accuracy studies on pelvic floor three-dimensional transperineal ultrasound: a systematic review.

OBJECTIVE: In recent years, a large number of studies have been published on the clinical relevance of pelvic floor three-dimensional (3D) transperineal ultrasound. Several studies compare sonography with other imaging modalities or clinical examination. The quality of reporting in these studies is not known. The objective of this systematic review was to determine the compliance of diagnostic accuracy studies investigating pelvic floor 3D ultrasound with the Standards for Reporting of Diagnostic Accuracy (STARD) guidelines. METHODS: Published articles on pelvic floor 3D ultrasound were identified by a systematic literature search of MEDLINE, Web of Science and Scopus databases. Prospective and retrospective studies that compared pelvic floor 3D ultrasound with other clinical and imaging diagnostics were included in the analysis. STARD compliance was assessed and quantified by two independent investigators, using 22 of the original 25 STARD checklist items. Items with the qualifier 'if done' (Items 13, 23 and 24) were excluded because they were not applicable to all papers. Each item was scored as reported (score = 1) or not reported (score = 0). Observer variability, the total number of reported STARD items per article and summary scores for each item were calculated. The difference in total score between STARD-adopting and non-adopting journals was tested statistically, as was the effect of year of publication. RESULTS: Forty studies published in 13 scientific journals were included in the analysis. Mean ± SD STARD checklist score of the included articles was 16.0 ± 2.5 out of a maximum of 22 points. The lowest scores (< 50%) were found for reporting of handling of indeterminate results or missing responses, adverse events and the time interval between tests. Interobserver agreement for rating the STARD items was excellent (intraclass correlation coefficient, 0.77). An independent t-test showed no significant mean difference ± SD in total STARD checklist score between STARD-adopting and non-adopting journals (16.4 ± 2.2 vs 15.9 ± 2.6, respectively). Mean ± SD STARD checklist score for articles published in 2003-2009 was lower, but not statistically different, compared with those published in 2010-2015 (15.2 ± 2.5 vs 16.6 ± 2.4, respectively). CONCLUSION: The overall compliance with reporting guidelines of diagnostic accuracy studies on pelvic floor 3D transperineal ultrasound is relatively good compared with other fields of medicine. However, specific checklist items require more attention when reported. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.

Measuring echogenicity and area of the puborectalis muscle: method and reliability.

OBJECTIVES: To develop a semi-automated method to assess puborectalis muscle echogenicity on three-dimensional/four-dimensional (3D/4D) volume transperineal ultrasound images using 4D View and Matlab® software and evaluate its intra- and interobserver reliability. METHOD: The data of 23 women in their first trimester were included. 3D/4D volume datasets were obtained at rest. Two inexperienced observers were trained by an experienced observer to construct tomographic ultrasound images (TUI) from the original data and to delineate all structures. Puborectalis muscle area (PMA) and the mean echogenicity of the puborectalis muscle (MEP) were calculated offline. Intra- and interobserver reliability were determined by intraclass correlation coefficients (ICC) and their 95% CIs. RESULTS: The development of a semi-automated method to calculate puborectalis area and echogenicity is described in detail. PMA and MEP measurements in pregnant women demonstrated almost perfect intraobserver reliability for both inexperienced observers, with ICC values ranging from 0.88 to 0.99. The interobserver reliability showed ICCs of 0.63 for PMA and almost perfect ICC values, of 0.96-0.98, for echogenicity. The majority of intraobserver mismatch between two delineations of PMA occurred near the borders. CONCLUSIONS: Matlab software can be used to provide reliable measurements of the area and echogenicity of the puborectalis muscle. As the latter can be used to assess structural changes in the puborectalis muscle, it appears a promising new tool for studying pelvic floor structural anatomy.