Reliability of the visual diagnosis of ovarian endometriosis

Vercellini, Paolo; Vendola, Nicoletta; Bocciolone, Luca; Rognoni, Maria Teresa; Carinelli, Silvestro; Candiani, G

doi:10.1016/s0015-0282(16)54744-x

Cited by 60 publications

(27 citation statements)

References 5 publications

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“…Although the attempt to classify endometriosis began as early as in the 1920s, so far the most widely adopted classifi cation system for endometriosis, the rAFS, has not met these criteria well in terms of predicting treatment responses for either infertility or chronic pelvic pain. While rAFS represents improvement over older classifi cation systems, it still has problems resulting from arbitrariness of the scoring system [30] , potential for observational errors [31,32] , limited reproducibility due to considerable intraobserver errors and notable interobserver errors [30,33] , failure to consider lesion morphologic type [34][35][36] , and inadequacy in correlating with severity and degree of pelvic pain [37] . It has been proposed by several authors that there are three types of endometriotic lesions (peritoneal, ovarian, and rectovaginal) and that each of them should be considered a separate entity, since each is thought to have a diff erent pathogenesis [38] .…”

Section: Discussionmentioning

confidence: 99%

Genomic Alterations in Ectopic and Eutopic Endometria of Women with Endometriosis

Strawn²,

Basir

et al. 2006

Gynecol Obstet Invest

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Background/Aims: Ectopic and eutopic endometria of women with endometriosis have been shown to contain genomic alterations. In this study, we sought to identify genomic alterations in both ectopic and eutopic endometria of 5 women with endometriosis and to examine whether the two tissues share any genomic alterations. We also attempted to classify tissue samples based on the alteration profiles. Methods: Laser capture microdissection was used to harvest epithelial cells. High-resolution comparative genomic hybridization microarrays were used to identify genomic alterations in eutopic and ectopic endometria from 5 women with endometriosis. The results were validated by real-time RT-PCR and loss of heterozygosity analysis. Results: All 5 patients had genomic alterations in their eutopic and ectopic endometria. The ectopic and eutopic endometria shared a sizable portion of genomic alterations. Cluster analysis of the genomic alteration profile correctly and consistently classified tissue samples from the 5 patients into two groups: peritoneal implants and ovarian cysts. Conclusions: The correct classification of tissue samples into two groups suggests that these two subtypes of endometriosis may have distinct genomic alteration profiles and are thus distinct entities, as previously proposed. The shared alterations are likely the ones that harbor genes responsible for an increased propensity of endometrial debris to implant to the ectopic sites and for early events that lead to the establishment of lesions. Alternatively, these shared alterations may harbor genes that are dysregulated in both eutopic and ectopic endometria. The identified genomic alterations should help to zero in genes involved in the pathogenesis of endometriosis in future studies.

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Section: Discussionmentioning

confidence: 99%

Genomic Alterations in Ectopic and Eutopic Endometria of Women with Endometriosis

Strawn²,

Basir

et al. 2006

Gynecol Obstet Invest

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“…Keywords Endometriosis Á Pelvic exenteration Á Colorectal resection Á Hysterectomy Á Laparoscopy Á Quality of life Á SF-36 health status Á IPSS Á BFLUTS Endometriosis is defined as presence of ectopic endometrial tissue outside the uterus [1][2][3][4][5]. Deep infiltrating endometriosis (DIE) is estimated to affect up to 20% of all women with endometriosis, although the exact incidence remains unknown.…”

Section: Introductionmentioning

confidence: 99%

Laparoscopic versus laparotomic radical en bloc hysterectomy and colorectal resection for endometriosis

et al. 2010

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“…This was extensively evaluated, modified in 1985, and is still used today (6)(7)(8)(9). Despite these revisions the currently used revised AFS system has serious limitations, including not effectively predicting the outcome of treatment (10)(11)(12)(13)(14)(15)(16)(17). Because an endometriosis classification system that effectively predicts outcomes has eluded scientists for decades, we chose a different approach: collect clinical data prospectively, assess infertility outcomes, and use comprehensive statistical analysis to derive a new staging system from the data rather than from a priori assumptions.…”

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confidence: 99%