Magnetic resonance imaging for deep infiltrating endometriosis: current concepts, imaging technique and key findings

Lorusso, Filomenamila; Scioscia, Marco; Rubini, D.; Ianora, Amato Antonio Stabile; Scardigno, D.; Leuci, Carla; Ceglie, Michele De; Sardaro, Angela; Lucarelli, Nicola Maria; Scardapane, Arnaldo

doi:10.1186/s13244-021-01054-x

Cited by 29 publications

(65 citation statements)

References 57 publications

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“…All the saliva samples were collected between January and June 2021. All the patients underwent either a laparoscopic procedure (therapeutic or diagnostic laparoscopy) and/or MRI imaging [5][6][7][8]. The laparoscopic procedures were systematically videoed and then analyzed by two operators (C.T., Y.D.…”

Section: Study Populationmentioning

confidence: 99%

“…The first is timely diagnosis mainly because the symptoms of endometriosis are non-specific, and clinical examination is often either negative or results in a wrong diagnosis [3,4]. The second challenge is that complementary explorations, especially biomarkers [5,6] and imaging examinations [5][6][7][8], are often inconclusive and fail to diagnose early-stage endometriosis with sufficient accuracy or are of limited relevance for the severe forms. Consequently, therapeutic and follow-up strategies are compromised, and there is a high rate of conventional treatment failure [2,4].…”

Section: Introductionmentioning

confidence: 99%

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Salivary MicroRNA Signature for Diagnosis of Endometriosis

Bendifallah

Suisse²,

Puchar

et al. 2022

JCM

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Background: Endometriosis diagnosis constitutes a considerable economic burden for the healthcare system with diagnostic tools often inconclusive with insufficient accuracy. We sought to analyze the human miRNAome to define a saliva-based diagnostic miRNA signature for endometriosis. Methods: We performed a prospective ENDO-miRNA study involving 200 saliva samples obtained from 200 women with chronic pelvic pain suggestive of endometriosis collected between January and June 2021. The study consisted of two parts: (i) identification of a biomarker based on genome-wide miRNA expression profiling by small RNA sequencing using next-generation sequencing (NGS) and (ii) development of a saliva-based miRNA diagnostic signature according to expression and accuracy profiling using a Random Forest algorithm. Results: Among the 200 patients, 76.5% (n = 153) were diagnosed with endometriosis and 23.5% (n = 47) without (controls). Small RNA-seq of 200 saliva samples yielded ~4642 M raw sequencing reads (from ~13.7 M to ~39.3 M reads/sample). Quantification of the filtered reads and identification of known miRNAs yielded ~190 M sequences that were mapped to 2561 known miRNAs. Of the 2561 known miRNAs, the feature selection with Random Forest algorithm generated after internally cross validation a saliva signature of endometriosis composed of 109 miRNAs. The respective sensitivity, specificity, and AUC for the diagnostic miRNA signature were 96.7%, 100%, and 98.3%. Conclusions: The ENDO-miRNA study is the first prospective study to report a saliva-based diagnostic miRNA signature for endometriosis. This could contribute to improving early diagnosis by means of a non-invasive tool easily available in any healthcare system.

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Section: Study Populationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Salivary MicroRNA Signature for Diagnosis of Endometriosis

Bendifallah

Suisse²,

Puchar

et al. 2022

JCM

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“…Adenomyosis could be missed as well. These disease types cannot necessarily be seen well from an intraperitoneal viewpoint ( Lorusso et al 2021 ). While laparoscopy with histologic confirmation of lesions remains the gold standard for diagnosis of endometriosis, it proves neither to be fully diagnostic nor therapeutic.…”

Section: Cons Of Diagnostic Laparoscopymentioning

confidence: 99%

“…Endometriosis affects 10% of women of reproductive age and nearly 90% of women with chronic pelvic pain and infertility ( Lorusso et al 2021 ). It is defined as the presence of endometrial-like tissue outside the uterus.…”

Section: Introductionmentioning

confidence: 99%

The future of diagnostic laparoscopy – Cons

Simko

Wright

2022

Reproduction and Fertility

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Endometriosis has a large impact on the lives of patients, affecting nearly 90% of women with chronic pelvic pain and infertility. Unfortunately, diagnosis for this condition is often delayed by an average of 7 years, with adolescent patients experiencing disproportionate delays, which can lead to disease progression. This is in part due to the use of an invasive procedure for primary diagnosis and limited access to subspecialty care. While laparoscopy serves an important purpose in the diagnosis and management of endometriosis, it has been found to be less cost effective than empiric medical therapy and puts an emphasis on the lesion as opposed to the patient and the disease process as a whole. As studies emerge, we gain a deeper understanding of the complex nature of this disease. Laparoscopy has been shown to have variable results, with high recurrence rates and varying improvement in symptoms over time. Additionally, studies have shown poor correlation between patient’s pain and the stage and location of lesions, with laparoscopy showing greater benefit for later stage disease and deep infiltrating endometriosis. This article seeks to evaluate the current standards for the management of endometriosis, discuss the place for diagnostic laparoscopy, and review future directions and alternatives.

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“…Early diagnosis of endometriosis is difficult as patients can present with a variety of non-specific symptoms including dysmenorrhea, dyspareunia, chronic pelvic pain, and infertility 1 , 2 , 4 : Despite the use of specific endometriosis screening questionnaires, the time from onset to diagnosis can take more than 7 years 5 – 8 . Moreover, a Cochrane review by Nisenblat et al highlighted that, although imaging explorations such as transvaginal ultrasonography and magnetic resonance imaging (MRI) 9 – 11 have a high accuracy in diagnosing endometrioma and some deep endometriosis locations, they exhibit poor accuracy for detecting peritoneal endometriosis which represents the early stages of the disease. Similarly, numerous studies have evaluated the diagnostic value of blood biomarkers but with disappointing results 4 , 12 – 17 .…”

Section: Introductionmentioning

confidence: 99%

MicroRNome analysis generates a blood-based signature for endometriosis

Bendifallah

Dabi

Suisse

et al. 2022

Sci Rep

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Endometriosis, characterized by endometrial-like tissue outside the uterus, is thought to affect 2–10% of women of reproductive age: representing about 190 million women worldwide. Numerous studies have evaluated the diagnostic value of blood biomarkers but with disappointing results. Thus, the gold standard for diagnosing endometriosis remains laparoscopy. We performed a prospective trial, the ENDO-miRNA study, using both Artificial Intelligence (AI) and Machine Learning (ML), to analyze the current human miRNome to differentiate between patients with and without endometriosis, and to develop a blood-based microRNA (miRNA) diagnostic signature for endometriosis. Here, we present the first blood-based diagnostic signature obtained from a combination of two robust and disruptive technologies merging the intrinsic quality of miRNAs to condense the endometriosis phenotype (and its heterogeneity) with the modeling power of AI. The most accurate signature provides a sensitivity, specificity, and Area Under the Curve (AUC) of 96.8%, 100%, and 98.4%, respectively, and is sufficiently robust and reproducible to replace the gold standard of diagnostic surgery. Such a diagnostic approach for this debilitating disorder could impact recommendations from national and international learned societies.

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Magnetic resonance imaging for deep infiltrating endometriosis: current concepts, imaging technique and key findings

Cited by 29 publications

References 57 publications

Salivary MicroRNA Signature for Diagnosis of Endometriosis

Salivary MicroRNA Signature for Diagnosis of Endometriosis

The future of diagnostic laparoscopy – Cons

MicroRNome analysis generates a blood-based signature for endometriosis

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