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Università di Pisa

Facoltà di Medicina e Chirurgia

Scuola di Specializzazione in Radiodiagnostica

Direttore: Prof. Carlo Bartolozzi

Tesi di Specializzazione

Anatomical localization of deep infiltrating endometriosis:

3D MRI reconstructions

Relatore:

Chiar.mo Prof. Carlo Bartolozzi

Candidata:

Dr.ssa Federica Forasassi

Anno Accademico 2009/2010

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Index

1. Abstract p. 3

2. Introduction p. 5

3. Materials and methods: p. 7

3.1 Patient characteristics p. 7

3.2 MRI image acquisition protocol p. 7

3.3 3D MRI reconstructions: the semi-automatic

segmentation technique (ITK-SNAP software) p. 8

3.4 Surgery Examination p. 13

3.5 Image Analysis p. 16

3.6 Methods of Analysis p. 16

3.7 Statistical Analysis p. 18

4. Results p. 18

5. Conclusions p. 23

6. Bibliography p. 26

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1. Abstract

Purpose

The goal of this study was to determine the accuracy of 3D MRI reconstructions obtained with

segmentation technique in the preoperative assessment of deep infiltrating endometriosis (DIE)

and in particular to evaluate rectosigmoid and bladder wall involvement.

Materials and methods

Institutional review board approval for this study was obtained, and each patient gave written

informed consent.

Fifty-seven consecutive patients with diagnosis of DIE who had undergone pelvic MRI at 1.5 T

before surgery between 2007 and 2011, were retrospectively evaluated and 3D post-processed

in order to obtain a detailed mapping of DIE. A blinded reader interpreted images.

MRI results were compared with surgical findings and were scored by using a four-point scale

(0_3 score).

Results

36/57 patients with symptomatic DIE underwent surgery: 18/36 had endometriotic nodules

infiltrating the recto-uterine pouch, 12/36 the vescico-uterine pouch and 6/36 the rectovaginal

pouch.

The sensitivity of MRI and 3D-MRI versus surgery was respectively 64% versus 83%;

diagnostic accuracy of 3D-MRI respect to MRI alone was 86% versus 67% for localization;

86% versus 67% for dimension; 79% versus 58% for rectosigmoid infiltration; 92% versus 75%

for bladder infiltration.

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Conclusions

In this preliminary study 3D MRI reconstructions obtained with semi-automatic method of

segmentation provided encouraging results for staging DIE preoperatively.

In fact, the addition of 3D MRI reconstructions improved diagnostic accuracy and staging of

DIE providing the exact volume of the lesions and enabling a precise mapping of these before

surgery.

Key words: Endometriosis; MRI; 3D reconstructions; semi-automatic segmentation; wall

infiltration; laparoscopyc or robotic surgery.

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2. Introduction

Endometriosis is defined as the presence of endometrial tissue outside the uterus; in particular,

deep pelvic endometriosis, also called deep infiltrating endometriosis (DIE), is defined as

infiltration of the implant of endometriosis under the surface of the peritoneum (5 mm in depth)

[1-4].

Although peritoneal endometriosis can be asymptomatic, DIE is a cause of pelvic pain,

dysmenorrhea, dyspareunia, dyschezia, and urinary symptoms and is frequently associated with

infertility.

Since, recto-sigmoid involvement represents a severe form and occurs with a frequency of

6%–30% of cases of DIE, this disease can have a negative impact on everyday life and sexual

life [5-7].

The treatment of symptomatic DIE consists of complete excision of the lesions by means of

laparoscopy or robotic surgery.

Transvaginal sonography (TVUS) is recommended as first step for the diagnosis of

endometriomas and endometriosis of the bladder , but its value for the assessment of superficial

peritoneal lesions, ovarian foci, and DIE is poor. Moreover, sonography may not differentiate

some endometriomas from hemorrhagic cysts or other ovarian neoplasms and is insensitive in

the detection of peritoneal implants.

Because of these limitations, laparoscopy or robotic surgery have remained the standards of

reference for diagnosis and staging of pelvic endometriosis.

However, as laparoscopy and robotic surgery do not visualize well “atypical” non-pigmented

extraperitoneal sites of involvement and regions involved by pelvic adhesions, MR imaging

(MRI) has resulted the alternative and noninvasive technique for evaluation of endometriosis

showing sensitivity and specificity of greater than 90% in the detection of endometriomas and

peritoneal implants [8-15].

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Therefore, the diagnosis and staging of endometriosis should guide the surgeon to schedule the

most appropriate one-step surgery: conservative laparoscopic/robotic surgery treatment or open

surgery with colonic resection if there is infiltrative parietal colon involvement [15-19].

The addition of 3D MRI reconstructions, obtained with semi-automatic segmentation-technique,

improved diagnostic accuracy and staging of DIE providing the exact volume of the lesions,

enabling a precise mapping of these before surgery and then planning the type of surgery

treatment to be performed.

The goal of this study was to determine the accuracy of 3D MRI reconstructions obtained with

segmentation technique in the preoperative assessment of deep infiltrating endometriosis and in

particular to evaluate rectosigmoid and bladder wall involvement.

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3. Materials and methods

3.1 Patient characteristics

Between January 2007 and May 2011, 57 consecutive patients referred for pelvic MRI because

of a clinical suspicion of endometriosis were prospectively enrolled. Among these, 36 patients

with symptomatic disease who underwent surgery (laparoscopic or robotic surgery) were

included in our study (mean age, 28 years; range, 17–39 years).

Endometriosis was suspected because of one or more of the following symptoms: pelvic pain

(36 of 36 patients), dysmenorrhea, (19 of 36 patients), dyspareunia (25 of 36 patients),

recurrence of symptoms and a past history of endometriosis (11 of 36 patients).

Exclusion criteria were the common contraindications to MRI (pacemaker, metallic foreign

bodies, and claustrophobia) and postmenopausal status.

3.2 MRI image acquisition protocol

MRI was performed with patients in the supine position by using a 1.5-T-whole-body MR

imager (Magnetom Symphony Maestro; Siemens Medical Solutions, Erlangen, Germany) with a

pelvic phased-array coil. No contrast medium was used for imaging.

Sequences acquired included thin-section high-spatial-resolution sagittal, axial and coronal

T2-weighted fast spin-echo images (FSE) with the following parameter: TR 4500 ms; TE107 ms;

slice thickness 3.0 mm; FoV 160 mm; Gap 0.8 mm; matrix 256 9 256; NEX 2.

Our protocol included also T1-weighted FSE sequence with fat saturation (TR 500 ms, TE 15

ms, slice thickness 3.0 mm, FoV 160 mm, Gap 0.8 mm, matrix 256 9 256, NEX 2) to detect

intra-nodal hematic signal and endometriomas. The total examination time was 15 min.

Retrospectively, we post-processed MR studies previously performed, in order to obtain 3D MRI

reconstructions.

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3.3 3D MRI reconstructions: the semi-automatic segmentation technique (ITK-SNAP

software)

Using MRI DICOM sagittal images radiologist made a semi-automatic segmentation of uterus,

vagina, sigma-rectum, bladder and endometriotic nodules by an open source software called

ITK-SNAP (by Cognita Corporation) (Figure 1).

Figure 1. The layout of ITK-SNAP software

Image segmentation plays a crucial role in many medical-imaging applications by facilitating

the delineation of anatomical structures and other regions of interest.

Segmentation is the process of dividing images into constituent subregions where anatomical

structures are indicated with different colors; the colors of the different organs were chosen by

the operator to facilitate differentiation (Figure 2).

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Figure 2. The colors of the different organs chosen by the operator to facilitate their differentiation

Since the organs of the pelvic floor have complex three-dimensional (3D) structures,

three-dimensional virtual reality models of the female pelvic floor enhanced the anatomy of this

complex part of the body [20-24].

A polygonal 3D model of each segmented structure was created by the semi-automatic program

which made also a surface smoothing (Figure 3a-b).

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Figure 3 a. Segmentation technique

Figure 3 b. Segmentation technique

Methods for segmentation of medical images are divided into three generations, where each

generation adds an additional level of algorithmic complexity.

The first generation is composed of the simplest forms of image analysis such as the use of

intensity thresholds and region growing: this is the earliest and lowest-level processing method.

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The second generation is characterized by the application of uncertainty models and optimization

methods, and the third generation incorporates knowledge into the segmentation process.

These generations indicate progress towards fully-automatic medical image segmentation and

their identification provides a framework for classifying the wide variety of methods that have

been devised [25-28].

Manual segmentation is possible but is a time-consuming task and subject to operator variability.

Reproducing a manual segmentation result is difficult and the level of confidence ascribed

suffers accordingly.

Automatic methods are, therefore, preferable; however, significant problems must be overcome

to achieve segmentation by automatic means and it remains an active research area.

Automatic segmentation methods are classified as either supervised or unsupervised.

Supervised segmentation requires operator interaction throughout the segmentation process

whereas unsupervised methods generally require operator involvement only after the

segmentation is complete.

Unsupervised methods are preferred to ensure a reproducible result; however, operator

interaction is still required for error correction in the event of an inadequate result [29-32].

However, segmentation of medical images involves three main image related problems.

Images contain noise that can alter the intensity of a pixel such that its classification becomes

uncertain, images exhibit intensity nonuniformity where the intensity level of a single tissue

class varies gradually over the extent of the image, and images have finite pixel size and are

subject to partial volume averaging where individual pixel volumes contain a mixture of tissue

classes so that the intensity of a pixel in the image may not be consistent with any one class.

These problems and the variability in tissue distribution among individuals in the human

population means that some degree of uncertainty must be attached to all segmentation results.

This includes segmentations performed by medical experts where variability occurs between

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experts (inter-observer variability) as well as for a given expert performing the same

segmentation on multiple occasions (intra-observer variability).

Despite this variability, image interpretation by medical experts is generally considered to be the

only available truth for in vivo imaging [33].

As far as concern the architecture of ITK-SNAP, it is based on “libraries” called Insight Toolkit

(ITK), Visualization Toolkit (VTK) and Fast LightToolkit (FLTK): they are all open source and

cross platform (Figure 4).

Figure 4. 3D reconstruction

ITK are libraries useful to implement algorithms of high level medical-image, from registration

and segmentation to filtering and quantitative measures; VTK are libraries for graphic

visualization and image processing; FLTK are useful to create graphic interfaces for the users

(GUI).

Graphic interface is very simple: the default configuration is made by four windows

(three for 2D and one for 3D navigation).

The panel control has an intuitive graphic to which we can easily accede to all functionalities.

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We focused primarily on the segmentation of magnetic resonance (MR) pelvis images although

many methods can also be applied to other image types and to images from other modalities

[34].

3.4 Surgery Examination

31/36 patients underwent laparoscopy and 5/36 patients underwent robotic surgery.

For each patient, independently from technique performed, the surgeon (more than 20 years of

experience in the evaluation of endometriosis) gave us a detailed report that included the

location, the number of lesions and the their extension to pelvic organs, including the rectal and

the bladder wall infiltration.

In 12/36 patients endometriotic nodules infiltrated bladder wall; in 19/36 patients infiltrated the

rectosigmoid serosa (13/36 rectouterine pouch; 6/36 rectovaginal pouch) and the surgeon

performed meticulous dissection (“slicing or shaving”) to preserve the rectosigmoid wall

(Figure 5 a-b-c; 6 a-b-c; 7 a-b; 9 a-b).

Figure 5 a-c. Non infiltrating recto-uterine pouch nodule; bladder wall infiltrating nodule Figure 5 b

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Figure 5 c

Figure 6 a-c. Infiltrating recto-uterine pouch nodule;

vescico-uterine non infiltrating nodule

Figure 6 b Figure 6 c

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Figure 7 a-c. Recto-vaginal pouch non infiltrating nodule Figure 7 b

Figure 8 a-b. Rectal wall infiltrating nodule Figure 8 b

Figure 9 a-b. Non infiltrating recto-uterine nodule Figure 9 b

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3.5 Image Analysis

A radiologist (with more than 8 years of experience in body MR imaging) who was blinded to

surgical information, analyzed all 3D MRI reconstructed images obtained with semi-automatic

segmentation and completed a standardized form.

MRI, 3D MRI reconstructions and their correspondence with surgery was graded on a scale

from 0 to 3 (0 _Inadequate, 1 _Poorly adequate, 2 _Fairly adequate, 3 _Perfectly coincident).

The scale was based on the possibility of depicting the exact localization of the lesions

(the Douglas pouch, the vagina, the rectal wall, the vescico-uterine pouch and the bladder wall).

DIE was described as nodular or retractile fibrotic-like tissue that was hypointense on

T2-weighted images and isointense to muscle on T1-weighted images.

The diagnosis of endometrioma was based on the identification of a cystic adnexal lesion with

characteristics of chronic bleeding: hyperintensity on fat suppressed T1-weighted images and a

signal intensity decrease (“shading”) onT2-weighted images.

Adhesions and indirect signs of adhesions were also described as hypointense peritoneal strands

that converged to loculated fluid collections or organ displacements.

If rectal involvement was suspected, the precise location (distance from the anorectal junction)

was described and stated whether or not was present. Surgical reports were used as the reference

standard.

3.6 Methods of Analysis

a) Chi-square test in small numbers of observation: Fisher's exact test

In experimental practice it is frequently necessary to check whether there is agreement between

an observed distribution and the corresponding waited or theoretical distribution.

The test is defined “test for goodness of fit” for both qualitative data, that may be classified into

nominal categories, both for quantitative data, distributed in classes of frequency: it is the

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purpose for which it was proposed the chi square test.

It is one of nonparametric methods that is used to determine whether a series of data, collected in

nature or in a laboratory, agreed with the specific hypothesis about their distribution or relative

frequency of classes.

Chi-square test is also used to compare two or more distribution observed. It is most frequently

used to verify the association between various modalities of two or more qualitative characters.

It is particularly useful in the initial phase of statistical analysis when it is necessary to look for

the most significant variables and the relationship of association between them.

It may test a null hypothesis (0 H ), if the frequency distribution of certain events observed in a

sample is consistent with a particular theoretical distribution, or to test an alternative hypothesis

when it demonstrates the existence of real difference even if the causes are unknown (1 H).

The choice between the two hypothesis is based on the estimated probability with the test.

It is the probability of finding by chance the observed distribution or a distribution that is further

away from the expected in the condition that the null hypothesis is true.

If the probability calculated is small, the logic of statistical inference rejects the null hypothesis,

implicitly accepting the alternative hypothesis.

Pearson's chi-square is the best-known of several chi-square tests statistical procedures whose

results are evaluated by reference to the chi-square distribution.

Its properties were first investigated by Karl Pearson in 1900.

The chi-square test is valid only for large samples. If the number of expected frequencies is small

in case of 2x2 tables must be used Fisher’s exact method.

b) Cohen test

K Cohen test is a measure of the agreement (coefficient of agreement) between the qualitative or

categorical responses given by two different people (inter-observer variation) or by the same

person at different times (intra-observer variation) but considering the same object.

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Agreement is considered to be good when was between 0.6 and 0.8 and was considered

to be excellent when was greater than 0.8; a K<0.6 represent a disagreement index.

3.7 Statistical Analysis

The data analysis evaluated the prevalence of infiltration detected by MRI and 3D MRI.

Subsequently it has been verified the sensitivity and specificity of MRI versus 3D-MRI and

then the sensitivity of these two techniques compared to surgery (gold standard).

By means of analysis between the observed and expected values (chi-square test) has been

evaluated the accuracy of MRI and 3D-MRI to detect the exact site of the nodules of DIE, their

volume and the grade of parietal infiltration (rectum, bladder).

In particular, to underline the best accuracy of 3D-MRI in the evaluation of recosigmoid/bladder

infiltration, we estimated the intra-observer-agreement/disagreement (Cohen index).

Agreement (k coefficient ) was considered excellent when it was > 0.8, good when it resulted

between 0.6 and 0.8 and evaluated as a disagreement index when <0.6.

4 .Results

In 36 (100%) of 36 patients, DIE was confirmed at surgery and histopathologic examination.

18/36 (50%) patients had endometriotic nodules infiltrating the recto-uterine pouch, 12/36(33%)

the vescico-uterine pouch and 6/36 (16%) the rectovaginal pouch.

10/36 patients (27%) had endometrioma correlating with DIE and another 4/36 (11%) had also

adenomyosis.

MRI detected the infiltration of recto-sigma and bladder in 23/36 (63%) patients, 3D-MRI

increased this percentage to 83% (30/36). In particular, in the group of 18/36 patients with

rectouterine localization, MRI revealed the infiltration in 10/18 (56%) and 3D-MRI in 13/18

(72%); in the group of 12/36 patients with vescicouterine localization MRI revealed infiltration

in 9/12(75%) 3D-MRI in 11/12 (92%); in the group of 6/36 patients with rectovaginal

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localization MRI revealed infiltration in 4/6 (67%) and 3D-MRI in 6/6 (100%) (Table 1).

Table 1. Infiltration: MRI vs 3D-MRI

If 3D MRI is considered the gold standard method, the sensitivity of MRI amounted respectively

to 77% in the recto-uterine pouch, 82% in the vescico-uterine pouch and 67% in the recto-

vaginal pouch. These values pointed out the accuracy of 3D MRI to identify positive tests and its

major sensitivity (Table 2).

Table 2. MRI versus 3D-MRI

Moreover were calculated the sensitivity of MRI and 3D-MRI versus surgery (Table 3).

Table 3. Sensitivity of MRI and 3D-MRI versus surgery

Also intra-observer agreement (analyzed with chi-square test) evidenced a difference statistically

Pts MRI % 3DMRI %

Total 36 23/36 0.63 30/36 0.83

Recto-uterine pouch 18 10/18 0.56 13/18 0.72

Vescico-uterine pouch 12 9/12 0.75 11/12 0.92

Recto-vaginal pouch 4 4/6 0.67 6/6 1

MRI vs 3D-MRI

Sensitivity (%) Specificity (%) PPV (%) NPV (%)

Recto-uterine pouch 77 (10/13) 100 (5/5) 100 (10/10) 62 (5/8)

Vescico-uterine pouch 82 (9/11) 100 (1/1) 100 (9/9) 33 (1/3)

Recto-vaginal pouch 67 (4/6) - 100 (4/4) -

MRI vs surgery

3D-MRI vs surgery

Sensitivity (%) 64% 83%

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significative (p< 0.05) between the two methods (Table 4).

Table 4. Intra-observer agreement

The analysis of qualitative data, useful to identify the size of nodules, their localization and the

infiltration of contiguous structures supported the best accuracy of 3D-MRI respect to MRI

alone.

In particular as far as concerned localization 3D-MRI resulted perfectly coincident (86% )

respect to MRI alone (67%) (p<0.000), (Graph 1); regard to dimension 3D-MRI resulted

perfectly coincident (86% ) respect to MRI alone (67%) (p<0.000), (Graph 2); the rectosigmoid

infiltration resulted perfectly coincident with 3D-MRI (79%) versus MRI alone (58%).

The poorly coincidence was 42% for MRI and 21% for 3D-MRI (p<0.006), (Graph 3); the

bladder infiltration resulted perfectly coincident with 3D-MRI (92%) versus MRI alone (75%).

The poorly coincidence was 25% for MRI and 8% for 3D-MRI (p<0.003), (Graph 4).

Intra-observer agreement between MRI and 3D-MRI

P

Localization 0,000

Dimension 0,000

Bladder infiltration 0,003

Rectum infiltration 0,006

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Graph 1. 3D vs MRI: localization

Graph 2. 3D vs MRI: dimension

0

5

10

15

20

25

30

35

Inadequate Poorly adequate

Fairly adequate

Perfectly coincident

3D MRI

0

5

10

15

20

25

30

35

Inadequate Poorly adequate

Fairly adequate

Perfectly coincident

3D MRI

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Graph 3. 3D vs MRI: rectal infiltration

Graph 4. 3D vs MRI: bladder infiltration

In order to confirm the differences between MRI and 3DMRI findings detected by means of

radiologist qualitative analysis, it was calculated Cohen’s K coefficient: for each evaluated

finding (localization, dimension, parietal infiltration) the K Cohen indexes resulted lower than

concordance parameters, demonstrating the effective discordance (all K coefficients were < 0.6)

between MRI and 3DMRI and than validating the greater efficacy of MRI supported by 3D

reconstructions.

0 2 4 6 8

10 12 14 16 18 20

Inadequate

Poorly adequate

Perfectly

coincident

3D MRI

Fairly adequate

0

2

4

6

8

10

12

Inadequate

Poorly adequate

Fairly adequate

Perfectly coincident

3D MRI

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Table 5. Agreement/disagreement obtained analyzing MRI and 3DMRI findings

5. Conclusions

Our study results showed an excellent correlation of 3D MRI reconstructions with surgical

examination findings of DIE. In particular, 3D MRI reconstructions detected the specific

locations and dimension of the endometriosis nodules with a higher sensitivity (83%) and

diagnostic accuracy (86%).

Due to this, the addiction of 3D MRI reconstruction in the future could influence the decision of

the surgeon to perform laparoscopy or robotic surgery rather than more extensive surgery,

providing the precise preoperative mapping of deep endometrial lesions especially in forms of

advanced endometriosis (stage IV) infiltrating rectosigmoid colon or bladder.

In our series, the prevalence of rectosigmoid wall involvement was high and the correlation

between 3D MRI and surgery just about the degree of invasion of this structure resulted excellent

(Cohen k coefficient of 0.28).

On the hand anterior deep endometriosis is much less frequent than posterior involvement and

involves the vescicouterine pouch and the bladder. Bladder involvement occurs in 2-6.4 % of

patients [6] and also at this level 3D MRI imaging resulted accurate (Cohen k coefficient of

0.39).

In our study, we had 12/36 cases of anterior deep endometriosis that infiltrated the bladder: while

Concordance of MRI and 3DMRI findings

K di Cohen

Localization 0,16

Dimension 0,18

Bladder infiltration 0,39

Rectal infiltration 0,28

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conventional MRI correctly identified 8/12 cases, 3D MRI reconstructions depicted correctly

11/12 cases of bladder involvement identifying also the smaller lesion (<1 cm): we missed one

case because the bladder was empty.

18/36 patients had the endometriosis nodules localized into the rectouterine pouch: 10/18 cases

were correctly identified at conventional MRI, while 3D MRI reconstructions depicted correctly

13/18 cases of rectosigmoid wall involvement and any case was missed.

6/36 patients had the nodules localization into the rectovaginal pouch: 4/6 cases were correctly

identified at conventional MRI, while 3D MRI reconstructions we depicted correctly 6/6 cases of

rectal wall involvement and any case was missed.

The assessment of endometriosis may be laborious for the patient, who may undergo multiple

examinations like transvaginal US, transrectal US, barium enema, cystoscopy, and rectoscopy.

Instead, MRI imaging supported by 3D MRI reconstructions enabled complete visualization of

the pelvis and therefore could be the preoperative imaging technique of choice for the

assessment of patients with a clinical suspicion of DIE also assessing the infiltration of

rectosigmoid and bladder walls.

Future research in the segmentation of medical images will strive toward improving the

accuracy, precision, and computational speed of segmentation methods, in order to reduce the

amount of manual interaction by incorporating prior information from atlases and by combining

discrete and continuous spatial-domain segmentation methods [20].

Not all 57 patients underwent surgery, so we do not know the accuracy of 3D MRI

reconstructions in our total study population; including only patients who underwent surgery

likely skewed our results, because of the poorly population study.

Our surgeon knew the results of the MRI examination, and also this could have biased results at

surgery.

Finally, because our population was selected in a referral center, it was biased for the prevalence

of endometriosis.

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In conclusion, pelvic MRI supported by 3D MRI reconstructions provided encouraging results

for the diagnosis and the preoperative planning of DIE providing the exact volume of the lesions

and enabling a precise mapping of these before surgery resulting particularly valuable as image-

guided surgery techinque, in wich visualization of anatomy is a critical component.

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