Part One Diffusion-Weighted MRI in The Genitourinary System

Abstract

Diffusion-weighted imaging (DWI) constitutes a major functional parameter performed in Magnetic Resonance Imaging (MRI). The DW sequence is performed by acquiring a set of native images described by their b-values, each b-value representing the strength of the diffusion MR gradients specific to that sequence. By fitting the data with models describing the motion of water in tissue, an apparent diffusion coefficient (ADC) map is built and allows the assessment of water mobility inside the tissue. The high cellularity of tumors restricts the water diffusion and decreases the value of ADC within tumors, which makes them appear hypointense on ADC maps. The role of this sequence now largely exceeds its first clinical apparitions in neuroimaging, whereby the method helped diagnose the early phases of cerebral ischemic stroke. The applications extend to whole-body imaging for both neoplastic and non-neoplastic diseases. This review emphasizes the integration of DWI in the genitourinary system imaging by outlining the sequence’s usage in the female pelvis, prostate, bladder, penis, testis, and kidney MRI. In gynecologic imaging, DWI is an essential sequence for the characterization of cervix tumors and endometrial carcinomas, as well as to differentiate between leiomyosarcoma and benign leiomyoma of the uterus. In ovarian epithelial neoplasms, DWI provides key information for the characterization of solid components in heterogeneous complex ovarian masses. In prostate imaging, DWI became an essential part of multi-parametric Magnetic Resonance Imaging (mpMRI) to detect prostate cancer. The Prostate Imaging–Reporting and Data System (PI-RADS) scoring the probability of significant prostate tumors have significantly contributed to this success. Its contribution has established mpMRI as a mandatory examination for the planning of prostate biopsies and radical prostatectomy. Following a similar approach, DWI was included in multiparametric protocols for the bladder and the testis. In renal imaging, DWI is not able to robustly differentiate between malignant and benign renal tumors but may be helpful to characterize tumor subtypes, including clear-cell and non-clear-cell renal carcinomas or low-fat angiomyolipomas. One of the most promising developments of renal DWI is the estimation of renal fibrosis in chronic kidney disease (CKD) patients. In conclusion, DWI constitutes a major advancement in genitourinary imaging with a central role in decision algorithms in the female pelvis and prostate cancer, now allowing promising applications in renal imaging or the bladder and testicular mpMRI.

Keywords

genitourinary MRI; diffusion; prostate; kidney; female pelvis; cancer.

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Introduction

In the broad range of clinical imaging methods, diffusion-weighted MR imaging (DWI) stands out for its exceptional value to patient management as well as for its fascinating technique. With a spatial resolution close to 1 mm, Diffusion-Weighted (DW) sequences probe the free movement of water molecules in the tissue at the micrometer level, with an amplification factor close to a thousand. First introduced in 1986 by Le Bihan et al. [1], DWI experienced major development after the demonstration of its ability to detect cerebral ischemia long before any other non-invasive methods [2,3]. While the process of impaired water diffusion following cellular swelling is still partly understood [4], the use of DWI was rapidly extended to other diseases. As water diffusion also decreases in tumors due to their high cellular density, many successful applications of DWI have been validated in oncology and, although the initial applications were limited to the brain, DWI expanded rapidly to other body parts including the genitourinary system.

The genitourinary system is usually investigated by ultrasound or axial computed tomography (CT) as first-line imaging modalities to detect signs of malignant lesions or to perform disease staging. Yet, magnetic resonance imaging (MRI) has emerged as a key player in the diagnosis and characterization of tumorous and non-tumorous diseases, in part due to its superior tissue contrast. MRI not only grants high-resolution morphological images but also provides various functional information, such as tissue oxygenation, perfusion, or diffusion. Among these functional imaging techniques, DWI certainly impacts the management of genitourinary cancer patients the most. In particular, DWI has become a pivotal tool in the diagnosis and staging of many gynecologic and prostatic cancers. Finally, driven by the advancement of respiratory motion mitigation methods, DWI has also been successfully applied to renal imaging.

Beyond renal cancer, DWI appears as an emerging tool that will most likely play a major part in the clinical management of non-tumorous renal diseases. This work aims to review the current applications as well as potential future use cases of DWI, with a focus on the female pelvis, the prostate, the bladder, the penis, the testis, and the kidneys.

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Principles of Diffusion-Weighted MRI in the Genitourinary System

Water is the most abundant molecule in soft tissues. Each water molecule bears two hydrogen nuclear spins, which are the physical source of the MRI signal in the overwhelming majority of clinical applications. Water molecules undergo chaotic perpetual microscopic motion, called molecular diffusion, exploring the available spaces in intra- and extracellular compartments. In the presence of a strong static magnetic field, these hydrogen nuclear spins begin to rotate around the axis of the field in a process called precession. The precession frequency is directly proportionate to the amplitude of the static magnetic field.

The well-known spin echo MR technique [5] yields intra-voxel refocusing of spins by “time mirroring” the individual differences in precession frequencies. These frequency offsets can occur due to local inhomogeneities of the static magnetic field or can be dynamically induced by the application of magnetic gradient pulses. Spin echo refocusing is imperfect if the observed spins are undergoing chaotic motion, corresponding to a partial loss of spin coherence and attenuation of the spin echo signal intensity [6]. Therefore, the observed MRI signal contains information on the molecular motion of water and specifically, the motion restriction due to various biological structures [4].

In a free medium, the probability to locate a given water molecule after a given period is a 3D isotropic Gaussian function, with full width at half maximum (FWHM) increasing proportionally to the square root of the observation time. In this case, a scalar value, the apparent diffusion coefficient (ADC, mm2 ·s −1 ), is determined as a measurement of the diffusion’s magnitude [7] and the MRI signal attenuation is a single exponential function of the sequence’s gradient weighting. The strength of such magnetic gradients is named using the letter “b” followed by a numeric variable representing the amplitude and duration of the applied gradients, expressed in SI base units of s·mm−2. Typical pairs of b-values vary between 0–500 or 1000 s/mm2 for the abdomen and 0–200 and 1000 s/mm2 for the pelvis [8].

In prostate imaging, values range between 0 and 2000 s/mm2, for example, b50, b500, b1000, b1500, and b2000. Diffusion-weighted sequences using gradient values higher than 1000 s/mm2 can be referred to as high (or even ultra-high) b-values DW sequences and their significance in prostate MRI has been demonstrated by multiple studies [9,10]. In the presence of such gradients, if barrier-like structures restrict molecular movements in a tissue, a high MR signal will be preserved and the tissue will appear distinctly hyperintense on DW images and hypointense on ADC, reflecting the reduced water diffusion. In theory, the simplest way to measure ADC only requires DWI acquisitions for two b-values and a monoexponential fit, but other more complex models have been developed to better describe the water molecule motion inside biological tissues. These models have been mainly investigated in the prostate and are described in the dedicated section.

Since MRI does not directly sample the object but its spatial frequencies (deposited in the so-called k-space) it is particularly sensitive to motion. Tissue displacement during the acquisition yields moderate and sometimes severe artifacts [11], for instance, blurring, ghosting, and alteration of tissue contrast. Various mitigation techniques have been developed to correct movement during the acquisition. The most basic method to avoid respiratory motion is to acquire images during a breath hold. Temporal synchronization of MR signal acquisition with the physiological motion was then obtained using triggering or synchronization to the ECG or respiratory waveforms. More elaborate approaches consist of tracking the tissue position by using MR-based navigators to prospectively or retrospectively correct motion. In a clinical setting, the acquisition of high-quality renal or pelvic DW images within a single apnea is not always feasible. Therefore, motion compensation techniques may be required to improve the image quality of DWI and to avoid the confounding effect of macroscopic movements on water diffusion [12,13].

To further reduce the effect of physiologic motion, DWI is conventionally acquired using single-shot encoding schemes which are referred to as echo planar imaging (EPI). In EPI, the initial excitation RF pulse generating the MR signal is followed by a series of gradient patterns and refocusing RF pulses that cover the k-space of each slice. The k-space in the frequency domain is then converted into an image using a mathematical operation, the Fourier transform. EPI is prone to geometric distortion when the local magnetic field is inhomogeneous and to other more complex artifacts, such as imperfect saturation of the fat signal. One solution to overcome these limitations is the segmentation of k-space yet at the cost of an increased acquisition time. The “Resolve” (REadout Segmentation Of Long Variable Echo-trains) technique [14] consists of the shortening of read-out lines in k-space which are subdivided into several parallel bands, at least three. This feature allows a reduction of the echo time and the frequency-encoding time. In return, the technique delivers sharper images that are generally free of distortion and high spatial resolution, allowing for broad use in prostate and renal DWI.

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Diffusion-Weighted Female Pelvis Imaging

Magnetic resonance imaging is a complementary imaging modality usually performed after an ultrasound. DWI is crucial and performed in most female pelvic studies in addition to conventional morphologic T1- and T2-Weighted (T2W) sequences, as shown in Figure 1. DWI, together with dynamic contrast-enhanced (DCE) imaging, is part of the functional imaging apparatus which in recent times increased the diagnostic performance of MRI in the field of gynecologic oncology. As DWI suffers from poor spatial resolution, and therefore, less anatomical definition, it has to be used in association with a morphologic T2W sequence [15]. DWI is particularly useful in the assessment of endometrial and cervical cancer, helping to differentiate between benign and malignant uterine or ovarian lesions and assessing the peritoneal tumor extension of gynecologic cancers [16].

Figure 1. The normal female pelvis of a 26-year-old in the coronal plane. (A) T2W image; (B) ADC map; (C) b-value = 0 s/mm2 DW image; (D) b-value = 1000 s/mm2 DW image. We see the disappearance of high fluid signal (as the one in the bladder) with increasing b-values but the persistence of high signal intensity on high b-value for the endometrium.

Most tumors of the cervix are squamous cell carcinomas, known to be associated with exposure to human papillomavirus (HPV) and more frequent than adenocarcinomas of the cervix. While the diagnosis is biopsy-proven, the role of imaging in cancer staging is. The International Federation of Obstetrics and Gynecology (FIGO) staging is essential for oncological therapeutic management. It includes carcinoma in situ (Tis), carcinoma confined to the uterus (T1), carcinoma invading beyond the uterus (T2), carcinoma extending to the pelvic wall and/or involving the lower third of the vagina (T3), and carcinoma invading the bladder or rectum (T4). Pelvic MRI is recommended for the local staging of cervical tumors as emphasized in the 2018 FIGO staging update [17].

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In addition to the morphologic T2W sequences, DWI is used to assess the local extension of the carcinoma and is equivalent to contrast-enhanced MRI [18]. The T2W axial oblique plane perpendicular to the long axis of the cervix is important in assessing parametrial invasion (stage IIB) and can be co-registered with the high b-value DW sequence to improve tumoral tissue delineation [19], as demonstrated in Figure 2. Cervical carcinomas are characterized by hypercellularity resulting in high signal intensity (SI) on high b-value (1000 s/mm2 ) DW images and a low Signal Intensity (SI) on the ADC map compared to normal cervical stroma [16]. So far, no ADC cutoff value has been validated to predict the presence of malignancy, mainly because of the mutual dependence between the calculated ADC value and the range of b-values used for calculation [16]. In the context of follow-up after local radiotherapy and systemic chemotherapy treatment, DWI is used to differentiate between residual disease and local fibrosis [20], as well as to detect tumor recurrence [21]. DWI may also be used as a biomarker for monitoring tumor response [22,23]. In a recent meta-analysis on the use of artificial intelligence (AI) in gynecologic tumors, cervical cancer was subject to a high number of studies (34 from 71) mainly focusing on the prognostic value of imaging [24]. As all MR sequences are exploited collectively in AI, it remains difficult to extrapolate the specific utility of DWI within this kind of black box approach.

Figure 2. MR images of a 66-year-old woman with a known cervical carcinoma. (A) Sagittal T2W image; (B) axial T2W image perpendicular to the cervical axis. Cervical cancer and its extension appearing as low-contrasted T2W area (arrow) through the normal stroma and the right parametrium, (C) high b-value (b = 1000 s/mm2 ) and (D) fusion images between T2W and high b-value sequences for better evaluation of the carcinoma’s extension.

Endometrial carcinoma is the most common gynecologic malignancy in developed countries, concerning women above 50 years old. According to the Bokhman classified. tion (25], Type I endometrial tumor also known as endometrioid carcinoma is the most frequent type of cancer, with a generally favorable outcome. The 2nd most frequent histo-logic type of endometrial cancer corresponds to the papillary clear cell adenosquamous carcinoma and belongs to the type ll group of tumors. Following FIGO classification, stage I of the tumor is limited to the body of the uterus, and stage ll is defined by an extension through the cervical stroma. In stage Ill, the tumor locally invades the adnexa, the vaginaor the parametrium, and/or the pelvic floor, or presents para-aortic lymphadenopathy whereas stage IV is defined by an extension of the tumor to the adjacent bladder or bowel or the presence of distant metastases.

MRI in endometrial cancer is performed for the staging of the disease. Invasion of less than 50% of the myometrium to separate stage la and Ib is based on a morphologic T2W plane perpendicular to the endometrial cavity. Endometrial cancer is usually hyperintense to the myometrium but can be difficult to differentiate from the surrounding tissue as illustrated in Figure 3. On DWI cancer shows diffusion restriction with a high b-1000 signal and low ADC values compared to the normal endometrium and adjacent myometrium. The addition of DWI to T2W imaging significantly improves the staging of endometrial cancer (26,27]. It is even more indispensable in patients with impaired renal function who cannot benefit from gadolinium administration, and therefore, from contrast-enhanced MRIHowever, the combination of DWI and contrast-enhanced MRI remains the best approach to predict myometrial invasion, as supported by a recent study on machine learning (28)DWI is also helpful in detecting other pelvic depositions in high-grade tumors (8]. A false positive high signal on DWI with low ADC values in the endometrial cavity corresponds to secretory and hyperplastic endometrium or blood during the female cycle which is easily recognized by its high signal on T1W FatSat sequences (8].

Figure 3. MR images of endometrial carcinoma in a 93-year-old woman. (A) Sagittal T2W image in the endometrial cavity with extension in the myometrium smaller than 50% of its thickness. (B) ADC map shows restricted diffusion in the endometrial carcinoma visible as a dark area (arrow) in opposition with (C) high signal (arrow) on high b-value images (b = 1000 s/mm?). (D) post-injection of gadolinium T1W image shows the endometrial carcinoma (arrow) with an enhancement less than the myometrium s muscle.

Leiomyosarcomas are rare malignant tumors of the uterus and account for less than 10% of uterine cancers. The differentiation between benign leiomyoma and leiomyosarcoma is essential for the surgical management of these lesions. MRI and especially DWl play an important role in the characterization and management of both tumors. In addition to morphologic specificities of leiomyosarcoma, such as the intermediate T2 signal, nodularborders, and hemorrhagic components, "T2 dark areas and central unenhanced areas (291DW-based parameters constitute another essential tool to differentiate benign leiomyoma from leiomyosarcoma. As shown in Figure 4, uterine leiomyosarcoma usually shows low ADC values and increased signal intensity on high b-value DW images compared to the normal myometrium (15]. In the meta-analysis of Virarkar et al. which included 795 patients from eight studies, ADC values were significantly lower in leiomyosarcoma than in leiomyomas (30]. In a recent case-control retrospective study, Wahab et al. proposed a diagnostic algorithm to differentiate leiomyomas from uterine sarcomas based on the presence of lymphadenopathy higher SI on high b-value images in the mass relative to the endometrium and ADC value inferior to 0.905 x 10-3 mm?/s 31]. The respective sensitivity and specificity of this algorithm to classify the uterine masses were 97% and 99%in a training set of 156 patients, 88% and 100% in a first validation set of 42 patients, and 83% and 97% in a second validation set of 59 patients. Focally or globally reduced T2W Sland DWI-based SI lower than the endometrium allows us to confidently diagnose the mass as benign [31]. However, this promising approach needs further validation by prospective multicentric studies.

Figure 4. MR images of leiomyosarcoma in a 54-year-old woman. (A) voluminous leiomyosarcoma with an intermediary 2W signal and irregular borders (arrow). Part of the leiomyosarcoma demonstrates a diffusion restriction with low (B) ADC values and high signal on the (C) b-1000 sequenceD) post-injection of gadolinium T1 W sequence shows the absence of central enhancement consistent with central necrosis. All features are characteristic of malignancy within a leiomyoma.

Ovarian tumor is mainly an epithelial type of cancer (95%), including serous and mucinous cancers. The two other categories include the sex-cord stromal tumor and the germ cell tumor types. Ovarian cancer is the most lethal of all gynecologic cancers with the prognosis determined by the initial staging at the time of detection. A precise characterization is, therefore, paramount to providing an accurate determination of the patient's prognosis. The initial diagnosis is usually achieved by ultrasound examination while MRI is kept for indeterminate cases.

Normal ovaries usually show high SI on both the high b-value sequences and the corresponding ADC maps, corresponding to the so-called "T2 shine-through" effect. DWI is essential for the characterization of a suspicious solid component in heterogeneous complex ovarian masses, identifying solid high cellularity content in malignant ovarian tumors (32as per the current European Society of Urogenital Radiology (ESUR) recommendations (33Illustrative MR images of adenocarcinoma can be found in Figure 5. The coregistration between the high b-value DWI and the morphologic T2W images is very efficient for this purpose. An adnexal lesion can be classified as benign when its solid component is hypointense on both the high b-value DWI and the T2W images (dark/ dark" lesion) (34]. However, DWI alone does not suffice to assess the malignancy of an ovarian tumor, as some benign lesions, such as mature cystic teratomas, endometriomas, or functional hemorrhagic cysts can show an impeded diffusion (16,32,35]. Dynamic contrast-enhanced MRI sequences are essential to further assess the probability of malignancy.

Figure 5. Histologically proven left ovary adenocarcinoma in a 64-year-old woman. (A) T2Whyperintense heterogeneous left adnexal mass next to the uterus (*). Tissular bilobed left adnexal mass with parts of low (B) ADC values and high (C) b-1000 signal consistent with a diffusion restriction in the lesion (C). Post injection of gadolinium (D) T1W sequence with fat-sa turation shows a heterogeneous enhancement (arrow).

The important role of DWI in the characterization of ovarian tumors is well demonstrated in the recent introduction of the Ovarian-Adnexal Reporting and Data System(O-RADS)-MRI scoring system, an international effort to improve the standardization of adnexal MRI reports (36,37]. T2W images and DWI are sufficient to differentiate lesions with solid content in almost certainly benign cases (O-RADS-MRI 2) and higher (O-RADS-MRI3 to 5), as the enhancement pattern of homogenously hypointense lesions on T2W and DWimages does not impact the O-RADS-MRI classification (37]. The O-RADS-MRI risk score is built on a prospective, multicenter study in 1194 women with histologic examination and a 2-year follow-up imaging or clinical examination. The risk score yields an overall accuracy of 92%, a sensitivity of 93%, a specificity of 91%, a positive predictive value of 71%, and a negative predictive value of 98% with a good agreement between junior and experienced readers, as attested by a kappa-score of 0.784 [36]. O-RADS-MRI validation and clinical acceptance are well advanced [38,39] and will be further improved when dedicated management recommendations are available [40].

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Some pitfalls in the evaluation of diffusion-weighted images must be avoided. As mentioned previously, T2 shine-through, seen as a persistent hyperintensity throughout high b-value and ADC images, is one of them. Not all structures with high signal on diffusion are cancer and one must be aware that healthy tissues can yield low ADC values and high signal on high b-value images: normal endometrium, bowel, kidneys, spleen, and lymph nodes [41,42]. Other criteria, such as the size, the heterogeneity, and the very low ADC values can help to differentiate suspicious lymph nodes from normal ones. The normal endometrium in women of reproductive age can also show restricted diffusion because of the tissue’s high cell density. In this matter, quantitative evaluation of the tissue on ADC maps must be sought, as endometrial tumors present with even lower ADC values compared to normal adjacent tissue [15,16].

In conclusion, DWI is crucial to determine the malignancy of pelvic lesions and to assess their extension. It is an important sequence that must be part of all pelvic MRI examinations. Analysis of these sequences must use both the b-values sequences and the ADC map to avoid misinterpretation and must be compared to the signal of normal adjacent structure in the pelvis. It has to be analyzed in combination with the morphologic T2W, T1W, and gadolinium-based sequences to avoid misdiagnosing some benign pelvic lesions as malignant.

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Thomas De Perrot 1, Christine Sadjo Zoua 1 , Carl G. Glessgen 1 , Diomidis Botsikas 1 , Lena Berchtold 2 , Rares Salomir 1 , Sophie De Seigneux 2 , Harriet C. Thoeny 3 and Jean-Paul Vallée 1

1 Division of Radiology, Geneva University Hospitals and University of Geneva, 1205 Geneva, Switzerland; christine.sadjo@hcuge.ch (C.S.Z.); carl.glessgen@hcuge.ch (C.G.G.); diomidis.botsikas@hcuge.ch (D.B.); raresvincent.salomir@hcuge.ch (R.S.); jean-paul.vallee@hcuge.ch (J.-P.V.)

2 Division of Nephrology, Geneva University Hospitals, 1205 Geneva, Switzerland; lena.berchtold@hcuge.ch (L.B.); sophie.deseigneux@hcuge.ch (S.D.S.)

3 Division of Radiology, Hôpital Cantonal Fribourgois, 1752 Villars-sur-Glâne, Switzerland; harriet.thoeny@h-fr.ch