Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2021  |  Volume : 34  |  Issue : 1  |  Page : 253-258

The role of MRI in evaluation of cervical carcinoma


1 Radiodiagnosis Department, Faculty of Medicine, Menoufia University, Shebeen El-Kom, Egypt
2 Radiodiagnosis Department, Menouf General Hospital, Ministry of Health, Menouf, Egypt

Date of Submission28-Apr-2019
Date of Decision24-May-2019
Date of Acceptance01-Jun-2019
Date of Web Publication27-Mar-2021

Correspondence Address:
Nehal A Ahmed
Radiodiagnosis Department, Menouf General Hospital, Ministry of Health, Abu Alam Street, Menouf, Menoufia
Egypt
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/mmj.mmj_169_19

Rights and Permissions
  Abstract 


Objective
To review the role of MRI in the diagnosis and staging of cervical carcinoma.
Background
It is widely accepted that MRI is the preferred imaging modality for detection of cervical carcinoma nowadays; different techniques are needed for early detection of the disease, its correct staging, and treatment.
Patients and methods
This case–control study included 62 patients divided into a case group of 32 patients diagnosed clinically or by transvaginal ultrasound with cervical cancer, confirmed by biopsy, and a control group of 30 patients who had pelvic MRI for other reasons. All patients were assessed by history and review of previous ultrasound reports and underwent pelvic MRI with diffusion-weighted MRI and dynamic contrast-enhanced MRI.
Results
This study revealed a statistically significant difference between the case and control groups regarding apparent diffusion coefficient (ADC) value (P < 0.001). There was no significant difference in ADC value between different subtypes of cervical cancer. The diagnostic accuracy of ADC in discrimination of patients and control in defining the best cutoff value of ADC (×10–3), which was 1.10, was 99.5%, with sensitivity of 96.6% and specificity of 96.9%.
Conclusion
Diffusion-weighted imaging is a potentially useful adjunct to conventional MRI in evaluating cervical carcinoma, thus improving overall diagnostic accuracy, tumor staging, prediction of response to therapy, and treatment follow-up. ADC values may vary not only with different imaging parameters but also with different types of MRI systems.

Keywords: apparent diffusion coefficient, cancer cervix, diffusion-weighted MRI


How to cite this article:
Mohamed HH, Mohamed SA, Ahmed NA. The role of MRI in evaluation of cervical carcinoma. Menoufia Med J 2021;34:253-8

How to cite this URL:
Mohamed HH, Mohamed SA, Ahmed NA. The role of MRI in evaluation of cervical carcinoma. Menoufia Med J [serial online] 2021 [cited 2021 Jun 21];34:253-8. Available from: http://www.mmj.eg.net/text.asp?2021/34/1/253/312003




  Introduction Top


Uterine cervical cancer is the third most common malignancy affecting the female genital tract in middle age group, between 45 and 55 years of age [1],[2]. The incidence is increasing in developing countries with mortality of nearly 30% in invasive cases, mainly if they are recurrent or undertreated [3]. Hence, early detection of the disease, its correct staging, and treatment are of great importance.

The International Federation of Gynecology and Obstetrics (FIGO) staging system, updated in 2009, is commonly used for treatment planning, but it cannot be relied upon in assessing tumor volume and nodal status [1],[4].

MRI is the preferred imaging modality for detection of cervical carcinoma because of its ability to assess soft tissue in detail, allowing detection of stromal and parametrial invasion. MRI demonstrates the exact volume, shape, and direction of the primary lesion; local extent of the disease; and nodal status accurately, which helps in treatment planning. Tumor behavior to chemoradiation is also better evaluated with MRI [5].

T2-weighted images (T2W) play a crucial role in identification of the primary tumor and assessment of its extent [5]. Acquisition in axial, sagittal, and coronal planes is enough for staging in most of the cases. The tumor shows intermediate to high signal on T2W images. Early tumors can be identified on dynamic contrast-enhanced (DCE) images [6]. Tumor tissue has significantly low apparent diffusion coefficient (ADC) value as compared with nontumor tissue [5]. The aim of this study was to review the role of MRI in the diagnosis and staging of cervical carcinoma.


  Patients and methods Top


This cross-sectional study included 62 patients recruited from National institute of oncology in Cairo spanning the period from November 2017 to November 2018. A written consent form approved by the Ethical Research Committee of Menoufia Faculty of Medicine was obtained from every participant before the study initiation. This was in accordance with Helsinki Declaration in 1975 (revised in 2000).

Participants of the study were distributed into two groups: a case group composed of 32 patients in whom cervical cancer had been provisionally diagnosed clinically or by transvaginal US and confirmed by biopsy, and a control group composed of 30 patients. Patients in the study group presented with menorrhagia, vaginal discharge, and postmenopausal bleeding associated with bulky cervix with increased vascularity detected by pelvic US. The control group included patients having normal uterine cervix but other pelvic diseases, also detected by US. Both groups were referred to the radiology department for MRI study of the pelvis.

Exclusion criteria included patients with absolute contraindications to MRI such as electronically, magnetically, and mechanically activated implants and ferromagnetic or electronically operated active devices like automatic cardioverter defibrillators or cardiac pacemakers. In addition, metallic splinters in the eye, ferromagnetic haemostatic clips in the central nervous system, and patients receiving radiotherapy or chemotherapy were additional exclusion criteria for this study.

All patients were assessed through full clinical history taking and review of the previous ultrasound (US) reports and underwent pelvic MR with diffusion-weighted imaging (DWI) and DCE-MR. Patients were asked to fast for 4 h before the MR study to limit artifacts owing to small bowel peristalsis, and intravenous administration of an antispasmodic 6th of October City drug (10 mg of visceralgine, SEDICO Pharmaceuticals, Egypt) was given immediately before MRI to reduce bowel peristalsis. We used a 1.5-T MRI unit (Achieva, Philips medical system) to conduct MRI examination. The examination was done for all patients with a partially full bladder. Patients were imaged in the supine position using a surface phased-array coil to provide higher signal-to-noise ratio than a body coil, with increased spatial resolution and reduced imaging time. An anterior pre-saturation band was used to reduce breathing motion artifacts. Pre-saturation pulses above and below the imaged volume reduce intravascular signals from pelvic vessels.

We adopted the following MRI protocol: axial T1-weighted images (T1WI) (TR/TE, 500/10 ms) and axial T2W images (TR/TE, 3300/100 ms), with slice thickness of 6 mm, gap of 1 mm, FOV of 32–42 cm, and matrix of 256 × 256, and sagittal T2W images and coronal T2W images, with slice thickness of 8–10 mm, gap of 1 mm, FOV of 40–50 cm, and matrix of 256 × 256. Sequences of diffusion-weighted (DW)-MRI were acquired in the axial plane before administration of contrast medium by using a single-shot echo-planar imaging sequence (with b values 0, 300, and 600; TR/TE, 5000/70; slice thickness: 6 mm; gap, 1 mm; FOV 36 cm; and matrix: 128 × 128). DCE-MRI: postcontrast T1 High Resolution Isotropic Volume Excitation (THRIVE high-resolution isotropic volume examination) images were obtained immediately after manually injecting gadolinium at a dose of 0.1 mmol/kg of body weight (maximum, 20 ml). This was followed by injection of 20 ml of normal saline for flushing the tube. Images were obtained sequentially at 0, 30, 60, 90, and 120 s.

MRIs were analyzed to assess MRI appearance of the tumor with respect to size, signal intensity, and enhancement, involvement of other pelvic organs, presence of infiltrated pelvic or para-aortic lymph nodes, peritoneal or omental deposits, hydronephrosis, or presence of ascites. Staging analysis was done using combination of T2W MRI sequence and dynamic postcontrast MRI. The MRI staging followed the FIGO staging analysis, in addition to interpretation of DWI. Quantitative analysis was done through generating ADC map, followed by selecting the ROI manually on, which was then automatically calculated on the work station to get a mean ADC value (×10-3 mm).

Statistical analysis

Data were collected and entered to the computer using statistical package for the social sciences program for statistical analysis, version 21 (SPSS Inc., Chicago, Illinois, USA). Data were entered as numerical or categorical, as appropriate. Descriptive statistics were performed with quantitative data shown as mean, SD, and range. Qualitative data were expressed as frequency (count) and relative frequency (percentage) at 95% confidence interval. Analytical statistics were performed with χ2-test and Fisher exact test to measure association between qualitative variables, as appropriate. The accuracy of MRI in predicting different pathological lesions was presented as sensitivity, specificity, positive predictive value, and negative predictive value. Comparison between cases and control was done using unpaired t-test. Receiver operating characteristics (ROC) curve was constructed with area under curve analysis performed to detect best cutoff value of ADC for detection of malignancy. P value less than 0.05 was considered as statistically significant.


  Results Top


This study was conducted on two patient groups: a case group consisting of 32 patients whose ages ranged between 33 and 78 years (mean ± SD age: 55.47 ± 12.38) and a control group consisting of 30 patients whose ages ranged between 38 and 80 years (mean ± SD age: 58 ± 10.82).

The clinical presentation of the study group was irregular bleeding in 15 (46.9%) cases, postmenopausal bleeding in 13 (40.6%) cases, and vaginal discharge in four (12.5%) cases. The control group patients presented with one or more of the following symptoms and signs: lower abdominal pain, increased abdominal size, infertility, menorrhagia, hematuria, and chronic constipation. The US examination of all the patients in the study group showed a cervical mass, whereas in the control group the cervix was normal.

Masses detected by MRI were mostly found circumferential (43.8%), posterior wall mass (28.1%), right lateral wall (15.6%), and lateral and anterior wall masses, being the least with 6.2% each.

The size of the detected cervical masses ranged between 2.4 and 11 cm (mean ± SD = 6.05 ± 2.23), and their signal intensities detected by MRI were isointense, hypointense, and hyperintense [Figure 1] and [Figure 2]. Hyperintense T2 signal was seen in 24 (75%) patients, whereas isointense T2 signal was recorded in eight (25%) patients. Hyperintense T2 signal was seen in 24 (75%) patients, whereas isointense T2 signal was recorded in eight (25%) patients. T1WI with contrast was performed for 31 patients: 20 masses showed heterogenous enhancement, nine masses showed homogenous enhancement, and two masses showed no enhancement.
Figure 1: MRI signal intensity in cervical carcinoma.

Click here to view
Figure 2: A case of cancer cervix stage IVb in different views and sequences of MRI (yellow arrow: left sacral ala BM infiltration, red arrow: intravesical soft tissue component, blue arrow: the cervical mass, green arrow: left external iliac LN).

Click here to view


All the detected cervical masses showed restricted DWI. High ADC value was seen in only one (3.2%) case which proved to be chronic cervicitis on histopathology; however, ADC was found to be low in the other 31 (96.8%) cases and proved to be cervical cancer by histopathology [Table 1].
Table 1: Correlation between dynamic contrast-enhanced MRI, diffusion-weighted imaging MRI, and pathological diagnosis

Click here to view


There was a statistically significant difference between the groups according to ADC value. The mean ADC values for malignant lesions was 0.81 × 10–3 mm2/s, whereas the mean ADC value in the control group was 1.64 × 10–3 mm2/s [Table 2].
Table 2: Comparison between the study and control groups according to the apparent diffusion coefficient values

Click here to view


The different ADC values elicited from the corresponding ADC maps were calculated, and a statistically significant difference was found between the malignant and benign lesions, with P value less than 0.001. We reported no significant difference in AD value between different histological subtypes of cervical cancer. Adenocarcinoma was diagnosed in four (12.5%) cases, squamous cell carcinoma in 27 (84.4%) cases, and one (3.1%) case was diagnosed as chronic cervicitis by histopathology [Table 3].
Table 3: Histopathology of cervical masse

Click here to view


ROC curve was used to define the best cutoff value of ADC (×10–3), which was 1.10, with sensitivity of 96.6%, specificity of 96.9%, positive predictive value of 96.6%, negative predictive value of 96.9%, and with diagnostic accuracy of 99.5%.


  Discussion Top


Cancer of the uterine cervix is the third most common cancer in women worldwide which is staged clinically according to International FIGO recommendations. The clinical presentations of women with cervical cancer varies to include abnormal vaginal bleeding, vaginal discomfort, malodorous discharge, and dysuria [7].

MRI is the preferred imaging modality owing to its precision in assessment of soft tissue and allowing better identification of stromal and parametrial invasion as compared with computed tomography. MRI shows with high accuracy the shape, volume, and direction of the primary lesion; local extent of the disease; and nodal status, aiding the clinician in treatment planning. Moreover, tumor response to chemoradiation is better evaluated with MRI [5]. MRI is a very helpful tool in staging of cervical cancer owing to its accuracy in detecting the exact extent of tumors because of its fine contrast resolution. MRI – as an advanced multiplanar multiparametric modality – can make staging and consequently management much easier, thus overweighing its high cost [8].

In this study, the clinical presentations of the patients were postmenopausal bleeding in 13 (40.6%) cases, irregular vaginal bleeding in 15 (46.9%) cases, and vaginal discharge with pain in four (12.5%) cases. In comparison, a study carried out by Dahiya et al. [9] showed the most common presenting complaints of women were unusual discharge from vagina (73.13%) followed by bleeding after menopause (55.10%) and pain in abdomen (44.77%). Pallor was present in nearly two-thirds (63.93%) of the study subjects.

In this study, all the patients were already provisionally diagnosed by US having a cervical mass. Cervical carcinoma was suspected on transvaginal US when detecting increased vascularity within an enlarged cervix with heterogeneous echogenicity, or when a hypoechoic or isoechoic mass lesion with undefined margins was seen, and this follows the concept adopted by Gaurilcikas et al. [10] that US examination should be the first-line imaging technique for the evaluation of early cervical cancer.

In this study, hypointense T1 signal was seen in 12 (37.5%) patients and isointense T1 signal in 20 (62.5%) patients. Hyperintense T2 signal was seen in 24 (75%) patients and isointense T2 signal in eight (25%) patients. This goes in line with what was described by Pannu et al. [11] that cervical cancer is mostly isointense in T1 compared with pelvic muscles and high signal in T2 relative to the low signal of the cervical stroma; hyperintensity is thought to be present regardless of the histological subtype.

Brocker et al. [12] mentioned in his study in 2011 that on contrast-enhanced T1WI, cervical cancer presents as a high signal relative to the low signal of the cervical stroma. Typically, cervical tumors enhance avidly in the early dynamic phase compared with the slight enhancement of the cervical epithelium and stroma, which may allow for the distinction of recurrent tumors from radiation fibrosis. In this study, T1WI with contrast was performed in 31 patients: 20 (64.5%) lesions showed heterogenous enhancement, nine (29%) lesions showed homogenous enhancement, and two (6.5%) lesions showed no enhancement.

The results of this study agreed with a study carried out by Kuang et al. [13] to determine diagnostic accuracy of DW MRI for differentiation of cervical cancer and benign cervical lesions in comparison with routine MRI and DCE-MRI. The study included 75 cervical carcinoma, 25 cervical leiomyoma, and 22 cervical polyps. In their results, DWI + routine MRI was significantly better than routine MRI and obtained high accuracy (0.95); the diagnostic performance was not significantly different between DWI + routine MRI and DCE-MRI.

Hoogendam et al. [14] stated that malignant cervical tissue ideally demonstrates restricted diffusion and hence reduced ADC values when compared with normal tissue. DWI and ADC maps allow differentiation of benign from malignant zones of cervix with high sensitivity and specificity.

In this study, the mean ADC values for malignant lesions were 0.81 × 10-3 mm2/s ± 0.14 SD, whereas the mean ADC value in the control group was 1.64 × 10–3 ± 0.24 mm2/s. Therefore, an ADC value of 1.10 × 10-3 mm2/s is the cutoff between benign and malignant cervical lesions, with 96.6% sensitivity and 96.9% specificity, with P value less than 0.001 (which was <0.05 and was considered a statistically significant result). A combination of increased extracellular tortuosity and the ratio of intracellular to extracellular water fraction may be the best biological explanation for the decreased ADCs in the cancer tissues [15].

In this study, the false-positive case was diagnosed histopathologically as chronic cervicitis. Cervicitis may appear as cervical mucosal thickening which may mimic early-stage cervical cancer on imaging (hypervascular on DCE-MRI reflecting increased blood supply owing to active inflammation, and DW-high owing to active inflammation with T2 shine-through effect) and should be differentiated from each other [16].

Another study was done by Nakamura et al. [17] on 80 patients with cervical cancer who underwent pelvic MRI within the 2–4 weeks before radical hysterectomy. In their results, the ROC curve identified an optimal ADCmax cutoff value of 1.122 × 10-3 mm2/s), ADCmean cutoff values of 0.852 × 10-3 mm2/s, and ADCmin cutoff values of 0.670 × 10-3 mm2/l. The patients categorized into lower ADCmean or ADCmin groups showed shorter disease-free survivals compared with the higher ADCmean or ADCmin, (P < 0.0001 or P = 0.0210, respectively). In their conclusion, the ADCmean of primary cervical cancer calculated by MRI could be an important factor.

Kundu et al. [18] concluded in their study that well-differentiated tumors had higher ADC values than poorly differentiated tumors (1.2 × 10–3 vs. 1.1 × 10-3 mm2/s; P = 0.01).

Similar results had been observed in another study by Liu et al. [19] which identified ADC of squamous carcinomas to be lower than adenocarcinomas, whereas another study by Payne et al. [20] reported no difference in ADC between different histological subtypes.

In this study, we found no significant difference in ADC between different histological subtypes. ADCmean value of SCC was 0.80 × 10-3 mm2/s and ADCmean value of adenocarcinoma was 0.89 × 10-3 mm2/s.

In this study, two masses did not show enhancement on the contrast study, as mass enhancement is linked to the degree of oxygenation of the tumor; the lower the oxygenation the less the enhancement, regardless of the histological subtype of the tumor [21].

Further studies with a larger number of patients are, however, needed to confirm these results.


  Conclusion Top


DWI is a potentially useful adjunct to conventional MRI for evaluation of cervical carcinoma, thus improving overall diagnostic accuracy, tumor staging, prediction of response to therapy, and treatment follow-up. Treatment options depend on morphologic assessment of the cervical cancer, with the critical management decisions based on the size of the mass and the presence of parametrial disease. ADC values may vary not only with different imaging parameters but also with different types of MRI systems.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Nicolet V, Carignan L, Bourdon F, Prosmanne O. MR imaging of cervical carcinoma: a practical staging approach. Radiographics 2000; 20:1539–1549.  Back to cited text no. 1
    
2.
Szklaruk J, Tamm EP, Choi H, Varavithya V. MR imaging of common and uncommon large pelvic masses. Radiographics 2003; 23:403–424.  Back to cited text no. 2
    
3.
Alfsen GC, Kristensen GB, Skovlund E, Pettersen EO, Abeler VM. Histologic subtype has minor importance for overall survival in patients with adenocarcinoma of the uterine cervix: a population-based study of prognostic factors in 505 patients with nonsquamous cell carcinomas of the cervix. Cancer 2001; 92:2471–2483.  Back to cited text no. 3
    
4.
Pecorelli S. Revised FIGO staging for carcinoma of the vulva, cervix, and endometrium. Int J Gynaecol Obstet 2009; 105:103–104.  Back to cited text no. 4
    
5.
Okamoto Y, Tanaka YO, Nishida M, Tsunoda H, Yoshikawa H, Itai Y. MR imaging of the uterine cervix: imaging-pathologic correlation. Radiographics 2003; 23:425–445.  Back to cited text no. 5
    
6.
Kinkel K. Pitfalls in staging uterine neoplasm with imaging: a review. Abdom Imaging 2006; 31:164.  Back to cited text no. 6
    
7.
Qaseem A, Humphrey LL, Harris R, Starkey M, Denberg TD. Screening pelvic examination in adult women: a clinical practice guideline from the American College of Physicians. Ann Intern Med 2014; 161:67–72.  Back to cited text no. 7
    
8.
Hauth E, Libera H, Kimmig R, Forsting M. MR Imaging of the pelvis in the diagnosis of the endometrium in breast cancer patients in tamoxifen therapy. RoFo 2006; 178:316–323.  Back to cited text no. 8
    
9.
Dahiya N, Bachani D, Acharya AS, Sharma DN, Gupta S, Haresh KP. Socio-demographic, reproductive and clinical profile of women diagnosed with advanced cervical cancer in a tertiary care institute of Delhi. J Obstet Gynaecol India 2017; 67:53–60.  Back to cited text no. 9
    
10.
Gaurilcikas A, Vaitkiene D, Cizauskas A, Inciura A, Svedas E, Maciuleviciene R, et al. Early-stage cervical cancer: agreement between ultrasound and histopathological findings with regard to tumor size and extent of local disease. Ultrasound Obstet Gynecol 2011; 38:707–715.  Back to cited text no. 10
    
11.
Pannu HK, Corl FM, Fishman EK. CT evaluation of cervical cancer: spectrum of disease. Radiographics 2001; 21:1155–1168.  Back to cited text no. 11
    
12.
Brocker KA, Alt CD, Eichbaum M, Sohn C, Kauczor HU, Hallscheidt P. Imaging of female pelvic malignancies regarding MRI, CT, and PET/CT. Strahlenther Onkol 2011; 187:611.  Back to cited text no. 12
    
13.
Kuang F, Yan Z, Li H, Feng H. Diagnostic accuracy of diffusion weighted MRI for differentiation of cervical cancer and benign cervical lesions at 3.0 T: Comparison with routine MRI and dynamic contrast enhanced MRI. J Magn Reson Imaging 2015; 42:1094–1099.  Back to cited text no. 13
    
14.
Hoogendam JP, Klerkx WM, de Kort GA, Bipat S, Zweemer RP, Sie-Go DM, et al. The influence of the b value combination on apparent diffusion coefficient based differentiation between malignant and benign tissue in cervical cancer. J Magn Reson Imaging 2010; 32:376–382.  Back to cited text no. 14
    
15.
Padhani AR, Liu G, Mu-Koh D, Chenevert TL, Thoeny HC, Takahara T, et al. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 2009; 11:102–125.  Back to cited text no. 15
    
16.
Whittaker CS, Coady A, Culver L, Rustin G, Padwick M, Padhani AR. Diffusion-weighted MR imaging of female pelvic tumors: a pictorial review. Radiographics 2009; 29:759–774.  Back to cited text no. 16
    
17.
Nakamura K, Joja I, Nagasaka T, Fukushima C, Kusumoto T, Seki N, et al. The mean apparent diffusion coefficient value (ADCmean) on primary cervical cancer is a predictive marker for disease recurrence. Gynecol Oncol 2012; 127:478–483.  Back to cited text no. 17
    
18.
Kundu S, Chopra S, Verma A, Mahantshetty U, Engineer R, Shrivastava SK. Functional magnetic resonance imaging in cervical cancer: current evidence and future directions. J Cancer Res Ther 2012; 8:11.  Back to cited text no. 18
    
19.
Liu Y, Bai R, Sun H, Liu H, Wang D. Diffusion-weighted magnetic resonance imaging of uterine cervical cancer. J Comput Assist Tomogr 2009; 33:858–862.  Back to cited text no. 19
    
20.
Payne GS, Schmidt M, Morgan VA, Giles S, Bridges J, Ind T. Evaluation of magnetic resonance diffusion and spectroscopy measurements as predictive biomarkers in stage 1 cervical cancer. Gynecol Oncol 2010; 116:246–252.  Back to cited text no. 20
    
21.
Hameeduddin A, Sahdev A. Diffusion-weighted imaging and dynamic contrast-enhanced MRI in assessing response and recurrent disease in gynaecological malignancies. Cancer Imaging 2015;15:3.  Back to cited text no. 21
    


    Figures

  [Figure 1], [Figure 2]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Patients and methods
Results
Discussion
Conclusion
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed98    
    Printed8    
    Emailed0    
    PDF Downloaded19    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]