Nghiên cứu giá trị của chụp cộng hưởng từ trong chẩn đoán ung thư buồng trứng tt tiếng anh
MINISTRY OF EDUCATION
Hanoi medical university
dOAN TIEN LUU
STUDY THE VALUE OF MR IMAGING IN OVARIAN CANCER DIAGNOSIS Specilised : Radiology Code : 62720166
Summarise of thesis of Philosophy doctor
Hanoi - 2019
Thesis made in hannoi medical university
THESIS SUPERVISORS: 1. Ass Prof. BUI VAN LENH 2. Ass Prof. VU BA QUYET
Ass Prof. Thai Khac Chau
Ass Prof. Nguyen Dinh Tuan
Ass Prof. Lam Khanh
Thesis will be protected in congress university level of Hanoi Medical University 2019.
Thesis will be found in: - National library - Library of Hanoi medical university
Researchs publised concerning to the thesis 1.
Đoàn Tiến Lưu, Bùi Văn Lệnh, Vũ Bá Quyết (2019), “Nghiên cứu áp dụng thang điểm cộng hưởng từ trong chẩn đoán khả năng ác tính của u buồng trứng”, Tạp chí Y học thực hành, số tháng 1 năm 2019 (1089), trang 86 - 90.
Đoàn Tiến Lưu, Bùi Văn Lệnh, Vũ Bá Quyết (2019), “Nghiên cứu giá trị của xung cộng hưởng từ động học sau tiêm thuốc đối quang từ trong chẩn đoán phân biệt u buồng trứng ác tính với u buồng trứng lành
tính”, Tạp chí Y học thực hành, số tháng 3 năm 2019 (1098), trang 23 – 27.
4 INTRODUCTION Ovarian cancer is the third most common cancer, after cervical cancer and endometrial cancer, but is the leading cause of death among female genital cancers. The disease has a poor prognosis because the majority of cases are detected late. Most cases have pelvic invasion and peritoneal metastases when detected. To change the prognosis, early detection and proper treatment should be made. Recently, with the development of new magnetic resonance pulse chains (CHT), it has faster shooting time, better resolution of images, analysis of many characteristics of tumor tissue, differentiating cancer tissue from benign tissue. At the same time, it is easier to surveyed the entire abdominal cavity to detect peritoneal metastases, lymph node metastasis. Magnetic resonance (MR) imaging is increasingly showing advantages in definitive diagnosis and diagnosis of ovarian cancer stage. There have been studies of the value of MR imaging in the diagnosis of ovarian cancer in developed countries. However, in Vietnam, there are no studies, especially studies on MR machines with advanced software for diagnosing ovarian cancer. So we conducted a research on the topic "Study the value of MR imaging in diagnosing ovarian cancers" with the following three research objectives: 1. Describe the MR imaging characteristics of ovarian cancer. 2. Evaluate the value of MR imaging in the differential diagnosis of ovarian cancer with benign ovarian tumors. 3. Evaluate the value of MR imaging in the diagnosis of ovarian cancer stage. * Urgency of the project: Finding out a medical imaging modality which has hight value in diagnosis of ovarian cancers and staging ovarian cancers. MR imaging with 1,5T machines, many new sequences, has hight potential in accurately differentiating between ovarian cancers and benign ovarian tumors, in staging ovarian cancers.
5 * New contributions of the thesis: This thesis is the first Vietnamese research of values of MR imaging in diagnosis of ovarian cancers. The study outcomes showed efficacy of MR imaging in diffentiating between ovarian cancers and benign ovarian tumors, and in staging ovarian cancer. Ovarian cancer’s tissues are always restricted diffusion (hight intensity on DW-b1000). Cutt-off of ADC value ≤ 1,26x10-3 mm2/s has moderate value in diffentiating between ovarian cancers and benign ovarian tumors. Ovarian tumor’s tissue with enhanced curve type II or type III is the most important characteristics in diagnosis of ovarian cancers. Diffusion imaging (DW-b1000) has hight sensitive in discovering peritoneal metastases. THESIS OUTLINE This thesis covers 131 pages, including: preamle (2 pages), chapter 1: The Overview (37 pages), chapter 2: Material and method (19 pages), chapter 3: Study outcomes (28 pages), chapter 4: Discussion (42 pages), Conclusions (2 pages), Recommendation (1 page). The thesis consists of 35 tables, 3 charts, 3 diagram, 29 figures. There are 105 references, of which 5 in Vietnamese and 100 in English.
CHAPTER 1: OVERVIEW 1.1. GENERAL ON OVARIAN CANCERS 1.1.1. Epidemiology of ovarian cancers Ovarian cancer represents the sixth most commonly diagnosed cancer among women in the world, and causes more deaths per year than any other cancer of the female reproductive system. it accounts for about 4% of all cancers in women. It is the third common after cervical cancer and endometrial cancer.
6 An estimated 1 in 70 women in the United States will develop ovarian cancer in their lifetime. On a worldwide basis, an estimated 204,000 new cases are diagnosed and 125,000 women die of ovarian cancer annually. In 2007, approximately 22,430 new cases of ovarian cancer will be diagnosed and 15,280 ovarian cancer-related deaths are expected in the United States. Mortality is high because women typically present with late-stage disease when the overall 5-year relative survival rate is 45%. Thus, the public health burden is significant. Ovarian cancer affects women in the age 20 - 80 years and older more frequently than younger women. More than 80% of all ovarian cancers occur in women in the age more than 40 years old. 1.1.2. Hispathology of ovarian cancers - Over 90% of ovarian neoplasms arise from the epithelial surface of the ovary, the rest from germ cells or stromal cells. The epithelial neoplasms are classified as serous (30–70%), endometrioid (10–20%), mucinous (5–20%), clear cell (3–10%), and undifferentiated (1%). - 5% - 10% of ovarian cancers are of germ cell origin, included dysgerminoma, endodermal sinus tumor, embryonal carcinoma, choriocarcinoma, malignant teratoma. - Sex cord-stromal are rare, <5% of ovarian cancers, included malignant granulosa cell tumor, Sertoli-Leydig cell tumor, fibrosarcoma. 1.1.3. Ovarian cancer staging Stage I: Tumor confined to ovaries - IA Tumor limited to 1 ovary, capsule intact, no tumor on surface, negative washings. - IB Tumor involves both ovaries otherwise like IA. - IC Tumor limited to 1 or both ovaries IC1 Surgical spill IC2 Capsule rupture before surgery or tumor on ovarian surface. IC3 Malignant cells in the ascites or peritoneal washings.
7 Stage II: Tumor involves 1 or both ovaries with pelvic extension (below the pelvic brim) or primary peritoneal cancer - IIA Extension and/or implant on uterus and/or Fallopian tubes - IIB Extension to other pelvic intraperitoneal tissues Stage III: Tumor involves 1 or both ovaries with cytologically or histologically confirmed spread to the peritoneum outside the pelvis and/or metastasis to the retroperitoneal lymph nodes - IIIA ( Positive retroperitoneal lymph nodes and /or microscopic metastasis beyond the pelvis) IIIA1 Positive retroperitoneal lymph nodes only IIIA1(i) Metastasis ≤ 10 mm IIIA1(ii) Metastasis > 10 mm IIIA2 Microscopic, extrapelvic (above the brim) peritoneal involvement ± positive retroperitoneal lymph nodes - IIIB Macroscopic, extrapelvic, peritoneal metastasis ≤ 2 cm ± positive retroperitoneal lymph nodes. Includes extension to capsule of liver/spleen. - IIIC Macroscopic, extrapelvic, peritoneal metastasis > 2 cm ± positive retroperitoneal lymph nodes. Includes extension to capsule of liver/spleen. Stage IV: Distant metastasis excluding peritoneal metastasis - IVA Pleural effusion with positive cytology - IVB Hepatic and/or splenic parenchymal metastasis, metastasis to extraabdominal organs (including inguinal lymph nodes and lymph nodes outside of the abdominal cavity) 1.2. MR PROTOCOL MR imaging is performed with a closed-configuration superconducting 1.5-T system (Signa HDxT; GE Healthcare). MR imaging is performed with the patient lying in the supine position (feet first). MR sequences:
Localizer sequence in the three spatial planes; Axial T2-weighted single-shot fast spin-echo (SSFSE) sequence, section thickness 6 mm, interslice gap 0.6 mm, used as second localiser to identify the longitudinal axis of the uterus in the case of laterally deviated uterus. - Sagittal T2-weighted fast spin-echo (FSE) sequence parallel to the longitudinal axis of the uterus (identified on the previous SSFSE sequence), section thickness 4 mm, interslice gap 1 mm. Oblique coronal T2-weighted FSE sequence parallel to the longitudinal axis of the uterus, section thickness 4 mm, interslice gap 1 mm. - Oblique axial T2-weighted FSE sequence perpendicular to the longitudinal axis of the uterus, section thickness 4 mm, interslice gap 1 mm. - Axial oblique fat suppressed T2-weighted FSE sequence, section thickness 4 mm; interslice gap 1 mm. - Axial T1-weighted gradient-echo (GRE) sequence in-out (chemicalshift imaging), section thickness 6 mm; interslice gap 0,6 mm. - Axial DWI SE EPI (TR/TE 3000/74,1; flip angle 90°; section thickness 5 mm; interslice gap 1 mm. - Axial oblique T1-weighted 3D gradient-echo liver acquisition with volume acquisition (LAVA) sequence with fat suppression, section thickness 3.4 mm; overlap locations −1.7 mm. After i.v. administration of 0.1 mmol/kg paramagnetic contrast agent (Dotarem) at a flow rate of 2 ml/s, followed by 20 ml of saline solution at the same flow rate, the following sequences are acquired: - Dynamic axial T1-weighted 3D gradient-echo LAVA with fat suppression, section thickness 3.4 mm, overlap locations −1.7 mm, 10 sequences acquired in 6 minutes after contrast administration. CHAPTER 2: OBJECTS AND METHOD
9 2.1. Materials Objects included 184 patients with ovarian tumors (93 patients with ovarian cancers and 91 patients with benign ovarian tumors). All the patients got pelvis and abdominal MR imaging to diagnose ovarian cancers at Radiology department of Hanoi University Hospital, operated at Oncology department of Hanoi University Hospital and National hospital of obstetrics and gynecology, from November 2013 to August 2017. 2.2. Study methods Prospective, descriptive cross-sectional study. 2.2.1. Study equipments - MR system 1.5T Signa X (GE Healthcare). - Paramagnetic contrast agent (Dotarem) 0,5mmol/1ml. 2.2.2. Study design - Select eligible patients. - Various MR criterias were evaluated on the basis of several previously published terms: + A purely cystic lesion was defined by the absence of solid tissue and the absence of internal enhancement after injection and corresponded to a unilocular cyst or hydrosalpinx, both of which have low T1-weighted and high T2-weighted MR signal intensities. + A purely endometriotic mass was defined as a lesion that displayed high T1- weighted signal intensity that was greater than or equal to that of subcutaneous fat, shading on T2-weighted MR images, and no solid tissue. + A purely fatty mass was defined as a lesion that displayed high T1weighted signal intensity that decreased after fat saturation and that displayed no solid tissue. + Readers also recorded enhancement of the cyst wall, bi- or multilocularity, and the presence of thickened regular septa or grouped septa.
10 + The presence of a solid tissue and its morphology (solid portion, vegetation, thickened irregular septa) were also evaluated. Then, T2weighted signal intensity within the solid tissue (low or intermediate compared with that of the outer myometrium) and b = 1000 sec/mm2– weighted signal intensity within the solid tissue (high b = 1000 sec/mm2– weighted signal intensity compared with that of serous fluid [urine in the bladder or cerebrospinal fluid]) were analyzed. As previously demonstrated, we described lesions that displayed both low T2 and b = 1000 sec/mm2–weighted signal intensity within the solid tissue. + Finally, readers analyzed the perfusion-weighted images at a standard workstation by using the breast or prostate perfusion tool and selecting two regions of interest—one in the external myometrium and one in the most enhancing part of any solid tissue. We classified the enhancement of the solid tissue by using a previously published time– signal intensity curve classification. A gradual increase in the signal intensity of the solid tissue, without a well-defined “shoulder,” was defined as curve type 1. A moderate initial increase in the signal intensity of solid tissue relative to that of myometrium, followed by a plateau, was defined as curve type 2. An initial increase in the signal intensity of solid tissue that was steeper than that of myometrium was defined as curve type 3. + The presence of free fluid in peritoneal cavity. + Peritoneal implants was also noted: Nodular thickening of the peritoneum that is restricted diffusion (hight intensisty on DW-b1000) and enhances after gadolinium chelate injection. + Pelvis invasion: Normally, there is a hight intensity interface on T2W between ovarian tumors and rectum, uterus, blader and pelvis wall. When we can not see this interface or the interface is irregular or retracted, it is said that there is pelvis invasion. + Metastases lymph nodes: Oval or round in shape, transverse diameter over 8mm, hyperintensity on DW-b1000, enhances after gadolinium chelate injection, beside to pelvis vessels and aorta, vena cava and superior mesenteric vessels.
11 + Diagnosis of malignant ovarian tumors based on MR criterias, comparing MR imaging diagnosis with surgery diagnosis to asses the values of MR imaging in diagnosis malignant ovarian tumors. + Staging ovarian cancers based on MR imaging diagnosis of peritoneal implants, metastases lymph nodes, pelvis invasion. + Calculating the malignancy ratio of tumors according to MR characteristics, following malignancy ratio to rank ovarian tumors in Thomassin's ADNEX MR scoring system, the ADNEX MR scoring system has 5 scores (score 1: no tumors; score 2: benign tumors; score 3: tumors with low malignancy ratio; score 4: tumors with high malignancy ratio; score 5: almost certainly malignant). - Based on MR imaging’s diagnosis of invasion of malignant ovarian tumors, diagnosis of peritoneal metastases, visceral metastases, lymph node metastases, to diagnose of pre-operative disease stage. Compare the results of MR imaging’s diagnosis of ovarian cancer stage with staging ovarian cancer after surgery and hispathologic results. Calculate the accuracy of MR imaging in diagnosing ovarian cancer stage. CHAPTER 3: RESEARCH OUTCOMES 3.1. General characteristics of the research object 184 cases of ovarian tumors in the study, there were 93 malignant cases (50.5%), 91 cases of benign tumors (49.5%). Malignant epithelial neoplasms account for the majority (84.6%), germ cell malignancy 8.3%, and genital cord cell cancers 7.1%. Patients with ovarian cancer had an average age of 49.5 ± 14.8 years, 72.1% at age 40 - 69 years. Clinical signs of malignant ovarian tumors were nonspecific, each of which showed signs of <50% of cases, but gynecological examination palpable the masses in 88.7% of cases.
12 Level of serum CA15 has the sensitivity of 94.9% with stage III, IV ovarian cancers, 78.9% with stage II ovarian cancers, 57.1% with stage I ovarian cancers. 3.2. MR imaging’s characteristics of ovarian cancer Malignant ovarian tumors have an average size of 93.9 ± 37.8mm. 93.6% cases of ovarian cancers had complex structure (tissue and cystic structure), 3.2% completed tissue structure, 3.2% purely cystic structure. Malignant ovarian tumors had serous fluid (increased signal on T2W, decreased signal on T1W) in 84.4% of cases; mosaic fluid, increased signal on T1W and T2W compartments and decreased signal on T1W, increased signal on T2W compartments (mucus, protein-rich fluid) in 10% of cases; chronic bleeding fluid, increased signal on T1W, T1W fat-saturation, decreased T2W signal in 5,6% of cases. 100% of malignant tumors’ tissues increased signal on DW-b1000, 94.4% of soft tissues had time–signal intensity curve type 2 or type 3, 5.6% of soft tissues had time–signal intensity curve type 1. 3.3. The value of MR in differential diagnosis of malignant ovarian tumors with benign ovarian tumors 3.3.1. Analysis of MR characteristics to diagnose of malignant ovarian tumors
13 Table 3.1: Multivariate analysis of MR characteristics for diagnosing malignant ovarian tumors Malignant Malignant Benign characteristics
When analyzing univariate, the MR characteristics of ovarian tumors, size of tumor ≥ 80mm, multilocularity, wall thickness ≥ 3mm, vegetations, tissues increase signal on DW-b1000, tissue’s ADC value ≤
14 1,26x10-3 mm2 / s, enhancement with curve type 2 or type 3, peritoneal metastases, peritoneal cavity’s fluid, all have value in diagnosis of malignant ovarian tumors.The malignant ratio of tumors with one of the above characteristics is higher than the malignant ratio of tumors with no corresponding characteristics, the difference is statistically significant p <0.05, malignancy odd ratio OR > 1. However, when analyzing multi-variable Regression Multinomial Logistic, there are only two characteristics, contrast-enhanced tissue with curve type 2 or 3 and peritoneal metastases, that are valuable for diagnosis of malignant tumor, malignancy aOR very high, dynamic range of odds ratio (CI 95%) always > 1, with p <0.001, other characteristics have no value to diagnose malignant ovarian tumors, aOR malignancy rate of these characteristics <1 or dynamic range (CI 95%) of aOR with oscillation <1, with p> 0.05. This is explained by the MR characteristics after multivariate analysis with p> 0.05, the ratio of aOR <1, are all characteristics when univariate analysis have low sensitivity (19.4% - 77.4%), specificity is not high (48.4% - 92.3%), low accuracy (55.4% - 71.2%) , the negative predictive value and the positive predictive value are also not high. On the contrary, contrast-enhanced tissue with curve type 2 or 3 is the MR characteristics with high diagnostic value, high sensitivity 91.4%, high specificity 90.1%, when tumors has contrast-enhanced tissue with curve type 2 or 3, they will often include many other malignant diagnostic characteristics. Peritoneal metastases is MR characteristics with low sensitivity but high specificity (reaches 100%), when we observe peritoneal metastases on MR images the tumors are almost certainly malignant.
15 The results of our research are similar to the results of some other studies. Thomassin et al. (2013) researched to construct of MR scores in differential diagnosis of ovarian malignant tumors to ovarian benign tumors, multivariate analysis also identified only two characteristics of malignant diagnosis had high value in diagnosis of ovarian malignant tumors that are contrast-enhanced tissue with curve type 2 or 3 and peritoneal metastases, other MR characteristic are not valuable when analyzing multivariate. Other tudies of applying Adnex MR score in the diagnosis of ovarian cancers, such as Pereira’s study (2018), Sadowski's study (2018), both studies had results which are similar to our research result, only two characteristics, contrast-enhanced tissue with curve type 2 or 3 and peritoneal metastases, are applied into malignant diagnostic criteria.
Figure 3.1: Cancerous tissue with contrast-enhanced curve type 3/Left ovarian mucinous adenocarcinoma. Cancerous tissue’s curve is purple, uterus’curve is green, the purle one if steeper than the green one . Patient: Vu Hong Ch., 44 years old, patient code: 178/13.
16 3.3.2. Analysis of MR characteristics for diagnosis of benign ovarian tumors Table 3.2: MR characteristics to diagnose benign ovarian tumors Benign MR characteristics
Cyst with thick wall, without tissue
Cyst with thin wall, without tissue
Endometriotic cyst, without tissue
Fatty cyst, without contrastenhanced tissue
Tissue’s low intensity on DW
Tissue with curve type 1
Benign ovarian cysts often do not have cell proliferation inside so they have MR images of pure cysts without tissue, whereas ovarian malignant cysts have malignant cell proliferation inside, often have MR images of mix cysts (solid portions inside the cysts). Therefore, ovarian cysts without tissue are more likely to be benign tumors. Thin-walled cysts are common, are benign serous cysts, benign mucous cysts, cysts of ovary, paraovarian cyst, peritoneal inclusion cyst, these benign cysts are without cell proliferation in the cyst, so they have thin. Endometriotic cysts are the most common benign cysts in the ovary, these cyst are high intensity on T1W and T1W-fatsaturate images, low signal on T2W images (chronic bleeding), thick wall or thin wall, but no solid portion inside. In some cases of endometrial carcinoma, clear cell carcinoma also has chronic internal bleeding, so they are high intensity on T1W and
17 T1W fat-saturation images, low signal on T2W images, but these cancers often have solid portions, the solid portions are strongly contrastenhanced. Pure fatty cystic tumors (high signal on T1W, low signal on T1W fat-saturation), without contrast-enhanced tissue inside, are benign teratomas or dermoid cysts. In cases of teratomas with contrast-enhanced tissue inside may be benign or malignant teratomas, not absolutely benign teratoma. The tissue, which is low signal on T2W and DW, is benign, rich in fiber, poor in cells, not restricted on DW image, so the tumors with this tissue are also usually benign. The tissue, with contrast-enhanced curve type 1, is hypovascular, so this tissue also has high benign ratio, low malignancy ratio. Therefore, in our study, thin-walled cyst, endometriotic cyst, fatty cyst, tissue with low signal on DW were definitely benign with malignancy ratio of 0%. Thick-walled cysts, tissue portion with contrast-enhanced curve type 1 are likely benign, with low malignant ratio, 5.3% and 15.2, respectively. Our research results are similar to other studies. The study of Thomassin (2013), also identified merely thin-walled cysts, endometriotic cysts, simple cyst, tumors with tissue of low signal on DW have malignant ratio of 0%, thick-walled cysts and tissue portion with contrast-enhanced curve type 1 have low malignant ratios of 4.3 - 4.5%. Pereira's study (2018), thin-walled cysts, endometriotic cysts, simple fatty cyst, tumors with tissue of low signal on DW have malignant ratio of 0%, thick-walled cysts and tissue portion with contrast-enhanced curve type 1 have low malignant ratios of 5.1%.
18 Table 3.3: Ovarian malignancy ratio according to the Adnex MR scores MR scores
Score 1 Score 2
Scores 3 Scores 4 5 Score
Low possibility of malignancy High possibility of malignancy almost certainly malignant
MR characteristics or ovarian tumors No ovarian masse Thin-walled cysts Endometriotic cysts Fatty cysts Tissues are low intensity on T2W, DW images Thick-walled cysts Solid portions with curve type 1 Solid portions with curve type 2
Solid portions with curve type 3 Peritoneal metastases
Score 1 is without ovarian masses, in our study all patients have tumors so there is no case of score 1. Score 2 is definitely benign, malignancy ratio is 0%. Score 3 is ovarian tumors with low possibility of malignancy, malignant ratio is 13.0%. Score 4 is tumors with high malignant possibility, malignant ratio is 82.2%. Score 5 is almost certainly malignant, malignancy ratio is 100%. Table 3.4: Value of magnetic resonance in the differential diagnosis of malignant ovarian tumors with benign ovarian tumors MR’diagnosis
Kết quả mô bệnh học Benign tumors Malignant tumors
Malignant tumors 87 7 94 (scores 4,5) Benign tumors 6 84 90 (scores 2,3) Total 93 91 184 We diagnose malignant ovarian tumors if the tumors have solid portions with contrast-enhanced curve type 2,3 or peritoneal (Adnex MR score of 4 or 5).
19 The results of our study showed that MR has high value in the diagnosis of malignant ovarian tumors, with high sensitivity of 93.5%, high specificity of 92.3%, high positive predictive value 92.6%, the negative predictive value is 93.3%, the high accuracy is 92.9%. Studies of Thomassin (2013) and Pereira (2018) also diagnose malignant tumors if the tumors have a Adnex MR score of 4 or 5, the results of these studies are similar to our results, MR is highly valuable in diagnosing malignant ovarian tumors. Research result of Thomassin has 93.5% sensitivity, 96.6% specificity, 96.0% accuracy. Pereira's research result (2018) has 94.9% sensitivity, 97.5% specificity, 96.6% accuracy. 3.4. The value of magnetic resonance in the diagnosis of ovarian cancer stage 3.4.1. The value of magnetic resonance in diagnosis of pelvic invasion We diagnose ovarian cancer’s invasion to the uterine, rectal, bladder invasion if we find to lost the high signal on T2W planes, which separate the tumor and the wall of the uterus, bladder wall, rectum wall, or these planes are irregular or shrinkage. We diagnose ovarian cancer’s invasion to pelvic wall if we find to lost the high signal on T2W plane between tumors and muscles, bones of the pelvic wall or tumor’tissue surrounds more than half of the perineal pelvic vassel’s perimeter. These characteristics are the standards applied in some studies of the values of MR in diagnosing ovarian cancer stage. When these standards were used to diagnose pelvic invasion of ovarian cancer, we found that MR has low sensitive 56.9%, low specificity 77.1%, quite high false positive rate 19.5%. The results of our study are similar to other research results, Forstner et al. (1995) studied the value of MR to diagnose ability of radical surgery for 50 cases of invasive ovarian cancer. MR diagnosis of pelvic invasion has low sensitivity 60%, not very high positive predictive value 69%, high false positives rate 31%. Kurst et al. (1999), investigating the value of MR in the diagnosis of ovarian cancer stage, MR diagnosis of pelvic invasion with low sensitivity of 58.3%, positive predictive value of 71.4% , high false positive rate is 28.6%. In many cases, the fat layer
20 of pelvic wall is thick, so when the tumor has already invaded into pelvic wall but not yet invaded all the thickness of the fat layer, so on MR images we still see the fat layer between tumors and muscles and bones. The plane of separation between the tumor and the rectum wall, bladder, uterus and ovary is the fat and serosa layer of the organs, in some cases the invasion does not occupy all the thickness of these layers, so it is still still observed on MR images. These cases lead to false negative diagnosis, so MR is not highly sensitive. In contrast, in some cases, the fat layer is very thin, so when the tumor is close to the muscle, the bone we can not see this layer but in fact that there is not invasion. At the same time, in many cases the serous fat layer of the organs in the pelvis is very thin, although the tumor has not invaded the pelvic organs but with the resolution of 6mm thickness T2W images we still can not observe the plane separating between the tumor and the organs. These cases lead to MR diagnosis with significant false positive rate, low specificity.
Figure 3.2: Images of pelvic invasion. Ovarian serous adenocarcinoma invades the uterus and rectum, lost the fat layer between the tumor and the uterine wall (white arrow), between the tumor and the rectum wall (yellow arrow), on T2W image horizontal plane (left), vertical vertical plane (right image). Patients: Pham Thi T., patient’code: 405/31. 4.4.2. The value of magnetic resonance in large lymph nodes detection
21 According to the study of Takeshima et al. (2005), most metastatic lymph nodes of the ovarian cancers are beside the abdominal aorta, and next to the pelvic arteries, the rate of ovarian cancer with metastatic lymph nodes accounts for the proportion 13-60% of cases, including many cases of metastatic lymph nodes but small in size. However, according to research by Maggioni et al. (2006), comparing the group of patients with surgical ovarian cancer, having systemic lymph node surgery with the group of ovarian cancer patients who had surgery but not systemic lymph node surgery, only large lymph nodes are taken as a attempt of maximal cutting of tumor, the study results show that there is no difference in the overall life time of these two groups of patients. In our study, surgeons only performed lymph node removal when there was a large size lymph node, so we only studied the role of MR in detecting enlarged lymph nodes, the horizontal diameter of lymph nodes are 8mm or more. The detection of enlarged lymph nodes before surgery helps surgeons to find large lymph nodes during surgery to remove them. There were 10 patients in our study, that surgeons discovered and removed large lymph nodes, MR detected large lym nodes in 8 cases, sensitivity reached 80%, specificity was 97.6%. There were 2 cases who had enlarged lymph nodes but MR did not detect enlarged lymph nodes. At the same time, there were two cases that MR diagnosed with enlarged lymph nodes but surgeons did not find in surgery, the rate of false positive was 20%. The sensitivity of MR in detection of lymphadenopathy in our study was lower than some other research results. Research by Kim J.K et al (2008), 125 cases of cervical cancer, 30 metastatic lymph nodes size ≥8mm, MR detected these nodes with 87% sensitivity. Harisinghani et al. (2003), studied the value of MR in
22 detecting metastatic lymph nodes size ≥8mm in patients with prostate cancer, MR has high sensitivity of 91%. In our study, two false positive cases are due to the misdiagnosis of peritoneal metastatic nodules in pelvic wall, near the pelvic arteries as lymph nodes. In contrast, two false negative cases we misdiagnosed lymph nodes as peritoneal metastatic nodules. Kim J.K's research subjects were cervical cancer cases, Harisinghani's research subjects were prostate cancers. These types of cancers often have metastatic lymph nodes, but peritoneal metastasis is less common than ovarian cancer, so it is seldom confused between pelvic lymph nodes and peritoneal metastases of pelvic wall. So the sensitivity and specificity of these studies are higher than our study. 3.4.3. The value of MR in diagnosis of visible peritoneal metastasis Peritoneal metastatic lesions are nodules in the parietal peritoneum (peritoneum of the diaphragm, colon recess, abdominal wall, pelvic wall), visceral peritoneum (on the surface of the liver, spleen, intestinal wall), greater omentum, mesentery. Peritoneal metastatic lesions are characterized by restricted diffusion on DWI, the signal of lesions is higher than the signals of abdominal organs on DW-b1000 image, low signal compared to peritoneal fat on T1W and T2W images, enhanced on T1W fatsat after contrast injection. Diffusion weighted (DW) is the basic sequence to detect peritoneal metastases, recent studies on the value of MR in the diagnosis of peritoneal metastases are based on DW, diagnosis of peritoneal metastasis based on high signal characteristics on DW with high b values (b800, b1000, b1200). Therefore, in the study, we diagnosed peritoneal metastasis based on high signal of the lesions on DW-b1000. There were 33 cases which had visible peritoneal metastases, MR detected visible peritoneal metastasis with relatively high sensitivity of 87.9%, accuracy of 95.6%.
23 The results of our research are similar to the results of other researchs. Low R. et al. (2009), study theo value of DW to diagnose visible peritoneal metastasis, the sensitivity of MR reaches 90%, accuracy of 91%. Tempany et al. (2000), studying comparing the value of diagnostic methods in ovarian cancer staging, MR has higher value than CT scanner and ultrasound, MR's sensitivity in diagnosis of visible peritoneum reaches 95%.
Figure 3.3: Images of metastases of visceral peritoneum and parietal peritoneum. Peritoneal metastases have high signal on DW-b1000. Metastatic nodules of the liver surface (yellow arrows), metastatic nodules of the peritoneum of abdominal wall (white arrows), metastasis of greater omentum (red arrow). Patient: Do Thi N., patient’code: 195/16. Our study also found that MR sensitivity depends on the size of peritoneal metastases. There were 5 cases of peritoneal metastasis at microscopic level that were not clearly observed by eye when surgery, MR did not detect any cases, the sensitivity was 0%; 17 cases of peritoneal metastasis, observed in surgery with size ≤10mm, MR detected 13/17 cases, sensitivity reached 76.5%; 16 cases of peritoneal metastasis with size > 10mm, MR detected 16/16 cases, sensitivity of 100%.
24 MR sequences investigated all abdominals with slice thickness of 6mm, which had certain resolution, and there were some image noises (noise due to movement of the respiratory, peristalsis). So small lesions, which may have the signal combined with the surrounding structure, will be difficult to distinguish from the surrounding structures, so the sensitivity of MR will be lower. In contrast, large-sized lesions are easier to observe, the signal distinction is clearer, so MR has higher sensitivity with larger lesions. 3.4.4. The value of MR in the diagnosis of ovarian cancer stage Table 3.5: MR's value in ovarian cancer staging Staging by MR
Staging by surgery Stage I
MR diagnoses the stage of ovarian cancer based on diagnosis of pelvic invasion, diagnosis of lymphadenopathy, diagnosis of peritoneal metastases. The results of our study, MR diagnosed each stage with low accuracy of 68.8%. The reason that MR diagnosed pelvic invasion with low accuracy of 64.5%, MR could not diagnose microscopic peritoneal metastasis, MR only had high accuracy of 95.6% with macroscopic peritoneal metastasis. Other research results in the world, MR diagnoses each stage with low accuracy, fluctuating 53% - 88%, our research results are also in this range. Kurtz et al. (1999) compared MR with other diagnostic imaging methods in diagnosing stages of ovarian cancer, MR had an accuracy of
25 72.9%. Forstner et al. (2004) studied the value of imaging diagnostic methods in diagnosing stages of ovarian cancer, MR had accuracy of 78%. The authors all have identified that 1.5 Tesla MR machine and multi-sequence CT scanner nearly equal value in diagnosis of ovarian cancer staging, but MR is a method that requires more complex techniques, to convey the entire abdomen will take longer time. Highermagnetic MR machines (3 Tesla) with new hardware and software for better image processing can improve these problems, with one sequence can convey the entire abdomen, faster speed, DW and new other higher resolution sequences enable to increase accuracy of MR in the diagnosis of peritoneal metastases and metastatic lymph nodes. Table 3.6: MR differential diagnosis of stage I, II with stage III, IV MR diagnosis Stage I, II Stage III, IV Total
Surgery diagnosis Stage I, II Stage III, IV 54 9 0 30 54 39
In our study, MR diagnosis of each stage has not high accuracy, but the differential diagnosis late stages (stage III and IV) with the earlier stage (phase I, II), MR has a high accuracy of 90.3%. Kurtz's study and Forstner's study also identified that MR had highvalue in distinguishing ovarian cancer stage I and II from stage III, IV. Kurtz et al. (1999), MR differentially diagnosed the early stages to the late stages with accuracy of 90%. Forstner et al. (2004), MR differential diagnosis of early-stages with late stages with accuracy of 95%. The differential diagnosis of the late stages with the early stages helps to get prognosis before treatment.
CONCLUSION 1. MR imaging’s characteristics of ovarian cancer Malignant ovarian tumors have an average size of 93.9 ± 37.8mm.