Understanding the Global Prevalence and Impact of Ovarian Cancer

Introduction

Currently, there is an alarming prevalence and incidence of ovarian cancer globally, making statistics dissertation help a crucial aspect of addressing this health concern. In fact, according to Guo, He, Zhu, Wu & Yuan (2018) ovarian cancer is currently considered the sixth most common type of cancer among females. Cancer occurs in the ovary, abdominal cells and may spread to other parts of the body (Piek et al., 2008). Statistics by Piek et al. (2008) indicated that approximately 239,000 women were affected by ovarian cancer, leading to approximately 152,000 deaths globally. Furthermore, according to Guo et al. (2018), at least 20% of women with stage one or stage two ovarian cancer may experience a reoccurrence within a period of five years, while the five-year survival for those with stage four and five remain extremely low (Arikan et al., 2014).

Context

Ovarian cancer is associated with many risk factors, such as genetics, environmental factors, and hormones (Hunn & Rodriguez, 2012). With many cases of ovarian cancer reoccurrences occur at the abdomen; peritoneal metastasis is considered as one of the leading causes of morbidity and mortality (Werner et al., 2011). According to Cannistra (2004), there is a generally poor prognosis of ovarian cancer among women with peritoneal metastasis, and this leads to fewer therapeutic approaches dedicated to it; there is no evidence that this situation has changed since then. Therefore, there is a record of rare correct ovarian cancer diagnosis until it advances into later stages.

Ovarian cancer is suspected to be associated with higher mortality rates because, by the time most patients are diagnosed, the disease is already at an advanced stage (Taylor & Schwartz, 1994). Therefore, considering the significant differences in prognosis between the early and later stages, it is paramount to have an early detection with accurate staging. However, according to Creasman (1991), physicians have had little success with the use of bimanual pelvic examination (i.e., the use of two hands to physically examine the internal and external pelvic organs), leading to rare detection of most ovarian diseases, especially because the sensitiveness of the technique is below 50% (Creasman, 1991). As a result, physicians have resorted to magnetic resonance imaging (MRI), computed tomography (CT), and ultrasonography (US) as alternatives.

Studies evaluating the effectiveness of US have demonstrated accuracy levels of 80% when used in evaluating ovarian masses (Liu et al., 2007). However, according to Liu et al. (2007), the studies on US have failed to demonstrate its consistency in diagnosing ovarian cancer. On the other hand, studies evaluating the effectiveness of MRI and CT scans have indicated an 80% accuracy in ovarian cancer diagnosis in both. Hence, the imperfect diagnosis accuracy levels of the tools make it difficult for physicians to depend on the accuracy levels of the tools’ diagnostic levels of performance. To the best of the researcher’s knowledge, only a few studies have compared the effectiveness of these diagnostic tools and established their superiority.

Types of Ovarian Cancer

Every patient suffering from ovarian cancer has different experiences, and each require a personalized treatment plan tailored to their specific diagnosis. According to Devaja & Papadopoulos (2018), this begins with identifying the type of ovarian cancer being dealt with. Whereas there are at least 30 categories of ovarian cancer, most types are identified with the cell names responsible for their existence. Nonetheless, Bast (2017) observes that cancerous cells mostly develop on the epithelial cells that form the outer layer of the ovary; where the eggs are released, or on the stromal cells where the hormone are released.

Ovarian epithelial cancer

According to Gubar (2012), ovarian epithelial cancers (i.e. epithelial ovarian carcinomas or cancerous epithelial tumors) account for 85% to 90% of ovarian cancer, and exists in various sub-types such as endometrioid, undifferentiated, clear cell and mucinous cancers cells. The epithelial cancer normally spread on the linings of abdomen and pelvis organs before spreading to other parts of the body such as the liver and lungs. According to Acton (2012), the cells may also spread to the skin, bones and the brain.

There are other ovarian cancer subtypes such as ovarian low malignant potential tumors that occur when the tissue covering the ovary develops abnormal cells (Gubar, 2012). They are named ovarian low malignant potential tumors because tumors are less likely to turn into cancer. But, according to Sims (2003), the tumor cells may become malignant; when that happens, they develop a slow growth and affect women of a younger age. However, Steligo et al (2012) observe that the tumors do not spread beyond the ovary and are more responsive to medication.

There are two other types of cancer cells akin to epithelial ovarian cancer, namely fallopian type cancer and peritoneal carcinoma, which are treated with the same approaches to epithelial ovarian cancer (Bledy, 2008). However, according to Devaja & Papadopoulos (2018), fallopian tube cancer begins in the fallopian tube while primary peritoneal carcinoma develops in the abdomen and pelvis lining (Gubar, 2012).

Germ Cell Tumors

Tumors may also appear in egg-producing cells and most of them are benign (Gubar, 2012). However, based on the writings by (ddd), these cells make up less than 2% of ovarian cancer cases, even though they are more common in women in their 20s and teens. Nonetheless, ovarian germ cell tumors are categorized into three types, namely teratomas, dysgerminoma, and endodermal sinus. According to Devaja & Papadopoulos (2018), teratomas are germ cell tumors that are either mature or immature. While the immature ones are rare, the cells of both immature and mature cells contain different tissues such as bones, muscles and hair. On the other hand, dysgerminoma germ cells rarely occur, but are the most common ovarian cancer germ cell (ddd). They may also exist in other parts of the body such as the central nervous system. Lastly, the endodermal sinus tumors are extremely rare and begin forming either in the ovaries or in the placenta during pregnancy (Gubar, 2012).

Sex Cord-stromal Tumors

These types of tumors rarely occur and comprise only 1% of ovarian cancers (Gubar, 2012). According to Bast (2017), they emerge from the stroma tissue cells where the progesterone and estrogen hormones are produced. They are responsible for abnormal vaginal bleeding because they cause an overabundant supply of estrogen (Gubar, 2012).

Methods of Screening

From several years back, physicians have used MRI as an imaging tool for imaging the anatomy and physiological processes within the body in health and disease. It uses strong magnetic fields, radio waves, and field gradients to construct images of target body organs (Hollingworth et al., 2000). According to Semelka et al. (2007), MRI is an important tool in diagnosing and treating various human diseases and helps in eliminates the risk associated with ionizing radiation. But, existing evidence also indicates that MRI may be unfavorable in some situations because it is time-consuming, expensive, and may exacerbate claustrophobia (Pasquinelli et al., 2012). Thus, computed tomography (CT) has been used as an alternative. However, CT scans have been the foundation to expose patients to high radiation despite being an important tool for population scans (Mc Laughlin et al., 2012). Due to the safety shortcomings of CT scans, medics devised multi-slice CT scans (MSCT), i.e. the normal CT scans used today, to enhance disease diagnosis through ultrasonography and X-rays, all who have progressively experienced increased usage in disease diagnosis and prevention (Liang et al., 2010). However, according to Brenner & Hall (2007), MSCT is associated with radiations known to destroy cell DNA molecules, thus causing cancer. Whereas both MRI and MSCT have been used in the diagnoses of many cancers, there still exists a debate over the use of MRI and CT in the diagnosis of ovarian cancer (Schmidt et al., 2015). Therefore, the main aim of the study is to compare CT and MRI and identify which among them is most effective in the diagnosis of early-stage ovarian cancer among females age 25 to 35 years in the UK.

Lack of tools and obvious initial symptoms has made early diagnosis of different types of ovarian cancer difficult (Lowe et al., 2013). As a typical example; various scientific advancements such as the discovery of tumor progression model means different types of ovarian cancers have been sub-categorized, including the epithelial ovarian cancer (EOC), which has been categorized as type II (the most common and aggressive) and type I (less common and aggressive) cancers (Kaldawy et al, 2016). These types of cancers have different prognoses and developmental patterns that require effective tools to diagnose.

From the 1980s, CT and MRI have been used as effective tools for obtaining images of the pelvic anatomy (Wakefield et al., 2013). Whereas many studies have established the clues for identifying cancer cells in the abdomen, a few studies have focused on the techniques and usability features of the two imaging tools. Therefore, by exploring the literature on the features of these two imaging tools, the present study may be significant in enhancing evidence-based practice in preoperative diagnosis and clinical evaluation of patients’ prognosis.

Research Questions

Which imaging tool between CT and MRI is superior in diagnosis early-stage ovarian cancer?

What are the features of CT and MRI in the diagnosis of early-stage ovarian cancer?

What are the diagnostic values of MRI and CT in the diagnosis of early-stage ovarian cancer?

Research Objectives

To compare the superiority of MRI and CT in the diagnosis of early-stage ovarian cancer

To explore the features of CT and MRI in the diagnosis of early-stage ovarian cancer

To identify the diagnostic values of MRI and CT in the diagnosis of early-stage ovarian cancer

Research Hypotheses

H1: MRI is more superior to CT for screening ovarian cancer

References

Piek JM, van Diest PJ, Verheijen RH. Ovarian carcinogenesis: an alternative hypothesis. Adv Exp Med Biol. 2008;622:79–87.

Arikan SK, Kasap B, Yetimalar H, Yildiz A, Sakarya DK, Tatar S. Impact of prognostic factors on survival rates in patients with ovarian carcinoma. Asian Pac J Cancer Prev. 2014;15(15):6087–6094.

Hunn J, Rodriguez GC. Ovarian cancer: etiology, risk factors, and epidemiology. Clin Obstet Gynecol. 2012;55(1):3–23.\

Werner ME, Karve S, Sukumar R, et al. Folate-targeted nanoparticle delivery of chemo- and radiotherapeutics for the treatment of ovarian cancer peritoneal metastasis. Biomaterials. 2011;32(33):8548–8554.

Cannistra SA. Cancer of the ovary. N Engl J Med. 2004;351(24): 2519–2529.

Bakkar R, Gershenson D, Fox P, Vu K, Zenali M, Silva E. Stage IIIC ovarian/peritoneal serous carcinoma: a heterogeneous group of patients with different prognoses. Int J Gynecol Pathol. 2014;33(3):302–308.

Taylor KJ, Schwartz PE. Screening for early ovarian cancer. Radiology 1994;192(1):1–10.

Creasman W, DiSaia P. Screening for early ovarian cancer. Am J Obstet Gynecol 1991;165(1):7–10.

Hollingworth W, Todd CJ, Bell MI, et al. The diagnostic and therapeutic impact of MRI: an observational multi-centre study. Clin Radiol. 2000;55(11):825–831.

Semelka RC, Armao DM, Elias J Jr, Huda W. Imaging strategies to reduce the risk of radiation in CT studies, including selective substitution with MRI. J Magn Reson Imaging. 2007;25(5):900–909.

Pasquinelli F, Belli G, Mazzoni LN, et al. MR-diffusion imaging in assessing chronic liver diseases: does a clinical role exist? Radiol Med. 2012;117(2):242–253.

Mc Laughlin PD, O’Connor OJ, O’Neill SB, Shanahan F, Maher MM. Minimization of radiation exposure due to computed tomography in inflammatory bowel disease. ISRN Gastroenterol. 2012;2012: 790279.

Liang X, Jacobs R, Hassan B, et al. A comparative evaluation of Cone Beam Computed Tomography (CBCT) and Multi-Slice CT (MSCT) Part I. On subjective image quality. Eur J Radiol. 2010;75(2):265–269.

Brenner DJ, Hall EJ. Computed tomography – an increasing source of radiation exposure. N Engl J Med. 2007;357(22):2277–2284.

Schmidt S, Meuli RA, Achtari C, Prior JO. Peritoneal carcinomatosis in primary ovarian cancer staging: comparison between MDCT, MRI, and 18F-FDG PET/CT. Clin Nucl Med. 2015;40(5):371–37.

K.A. Lowe, V.M. Chia, A. Taylor, et al., An international assessment of ovariancancer incidence and mortality, Gynecol. Oncol. 130 (1) (2013) 107–114.

A. Kaldawy, Y. Segev, O. Lavie, et al., Low-grade serous ovarian cancer: areview, Gynecol. Oncol. 143 (2) (2016) 433–438.

J.C. Wakefield, K. Downey, S. Kyriaze, et al., New MR techniques ingynecologic cancer, AJR Am. J. Roentgenol. 200 (2) (2013) 249–260.

Devaja, O., & Papadopoulos, A. (2018). Ovarian cancer: From pathogenesis to treatment. Rijeka: InTech.

Bast, R. C. (2017). Holland-Frei cancer medicine. Hoboken, New Jersey : John Wiley & Sons, Inc., 2017.

Acton, Q. A. (2012). Ovarian Cancer: New Insights for the Healthcare Professional. Atlanta: Scholarly Editions.

Gubar, S. (2012). Memoir of a debulked woman: Enduring ovarian cancer. New York: W.W. Norton & Co.

Steligo, K., Greene, M. H., & Overdrive Inc. (2012). Confronting Hereditary Breast and Ovarian Cancer. Place of publication not identified: Johns Hopkins University Press.

Sims, D. (2003). An ovarian cancer companion. Burnstown, Ont: General Store Pub. House.

Bledy, C. (2008). Beating ovarian cancer: How to overcome the odds and reclaim your life.

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