Systematic Review: Effectiveness Of MRI And Ultrasound Scan Methods Of Cancers In Dense Breast Tissue

Current Imaging Techniques and Challenges

A Systematic review On Effectiveness of MRI and Ultrasound Scan Methods of Cancers in Dense Breast Tissue

Radiographical imaging of dense breast represents a diagnostic challenge among radiologists. Breast cancer has a high chance of missed assessment in dense breast compared to radiologically fatty breasts (MacInnes et al., 2020). Lowered visibility and lesions to the missed dense breasts tissues and increased risks of malignancy dense breasts is a major challenge. With the increased risks states, the difficulty of recognizing the lesions through various methods tends to improve the overall specificity of visualizing the underlying malignancies. Current methods being used entail magnetic resonance imaging, digital imaging, computer-aided detection, ultrasound, sestamibi and position emission tomography-PET imaging.

Dense breast tissues are defined in three various ways (dos Santos et al., 2016); four progressive mode dense patterns as described by patterns of N1, P1, P2, DY referred to as Wolf patterns, four progressive dense patterns as defined by the American College of Radiology of breasts Imaging. These four broad assessments entail the BIRADS; ACR, Reston, VA; BIRADS assesses entirely fat content, ACR assess the scattered fibro glandular densities which could affect obscured lesion states, Reston identifies the heterogeneous dense which might lower the sensitivity and VA assessment system exploring the extremely dense which lowers the sensitivity of the mammography (Sood et al., 2019). The final method of definition entails the percentage of parenchyma tissues as compared with fat density levels in planimetry or computer systems. In most of the clinical systems, BIRANDS terminology is often used. According to Kolb et al (2002), BIRADS definition is based on fat interspersed in the area of high density on the fibro glandular tissues and the overall size of the tissues. This outlines four broad classification; Grade 1; areas of tissues which could be obscure with cancer, Grade 2; having at least one region with obscure cancer, Grade 3; having tissues with obscure cancer in about 50% to 70% positive of cancer and Grade 4 entailing tissues with obscure cancer greater than 75% of breasts. The dense breast density of key interest entails that of grade 3 and 4. The reduced overall visibility levels of masses and calcifications linked to decreased contrast levels. The results have shown obscure subtle abnormalities and increased levels of no visualization of malignancies.

Various studies have illustrated wide variability of radiologists levels of categorizing breast density based on Wolfe’s classification system with reliability and reproducibility being a key focus. Few studies have assessed the variability of radiologists based on the BIRADS system (D’Orsi, Bassett & Feig, 2018) due to the wide variability in breast density classification, Wolfe suggestion on the usage of planimetry have shown validity and reproducibility aspects. In a view for standardizing this method,Wei et al (2011), developed a computerized technique which categorizes the breast tissues density levels. The single cranial-caudal view is digitalized, this allows the radiologists to select breast edges and regions of density and computer generates the density percentage. This is a likely fundamental future avenue for additional imaging process for modalities which are key benefits for patients with dense breast levels. Further computer-aided programs tend to be accurate and reproduce breast density percentage in any digital mammogram of interests (Rampun et al., 2019).

Research Questions and Aim

The elevated levels of breast cancer dense cells have been demonstrated to be between 1.8 and 1.6 times greater compared to normal breasts. Boyd et al (5) assessed 571 monozygotic and 380 dizygotic assessments and showed that dense breast occurring in tins was a fourfold increased level of risks of malignancy as compared to twins with few dense breasts. Factors associated with breast cancer were linked as age, diet, hormonal therapy, weight, menopause, genetics and live births (Lafourcade et al., 2018). Hormonal therapy was observed to affect the overall breast density. Greendale et al (2003) demonstrated that breast density increase of 4.6% to 4.8% was observed when the oestrogen and progestogen were offered at the same time, while there was no similar increase in oestrogen levels alone. Further Carney et al (2004) assessed 463 378 mammograms and showed that hormonal therapy elevated the breast density and lowered the overall sensitivity of mammography. Hormonal therapy was not linked to the independent predictor on mammography accuracy but influences the accuracy levels according to elevated breast tissues density.

Studies have shown that ultrasound imaging of the breast and magnetic resonance imaging (MRI) may help identify breast cancers that can be missed on mammograms alone. As well as finding breast cancers with these two imaging modalities, ultrasound and MRI are also able to find information that is not cancerous (Breast Density and Mammogram Reports; Dense Breast Tissue, 2020).

Ultrasound technique is readily available tools for assessing the modality of screening among women with dense breast levels who are at an increased risk for breast cancer. Various studies have shown that breast screening of ultrasound tends to increase in additional 2-4 mammographically occult levels in cancer cases per 1000 (Weigert & Steenbergen, 2015).  Ultrasound screening, however, has been observed to encompass various limitations; these include aspect relating to time, costs and low predictive levels of about 8% in biopsy assessment. A low predictive positive value is a risk as it leads to an increasing number of unnecessary biopsies and high rate of short term follow-up (Hooley et al., 2012). This suggests the sole usage of breast ultrasound among women with average intermediate risks of developing breast cancer is an issue of concern.

Application of enhanced magnetic resonance imaging-MRI is based on neo angenesesis process. Tumour is linked to the blood vessels which have increased levels of increased permeability levels is responsible for the uptake and the overall washout gadolinium after it is administered. The lesions morphology enhances and washout kinetics is an essential feature in distinguishing between various states of benign lesions. Studies have reported high sensitivity levels of over 90% but low specific levels of low to moderate at 72%, this discriminates benign and malignant lesions to be a challenging task. Since early 2000, breast MRI has been extensively and has become a high risks screening tool for diagnosis, staging and follow up of breast cancer. Breast MRI has shown to be a high-value risks screening tool, evaluation the unknown primary, local disease extent, multi centrally and bilateral dense breasts, offering differentiation on a scare from local recurrences ad the overall evaluation response of adjuvant therapy process in chemotherapy and integrity of implants (Radhakrishna et al., 2018).

Inclusion Criteria

Women with dense breast tissue are at risk of being misdiagnosed concerning breast cancer. By reviewing research, it allows us to compare problems in current imaging techniques and provide other options for this group of women allowing for future improvement, thus allowing for future improvement imaging techniques.

Problem statement 

Mammograms are the gold standard in detecting early-stage breast cancers but can also give the patient information on how dense their breast tissues are. Dense breast tissue consists of lobules, also known as glandular tissue, that produces milk, ducts that deliver breast milk from the lobules to the nipple, the fatty and fibrous connective tissue that gives the breasts it shapes and size (Breast Density and Mammogram Reports | Dense Breast Tissue, 2020). Women that have dense breasts tissue are at a higher risk of developing breast cancer than women with less dense breast tissue. Women with dense breast tissue make it difficult for the radiologist to identify cancer. This is because, on the mammogram, dense breast tissues appear radiopaque on the image, and breast mass/tumour also has a radiopaque appearance, so this can be easily missed as the mass/tumour can hide within the fatty tissue(Breast Density and Mammogram Reports; Dense Breast Tissue, 2020).

The following research question is being explored in this study; Which imaging modality between MRIS and Ultrasound methods is more superior in detecting cancer in women with dense breast tissue?

The purpose of this study is to assess the effectiveness of two key methods; MRI and ultrasound on detection of breast dense cancer among women. This is key towards identifying a better technique which can offer high specificity and sensitivity values on detecting dense breast cancer cells. This is achieved through literature review search on recent studies exploring the application of these two techniques. 

Aim

The aim of this literature review to identify whether MRI or Ultrasound is more effective in identifying breast cancer in women with dense breasts using relevant research articles

Objectives

Current research articles will be analysed concerning the effectiveness of magnetic resonance imaging and ultrasound detection of breast cancers in women with dense breasts. Through comparison, we will be able to critique current techniques and provide a clearer understanding as to what should be offered for women in this category.

Inclusion/exclusion Criteria 

The inclusion criteria for the selection entailed analysis of peer reviewed studies on human subjects where ultrasound and MRI were assessed as a primary detection tool for breast cancer. The search process was based on English articles. Both protective, reproductive and cross-sectional studies published from 2015 to 2020 were included in the study. The appropriate references standard was focused on biopsy of the histopathology results. Each of the manuscripts selected was required to have calculatable true positives, false negatives and false-negative positives this enhanced the sensitivity, positive, negative predictive and positive predictive value to be predicted. Studies comparing both were included in the search process.

Methods

A systematic review of the literature and meta-analysis was perfumed in the Pubmed and Cochrane databases based on guidelines for screening and diagnostic test and preferred reporting system for review and meta-analysis guidelines. Eligible studies published within the last 5 years that is 2020 and 2015 were searched. The search was designed and modified to identify studies on ultrasound and MRI screening procedures as priory detection for dense breast cancer both on screening and diagnostic abilities were performed. A comprehensive search was performed which entailed the application of free text and MeSH terms. the search terms used in the search entailed; ‘breast cancer’, ‘breast lesions’, ‘breast ultrasound’, ‘breast MRI’, ‘breast magnetic resonance imaging’ and ‘screening’. The titles and abstracts of the papers found were screened to assess the primary eligibility based on the preferred reporting items for systemic review and meta-analysis algorithm. The references were further screened for any additional relevant studies.

Data extracted included all demographic data, type of study, the setting of the study, age, positive case identification image interpretation and standard reference for each study were extracted. The quality assessment process was made based on the Quality assessment of diagnostic studies tool was used (Whiting et al., 2011). Three key potential domains were used; this included selection of patients, index tests performances and references standard.

The Pubmed search yielded 510 studies with additional records identified elsewhere were 47, after duplicates removal 52 studies remained and entered the screening phase. A total of 400 studies were excluded based on relevance. 107 studies were reviewed. The further exclusion was performed for eligibility purposes with further exclusion being performed. A total of 15 studies were included in the review meeting the inclusion criteria process. The tables provide summaries of the results obtained in the systematic review search process;

Table 1 Summary of Ultrasound assessment protocols

	Lehman et al 2016	Vreemann et al 2018	Sood et al	Bahl et al 2015	Rebolj et al 2018	Jeh et al 2015	Yong et al 2019	Weigert 2017
Study period	2002–2005	2003–2014	2000-2018	2009-2011			2012-2016	2009-2013
Number of participants	687	2463	26 studies	327	29 studies	173	72250	Year 1= 2706 Year 2= 3,351 Year 3= 4,128 Year 4= 3,331
Number of cancers	27	170	76,026 ultrasound examinations	273	494-29%	206	9765(13.51%)	Year 1= 11 Year 2= 11 Year 3= 13 Year 4= 11
Sensitivity (%)
MRI	93	81.4	88.4	56
US	37	NA	80.1	–		83-automated 94.2-handheld
PPV (%)				–
MRI	48	28		–
US	33	NA		11.7				Year 1= 7.3 Year 2= 6.1 Year 3= 8.8 Year 4= 20.1

*MRI=Magnetic Resonance Imaging; US= Ultrasound ; PPV= Positive Predictive Value

Typical breast MRI examination assessed and generates various images for interpretation purposes and requires upto about 40 minutes for the image acquisition process. Abbreviated protocols of MRI have one pre-contrast image, 1 post-contrast image and derived images. These methods often vary and reduce the overall acquisition and interpretation times; these abbreviated protocols are presented in table 2 above. The rationale for first post-contrast sequence is often based on the observation of cancer which is best visualized based on arterial phase after contrasts injection in between the angiogenic tumour and adjacent fibro glandular regions which is greater (Rahim et al., 2017). The dynamic process of the sequences and pulse sequence is generated for the characterization process rather than for enhanced lesions. Benign lesions tend to change in compared to malignant lesions and the background parenchymal enhancement of normal fibro glandular tissues tend to exhibit slower enhancing persistence leading to lowered visualization process and low levels of detecting false-positive interpretations.

Results

Table 2 Summary of MRI protocols results

	Sensitivity (%)	Specificity (%)	Acquisition Time	Interpretation Time
Heacock et al. (2016)
AP1	97.8	–	–	14.0–25.4 s
AP2	99.4	–	–	–
AP3	99.4	–	12 min	19.0–35.3 s
FP	–	–	35 min	–
Mango et al. (2015)
MIP	93	–	10–15 min	44 s
Subtraction	96	–	–	–
Post-contrast	96	–	–	–
FP	–	–	–	4.7 min
Grimm et al. (2015)
AP1	86	52	–10 min	2.98 ± 1.86 min
AP2	89	45	–	–
FP	95	52	20 min	2.95 ± 1.59 min
Moschetta et al. (2016)
AP	89	91	10 min	2 ± 1.2 min
FP	92	92	16 min	6 ± 3.2 min
Harvey et al. (2016)
AP	89	91	10 min	1.55 min
FP	92	92	16 min	6.43 min
Chen et al. (2017)
AP1	92.9	86.5	–	–
AP2	100	95.0	–	–
FP	100	96.8	32 min	–
FP =  full  diagnostic  protocol; AP= Abbreviated protocol

 
The performance, acquisition and interpretation duration of MRI has been assessed and presented as shown in table 2. The protocols show indicated a shorter duration of abbreviated MRI compared to full protocols. Heacock et al (2016) assessed the MRI images on 107 biopsies of proven breast cancers. The MRI protocol showed consistent fat-suppressed sagittal on the T1- weighted pre contrasts and subtracted images. The reported sensitivity ranged from 97.8% to about 99.4% in three protocols conducted based on without clinical information during imaging, with clinical data and prior imaging and after addition of T2 images. The study concluded that T2 weighting did not show any improvement in the detection of rate and showed that abbreviated MRI has a high rate of detecting cancer. The shorter interpretation was observed linked with masses as compared to non-masses enchanters and elevated the overall initial enhancement rations. Further, there was an observed enhancement ratio correlated with tumour grade increase, disease invasiveness and conspicuity of lesion suggesting a wash in a characteristic of malignancy likely to contribute to efficacy levels of MRI protocols. The study by Mango et al (2015) based on 100 consecutive MRI examinations among patients with biopsy-proven breast carcinomas. Evaluation of post contrasts T1 weighted images and their underlying subtractions and MIP. The average sensitivity levels were shown to be 96% with average time reading being 4.7 minutes. Both studies of Mango et al (2015) and Heacock et al (2016) based their studies on known cases of breast cancer hence did not exhibit real clinical setup, further, an observe tests were not conducted hence making the comparison not effective.

Grimm et al (2015) assessed multi-reader based on abbreviated MRI protocols with 24 normal subject don clinical information reports, 12 benign d 12 malignant patients. The first project consisted of the fat-suppressed sagittal imaging process, then one pre contrasts and first post contrasts T1 weighted acquisition. The second protocol consisted of protocol 1 images with second post contrasts acquisition. The findings were not significant in cancer detections rates based on sensitivity assessments between protocol and diagnostic protocol at 1 (86%; p = 0.22) and 2 (89%; p = 0.38)., further there as the average time of 2.98 vs 3.56 respectively in both protocols. The study by Moschetta et al (2016) assessed 470 patients and 185 breasts lesions undergoing MRI breast cancer for various clinical conditions arranging from screening, staging and problem-solving. The study reported sensitivity, specificity and negative values for the abbreviated and MRI protocols and the results demonstrated longer values compared to those of Moschetta et al (2016), this was most likely due to additional morphological and pre contrasts sequences.

Discussion

The study by Harvey et al (2016) assessed the usage of abbreviated protocols for high-risk screening. The use of MRI protocol often takes over 30 minutes to get the images while the abbreviated protocol process showed decreased time to just 10 minutes. The authors showed an interruption time of 1.55 minutes in the abbreviated protocol. Patient management changes were observed in 12 out of 588 MRI studies representing 2.1% of the subjects. the images obtained were obtained from breast cancer patients, there was full awareness of subject cases hence making the results not to be applied in the real screening process. The study by Chen et al (2017) based on abbreviated protocols among 356 women with dense breast assessed based on mammography process. Protocol 1 consisted of fat-suppressed T2 image weighted, a second protocol consisting of protocol 1 images and diffused weighted images. The results showed no significant differences in the three protocols of breast cancer diagnostics. The specificity level of protocol 1 was higher than the protocol 2 and full diagnostic protocol. The result showed that protocol 2 consisting of fat-suppressed T2 weighted imaging and diffused weighted imaging was effective in higher specificity levels of breast cancer detection.

In the assessment of Ultrasound imaging of breast cancer density levels, the study by Rebolj et al (2018) assessed ultrasound to mammography techniques in assessing breast cancer density through a systematic review. The results showed that there was a proportion of 0.29 (95% CI: 0.27–0.31) equivalent to 40% detection of cancers compared to mammography. This was translating to about additional 3.8 cases per 1000 negative mammography women. The study showed that ultrasound doubled the overall referral assessment in this data analysis. Among nipple pathology discharge patients, evaluation for ultrasound was assessed by Bahl et al (2015). The study undertook a retrospective assessment of records presented with nipple discharge between 2009 and 2011 over three years, the results showed a total of 327 females were identified presenting with nipple discharge, among this a 273 were either offered surgical excision, clinical or radiographic follow up with at least 2 years of presentation. Among this 246 patients underwent tomography. 8% (20) of the patients with ductile carcinoma in situ or occurrence of invasive adenocarcinoma were diagnosed. In this detection, the sensitivity and specificity of the ultrasound were shown to at 56% and 75% respectively.

The study by Jeh et al (2015) assessed automated and handheld breast ultrasonography ion detection of breast lesions. A total of 173 consecutive women to underwent ultrasonography process. Among this there were 206 lesions, 46 were observed to be malignant and 160 were benign. The detection rates in automated ultrasound were 83% while in handheld method was 94.2%. in the 194 handhelds detected lesions, 169 were detected by automated breast ultrasound while 25 benign cases were not identified. This demonstrated that automated breast ultrasonography was less effective in detecting the lesions especially those of smaller size and those of benign appearances and a low final assessment at p=0.011 and p<0.0001 respectively. Similarly in a study by Wang et al (2019) in detecting breast cancer among high risks women assessed a total of 1,938,996 subjects from 2012-2016 in China provinces. In this subjects participants a further 75,250 women were assessed to be high risks hence took screening as per protocol. The evaluation was based on the Breast Imaging Reporting and Data system –BIRADS. The results showed that 13.51% of women had positive ultrasound screening, this included 11.75%, 1.67% and 0.09% based on BIRADS assessment of II, IV and V categories respectively. Multivariate prediction model yielded modest prediction levels f AUC 0.55.

Conclusion

A study by Weigert (2017) assessed dense breast cancer based on bilateral ultrasound for 4 years among women. The study took a retrospective data from 2009 to 2013 with data focusing on mammograms and ultrasound process, BIRADS, biopsy results and patient information.  In year 1, there was 2,706 ultrasound with 151 biopsies found 11 cancers with the positive predictive value of 7.3%, the detection rate was 4.0/1000. In year 2, there were 3,351 ultrasounds with 180 biopsies, there were 11 cancers and high risks related lesions, and the positive predictive value was 6.1% with a detection rate of 3.3/1000. In year 3, there were 4,128 ultrasounds with 148 biopsies; there were 13 cancers with high risks lesions, 13 cancer cases were found with a positive predictive value of 8.8% with detection rates of 3.1/1000. In year 4 there were 3,331 ultrasounds performed, this yielded 11 cancers and high risks lesions with a positive predictive value of 20.1% and detection rate of 3.3 /1000. Cancers observed before negative screening process was measured at 0.4 -1.2 cm based ultrasound. Ultrasound of breast among women with dense breast was detected mammographic occult-based malignancy.  

Ultrasound methods have been a readily available technology being supplemental imaging avenues for assessing breasts density among the average and interlinear risk of breast cancer among women. Various studies have shown that breast cancer screening ultrasound can detect an additional 2.4 mammographic occult per 1000 screened women, despite these various limitations have been sobered regarding time, cost and low predictive positive values with an approximate o 8%. Often low biopsy levels lead to unnecessary biopsies examinations and high rate of follow up (Weigert et al., 2015; Hooley et al., 2012). This signifies that breast ultrasound examination may be problematic among women with breast cancer. On the contrary, MRI has been preferred for breast cancer screening due to increased levels of performance and detection of biological characteristics which are essential in breast cancer identification process. MRI has been viewed as an effective form of tests for detecting breast cancer among women with increased risks of breast cancer, in comparing with ultrasound; MRI shows improved efficacy levels for detecting dense breast cancer. Interval rates in cancer screening are a metric essential for assessing the overall performance of screening programs. According to Europe Mammographic screening programs, the accepted range is 30% to 50% being observed among participants (European guidelines, online). Low interval rates of 0% have been reported in other studies (Kuhl et al., 2017).

Based on the MRI biological characteristics feature, Sung et al (2016) assessed clinical imaging and histopathological features of breast cancer assessment with MRI screening, mammography and interval cancers among 7519 high-risk women, 1804 MRI screening and 26,866 mammography screening. MRI detected a likely to be induced in situ with the presence of calcification. In a prospective cohort study by Kuhl et al (2010), diagnosis of 2 cancer cases was made based on mammography screening, no case for an ultrasound while in MRI, there were 14 cases with a total of 27 cases. Among these cases, 8 cases were observed to be invasive and 6 were ductal carcinoma in situ. This depicted that MRI can have a significant effect on cancers of the breast.

In this review, an assessment of abbreviated MRI showed that as a way of increasing the specificity and confidence levels in diagnosis, abbreviated MRI with T2 weighted sequence was explored (Heacock et al., 2016; Grimm et al., 2015; Moschetta et al., 2016). Despite, the T2 weighted sequence, there was no improvement on the reading levels in Heacock et al (2016), in the other two studies, there was a significant increase in the confidence levels of evaluation of lesion. The limited kinetic evaluation may trigger MRI diagnostic evaluation. Grimm et al (2015) showed that the addition of the second post-contrast series did not show any effects on sensitivity and specificity levels. Limited analysis of lesion characterization can play a major factor. Full MRI evaluation offers high resolution informational cross-sectional morphology process and functional information on tissue perfusion, permeability, relaxation period, tissue proliferation and interstitial pressure. These attributes are useful in characterizing the tissues and contributed greater differential of benign and malignant lesions and classification of the biological and prognostics impact of lesions obtained. Lesions having fats uptake process followed by a washout during the delay process have a higher chance of being malignant, despite this, there is an overlap of kinetic assessments of malignant and benign based MRI. To overcome this effect, combining the ultrafast process of MRI based on the abbreviated protocol process is essential (Oldrini et al., 2017).

Despite the observed beneficial effects of MRI on breast cancer screening, ultrasound is an effective avenue for the detection of small, invasive and negative node cancers in dense display breast tissue. Various studies have indicated increased sensitivity and high negative predictive value of upto 100% in cancer detection on focal breast symptoms (Mann et al., 2008; American College of Radiology, 2015). As a tool for detection, ultrasound has the potential to affect earlier detection states. A study by Thigpen, Kappler and Brem (2018) assessed ultrasound screening process for dense breast cancer. The study showed that ultrasound as increased by detection rate of 1.9-4.2% depending on the population type. Further, it observed that automated ultrasound devices play a crucial role on improving challenges obsvee3rd in handheld programs coupled with faster scan times, lowered operator dependencies and improved workflow exhibited in datasets, similar to findings observed by Su et al (2016) in comparing handheld and automated ultrasound, who gave preference to the automated ultrasound technique as it detected all malignant lesions, hence being preferred type of ultrasound tool.

A study by Rebolji et al (2018) assessed additional ultrasound to mammography methods on breast dense tissues. The study demonstrated that there is an increased detection thought supplementary but predominantly invasive ultrasound in detecting dense breast cancers. Similarly Bahl et al (2015) in assessing diagnostic value among female patients with nipple discharge concluding that ultrasound was an effective form of the routine evaluation of breast cancer-related care. Despite this, its application in clinical practices proves a challenge due to limited resources, health care capacities similar to observation observed by Thigpen, Kappler and Brem (2018) who opined the barriers of implementation especially on health care resource and costs impacts.

Wang et al (2019) assessed ultrasound screening process for high risks women from the population screening program. This study assessed the effectiveness of ultrasound in population-based assessment protocols. The findings demonstrated that ultrasound can showcase satisfactory results in screening breast cancer in a population level, however, the prediction model levels on environmental risks were low. Further in 4 years based evaluation period of ultrasound-based technique on dense breast among women, there was increase positive predictive value over the four years, doubling from the first year indicating increased levels of accuracy on lesions biopsy.

The key underlying strengths of this study were based on the broad inclusion criteria with comprehensive search terms which captured the relevant studies. This study evaluated ultrasound techniques and MRI with most of the studies focusing on abbreviated MRI showing the significant potential of improving the overall screening process of dense breasts cancer. Despite these benefits of abbreviated MRI, human clinical trials are still limited in the current domain of literature. The abbreviated MRI has shown increased specificity levels and sensitivity to assess dense breast cancer, these similar findings to normal MRI protocol which has a high evaluation outcome compared to ultrasound techniques. MRI offers clear and detailed images displaying the soft tissues compared to ultrasound which is key in differentiating malignancy breast cancer cells. Another critical benefit entails the ability to create many images and cover a wider area of the breast is key in offering critical evaluation concerning the spread of cancer. Hence based on the objective, MRI provides an effective avenue for assessing dense breast cancer.

Conclusion

Breast cancer medical imaging services offer an avenue for being the third eye for physicians and diagnostic experts to obtain correct breast dense cancer cells enabling positive diagnosis. The review selected studies covering on ultrasound and MRI techniques. The results show that MRI has a high potential of being specific and sensitive hence detecting breast cancer cells. MRI full protocol and abbreviated protocol in one study showed 100% sensitivity with high specificity levels. Moreover, most of the studies signified high sensitivity and specificity values.

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