Positive enhancement integral values in dynamic contrast enhanced magnetic resonance imaging of breast carcinoma: Ductal carcinoma in situ vs. invasive ductal carcinoma

Nadrljanski, Mirjan; Maksimović, Ružica; Plesinac-Karapandzic, Vesna; Nikitović, Marina; Marković-Vasiljković, Biljana; Milošević, Zorica

doi:10.1016/j.ejrad.2014.05.006

Cited by 14 publications

(14 citation statements)

References 20 publications

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“…Upstaging of DCIS to invasive carcinoma has implications for treatment planning. In this dataset, the rate of upstaging from DCIS to DCIS with an invasive component was within the ranges previously identified and similar to the average rate of upstaging found in Brennan et al and Lee et al Our study shows that semiautomatically assessed MRI features may have a role in predicting patients with a preoperative diagnosis of DCIS who are at increased risk for having an invasive component to their disease.…”

Section: Discussionsupporting

confidence: 89%

“…While a CNB is typically sufficient for a pathologist to make a diagnosis of DCIS, the small total volume of tumor sampled by CNB may miss adjacent invasive cancer. At the time of definitive surgery, upstaging to invasive disease occurs in 3.5–56% of cases . A meta‐analysis of DCIS upstaging rates by Brennan et al concluded an average upstaging rate of 25.9%, while Lee et al reviewed the literature to find an average rate of 20.9%.…”

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confidence: 99%

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Can algorithmically assessed MRI features predict which patients with a preoperative diagnosis of ductal carcinoma in situ are upstaged to invasive breast cancer?

Harowicz

Saha

Grimm

et al. 2017

Magnetic Resonance Imaging

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Purpose To assess the ability of algorithmically assessed magnetic resonance imaging (MRI) features to predict the likelihood of upstaging to invasive cancer in newly diagnosed ductal carcinoma in situ (DCIS). Materials and Methods We identified 131 patients at our institution from 2000–2014 with a core needle biopsy-confirmed diagnosis of pure DCIS, a 1.5 or 3T preoperative bilateral breast MRI with nonfat-saturated T1-weighted MRI sequences, no preoperative therapy before breast MRI, and no prior history of breast cancer. A fellowship-trained radiologist identified the lesion on each breast MRI using a bounding box. Twenty-nine imaging features were then computed automatically using computer algorithms based on the radiologist’s annotation. Results The rate of upstaging of DCIS to invasive cancer in our study was 26.7% (35/131). Out of all imaging variables tested, the information measure of correlation 1, which quantifies spatial dependency in neighboring voxels of the tumor, showed the highest predictive value of upstaging with an area under the curve (AUC) = 0.719 (95% confidence interval [Cl]: 0.609–0.829). This feature was statistically significant after adjusting for tumor size (P < 0.001). Conclusion Automatically assessed MRI features may have a role in triaging which patients with a preoperative diagnosis of DCIS are at highest risk for occult invasive disease. Level of Evidence 4

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Section: Discussionsupporting

confidence: 89%

mentioning

confidence: 99%

Can algorithmically assessed MRI features predict which patients with a preoperative diagnosis of ductal carcinoma in situ are upstaged to invasive breast cancer?

Harowicz

Saha

Grimm

et al. 2017

Magnetic Resonance Imaging

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show abstract

“…These results are in agreement with previous studies performed with other types of solid tumors, including orbital (23), breast (24,25), head and neck (26) and pancreatic tumors (11). A previous study in colorectal cancer is consistent with the present study (27).…”

Section: Discussionsupporting

confidence: 83%

Diagnostic value of dynamic contrast-enhanced magnetic resonance imaging in rectal cancer and its correlation with tumor differentiation

Chen

et al. 2016

Molecular and Clinical Oncology

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Abstract. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a novel imaging modality that can be used to reflect the microcirculation, although its value in diagnosing rectal cancer is unknown. The present study aimed to explore the clinical application of DCE-MRI in the preoperative diagnosis of rectal cancer, and its correlation with tumor differentiation. To achieve this, 40 pathologically confirmed patients with rectal cancer and 15 controls were scanned using DCE-MRI. The Tofts model was applied to obtain the perfusion parameters, including the plasma to extravascular volume transfer (Ktrans), the extravascular to plasma volume transfer (Kep), the extravascular fluid volume (Ve) and the initial area under the enhancement curve (iAUC). Receiver-operating characteristic (ROC) curves were plotted to determine the diagnostic value. The results demonstrated that the time-signal intensity curve of the rectal cancer lesion exhibited an outflow pattern. The Ktrans, Kep, Ve, and iAUC values were higher in the cancer patients compared with controls (P<0.05). The intraclass correlation coefficients of Ktrans, Kep, Ve and iAUC, as measured by two independent radiologists, were 0.991, 0.988, 0.972 and 0.984, respectively (all P<0.001), indicating a good consistency. The areas under the ROC curves for Ktrans and iAUC were both >0.9, resulting in a sensitivity and specificity of 100% and 93.3% for Ktrans, and of 92.5%, and 93.3% or 100%, for iAUC, respectively. In the 40 rectal cancer cases, there was a moderate correlation between Ktrans and iAUC, and pathological differentiation (0.365 years old, and rectal cancer occurs rarely in patients who are under 40 years of age; in addition, men are predominantly affected (2). Probable risk factors include age, male gender, colon polyps, a history of colorectal cancer, a history of inflammatory bowel disease, hereditary syndromes, lifestyle factors (diet, alcohol, obesity, sedentary lifestyle and smoking), and a history of diabetes mellitus (1). Rectal cancer is usually managed using a combination of surgery, chemotherapy, targeted therapy and radiation therapy (3). The five-year survival rates following surgical resection are 85-95% for stage I, 60-80% for stage II, and 30-60% for stage III cancer. With the aging of the Chinese society and a Westernization of the diet, the incidence of rectal cancer in China is increasing (4). Therefore, finding novel means to efficiently detect and diagnose rectal cancer are required.Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a relatively novel imaging modality that demonstrates the capillary blood flows (5,6). In DCE-MRI, the distribution of the contrast agent is repeatedly evaluate...

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“…We found that the D pf mean, 75 th , and 90 th percentile metrics were significantly higher in the group with the DCIS component <5% than in the group with the DCIS component ≥5%. It might be because perfusion rates increase from benign to DCIS to invasive cancer . Liu et al also reported that a higher value of the perfusion fraction was found in malignant tumors than that in benign lesions, and the high perfusion fraction purported high vascularity in malignant tumors .…”

Section: Discussionmentioning

confidence: 98%

Intravoxel incoherent motion (IVIM)‐derived parameters in diffusion‐weighted MRI: Associations with prognostic factors in invasive ductal carcinoma

Lee

Kim

Kang

et al. 2016

Magnetic Resonance Imaging

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Positive enhancement integral values in dynamic contrast enhanced magnetic resonance imaging of breast carcinoma: Ductal carcinoma in situ vs. invasive ductal carcinoma

Cited by 14 publications

References 20 publications

Can algorithmically assessed MRI features predict which patients with a preoperative diagnosis of ductal carcinoma in situ are upstaged to invasive breast cancer?

Can algorithmically assessed MRI features predict which patients with a preoperative diagnosis of ductal carcinoma in situ are upstaged to invasive breast cancer?

Diagnostic value of dynamic contrast-enhanced magnetic resonance imaging in rectal cancer and its correlation with tumor differentiation

Intravoxel incoherent motion (IVIM)‐derived parameters in diffusion‐weighted MRI: Associations with prognostic factors in invasive ductal carcinoma

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