On the Additional Information Provided by 3T-MRI ADC in Predicting Tumor Cellularity and Microscopic Behavior

Background: to evaluate whether Apparent Diffusion Coefficient (ADC) values of invasive breast cancer, provided by 3T Diffusion Weighted-Images (DWI), may represent a non-invasive predictor of pathophysiologic tumor aggressiveness. Methods: 100 Patients with histologically proven invasive breast cancers who underwent a 3T-MRI examination were included in the study. All MRI examinations included dynamic contrast-enhanced and DWI/ADC sequences. ADC value were calculated for each lesion. Tumor grade was determined according to the Nottingham Grading System, and immuno-histochemical analysis was performed to assess molecular receptors, cellularity rate, on both biopsy and surgical specimens, and proliferation rate (Ki-67 index). Spearman’s Rho test was used to correlate ADC values with histological (grading, Ki-67 index and cellularity) and MRI features. ADC values were compared among the different grading (G1, G2, G3), Ki-67 (<20% and >20%) and cellularity groups (<50%, 50–70% and >70%), using Mann–Whitney and Kruskal-Wallis tests. ROC curves were performed to demonstrate the accuracy of the ADC values in predicting the grading, Ki-67 index and cellularity groups. Results: ADC values correlated significantly with grading, ER receptor status, Ki-67 index and cellularity rates. ADC values were significantly higher for G1 compared with G2 and for G1 compared with G3 and for Ki-67 < 20% than Ki-67 > 20%. The Kruskal-Wallis test showed that ADC values were significantly different among the three grading groups, the three biopsy cellularity groups and the three surgical cellularity groups. The best ROC curves were obtained for the G3 group (AUC of 0.720), for G2 + G3 (AUC of 0.835), for Ki-67 > 20% (AUC of 0.679) and for surgical cellularity rate > 70% (AUC of 0.805). Conclusions: 3T-DWI ADC is a direct predictor of cellular aggressiveness and proliferation in invasive breast carcinoma, and can be used as a supporting non-invasive factor to characterize macroscopic lesion behavior especially before surgery.

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Dynamic Perfusion Computed Tomography and Apparent Diffusion Coefficient as Potential Markers for Poorly Differentiated Pancreatic Adenocarcinoma

Digestive Surgery ◽

10.1159/000511973 ◽

2021 ◽

pp. 1-8

Author(s):

Inga Zaboriene ◽

Kristina Zviniene ◽

Saulius Lukosevicius ◽

Povilas Ignatavicius ◽

Giedrius Barauskas

Keyword(s):

Computed Tomography ◽

Diffusion Coefficient ◽

Apparent Diffusion Coefficient ◽

Tumor Grade ◽

Adc Value ◽

Predictive Values ◽

Apparent Diffusion ◽

Adc Values ◽

Poorly Differentiated ◽

Grade One

Introduction: Tumor grade, one of the most important risk factors for survival, is routinely determined after examining the biopsy material or a surgically removed specimen. The aim of the study was to analyze computed tomography (CT) perfusion parameters and diffusion-weighted imaging apparent diffusion coefficient (ADC) values in pancreatic ductal adenocarcinoma (PDAC) and to establish the diagnostic value of these modalities determining the tumor grade. Materials and Methods: A prospective clinical study included 56 subjects with PDAC. All the patients had a local perfusion assessment and ADC measurement of the tumor. For the prediction of poor tumor differentiation sensitivity, specificity, positive, and negative predictive values for each perfusion CT and ADC parameters based on cutoff values from ROC analysis were calculated. Results: Mean transit time (MTT) and ADC values were found to be independent prognosticators for the presence of G3 PDAC. MTT and ADC at the cutoff of 17.37 s and 1.15 × 10−3 mm2/s, respectively, appeared to be significant parameters discriminating against the differentiation grade of PDAC. If both values exceeded the defined cutoff point, the estimated probability for the presence of G3 PDAC was 89.29%. Conclusion: The MTT parameter, calculated with the deconvolution method, and the ADC value may serve as effective independent prognosticators identifying poorly differentiated PDAC.

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Evolving Concept Of Non Ischaemic Brain Lesions Through Diffusion Weighted MRI Imaging

QJM ◽

10.1093/qjmed/hcaa068.025 ◽

2020 ◽

Vol 113 (Supplement_1) ◽

Author(s):

M A Elkory ◽

H M Mansour ◽

A F Abdelghany ◽

E H Abdeldayem

Keyword(s):

Intracranial Hemorrhage ◽

Brain Infarction ◽

Brain Lesions ◽

Demyelinating Diseases ◽

Mri Imaging ◽

Adc Value ◽

Diffusion Weighted Images ◽

Diffusion Weighted ◽

Ischaemic Brain ◽

Adc Values

Abstract Purpose to assess the role of Diffusion weighted images in evaluation and characterization of non ischemic brain lesions, which is essential in determining appropriate patient management . Methods and Material The included 100 patients with different brain lesions other than infarctions (37 males & 63 females) were further classified into 6 groups. These are intracranial infarctions, intracranial hemorrhage, intracranial masses (which is further subdivided into extra-axial and intra-axial masses), traumatic brain lesions, demyelinating diseases and others (encephalopathies and leukodystrophies). Their ages ranged from 8 days to 77 years with a mean age of 37.6 years. Results The ADC value of lesions of each group was then compared with that of normal appearing white matter (NAWM) in the same patients.In intracranial infections the ADC values of those lesions that showed true restriction (n = 6/7) ranged from 0.32 x 10-3 mm2/sec to 0.93 x 10-3 mm2/sec (with a mean of 0.63±0.2 x 10-3 mm2/sec) while that of NAWM in the same patients ranged from 0.76 x 10-3 mm2/sec to 0.94 x 10-3 mm2/sec (with a mean of 0.86±0.8 x 10-3 mm2/sec). In intracranial hemorrhage, 6 lesions showed true restriction with ADC values ranging from 0.25 x 10-3 mm2 / sec to 1.0 x 10-3 mm2 / sec (with a mean of 0.71±0.33 x 10-3 mm2 / sec) while the ADC value of the NAWM in the same patients ranged from 0.64 x 10-3 mm2 / sec to 0.7 x 10-3 mm2 / sec (with a mean of 0.68±0.04 x 10-3 mm2 / sec). In extra-axial masses, true restriction was identified in 16 patients with ADC values ranging from 0.43 x 10-3 mm2 / sec to 1.1 x 10-3 mm2 / sec (with a mean of 0.75±0.2 x 10-3 mm2 / sec). The ADC values of NAWM in the same patients ranged from 0.64 x 10-3 mm2 / sec to 0.76 x 10-3 mm2 / sec (with a mean of 0.68±0.04 x 10-3 mm2 / sec). In intra-axial masses, true restriction was identified in 32 patients with ADC values ranging from 0.34 x 10-3 mm2 / sec to 1.1 x 10-3 mm2 / sec (with a mean of 0.82±0.2 x 10-3 mm2 / sec). The ADC values of NAWM in the same patients ranged from 0.6 x 10-3 mm2 / sec to 0.85 x 10-3 mm2 / sec (with a mean of 0.69±0.06 x 10-3 mm2 / sec). Conclusion Diffusion MRI (or DWI) imaging has assumed an essential role in the detection of acute brain infarction and in the differentiation of acute infarction from other disease processes. DW MR imaging is also assuming an increasingly important role in the evaluation of many other intracranial disease processes. It shows promising value in the evaluation of intra-cranial infections, tumors, demyelinating diseases, traumatic brain lesiones as well as encephalopathies and leukodystrophies. Further evaluation of the ADC value could be of help especially in the evaluation of the grades of neoplastic processes, evaluation of the prognosis of traumatic brain lesions and in the assessment of the plaques of multiple sclerosis. We concluded that DWI is an essential sequence in the evaluation of different brain lesions and recommend its addition to the routine MRI examination of the brain.

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Prediction of the Recurrence of Non-Functioning Pituitary Adenomas Using Preoperative Supra-Intra Sellar Volume and Tumor-Carotid Distance

Frontiers in Endocrinology ◽

10.3389/fendo.2021.748997 ◽

2021 ◽

Vol 12 ◽

Author(s):

Wenli Chen ◽

Mengqi Wang ◽

Chengbin Duan ◽

Shun Yao ◽

Haosen Jiao ◽

...

Keyword(s):

Pituitary Adenomas ◽

Tumor Volume ◽

Volume Ratio ◽

Roc Curves ◽

Tumor Diameter ◽

Distance Ratio ◽

Ki 67 ◽

Mri Features ◽

D Values ◽

D Value

BackgroundCurrently, it is difficult to estimate the possibility of recurrence of nonfunctioning pituitary adenomas (NFPAs). Markers such as Ki-67 or transcription factors rely on postoperative pathology, while few indices can be used for preoperative prediction. Therefore, we aimed to investigate the predictive effectiveness of supra-intrasellar volume and tumor-carotid distance based on measurements derived from preoperative magnetic resonance imaging (MRI) data.MethodNinety-eight cases of NFPAs were evaluated, along with their clinical characteristics and MRI features. Four radiologic indices were analyzed, including intrasellar tumor volume, suprasellar tumor volume, maximum horizontal tumor diameter, and intercarotid distance. The ratio of supra-intrasellar volume and ratio of tumor-carotid distance were measured using 3D Slicer software, and the sum of two ratios was defined as the V-D value. The correlation between recurrence and multiple factors was analyzed using univariate and multivariate logistic regression and Kaplan-Meier analysis, and ROC curves were used to estimate the prognostic performance of radiologic measurements in NFPAs.ResultThe supra-intrasellar volume ratio, tumor-carotid distance ratio and V-D value were significantly correlated with the recurrence of NFPAs. The predictive importance of the V-D value reached 84.5%, with a sensitivity of 83.7% and specificity of 67.3%. The cutoff limit of the V-D value was 1.53, and patients with V-D values higher than 1.53 tended to relapse much earlier.ConclusionThe V-D value has predictive importance for the recurrence of NFPAs preoperatively. Patients with higher V-D values will undergo recurrence earlier and should be given greater consideration in terms of surgery and follow-up time.

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Value of Apparent Diffusion Coefficient for Assessing Preoperative T Staging of Low Rectal Cancer and Whether This Is Correlated With Ki-67 Expression

Canadian Association of Radiologists Journal ◽

10.1177/0846537119885666 ◽

2020 ◽

Vol 71 (1) ◽

pp. 5-11 ◽

Cited By ~ 1

Author(s):

Weiqun Ao ◽

Xiangdong Bao ◽

Guoqun Mao ◽

Guangzhao Yang ◽

Jian Wang ◽

...

Keyword(s):

Rectal Cancer ◽

Diffusion Coefficient ◽

Apparent Diffusion Coefficient ◽

Low Rectal Cancer ◽

Biological Behavior ◽

Proliferation Index ◽

Ki 67 ◽

Adc Value ◽

Apparent Diffusion ◽

Adc Values

Purpose: To explore the value of the apparent diffusion coefficient (ADC) in assessing preoperative T staging of low rectal cancer and the correlation between ADC value and Ki-67 expression. Methods: Data on 77 patients with a proven pathology of low rectal cancer were retrospectively analyzed. All patients underwent a magnetic resonance imaging scan 1 week prior to operation, and the mean ADC value was measured. All tumors were fully removed, and pathologic staging was determined. The Ki-67 expression was determined using immunohistochemical methods in all patients. The correlation between Ki-67 expression and ADC features was studied. Results: A total of 77 patients with low rectal cancer were included in the study. The pathology type was adenocarcinoma. The numbers of patients with pathological stages T1, T2, T3, and T4 were 9, 23, 32, and 13, respectively. The ADC value of all tumors ranged from 0.60 to 1.20 mm2/s. The average Ki-67 proliferation index was 55.3% ± 20.2%. A significant difference was observed between the preoperative ADC value and pathological T staging of low rectal cancer ( P < .01). The more advanced the T stage, the lower the detected ADC values were. A negative correlation was noted between the preoperative ADC value and Ki-67 proliferation index of rectal cancer ( r = −0.71, P < .01). When the Ki-67 proliferation index increased, lower ADC values were detected. Conclusion: The ADC values can provide useful information on preoperative tumor staging and may facilitate evaluation of the biological behavior of low rectal cancer. The ADC values should be considered a sensitive image biomarker of rectal cancer.

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Comparison of the Mutation Profiles of Triple-Negative Breast Cancers and Hormone Receptor-Positive/Human Epidermal Growth Factor Receptor 2-Negative Breast Cancers at the T2N0-1M0 Stage

10.21203/rs.3.rs-129609/v1 ◽

2020 ◽

Author(s):

Seungju Lee ◽

Hyun Yul Kim ◽

Youn Joo Jung ◽

Hyun-June Paik ◽

Chang Shin Jung ◽

...

Keyword(s):

Breast Cancer ◽

Epidermal Growth Factor Receptor ◽

Growth Factor ◽

Growth Factor Receptor ◽

Tumor Grade ◽

Breast Cancers ◽

Ki 67 ◽

Hormone Receptor Positive ◽

Her2 Breast Cancer ◽

Epidermal Growth

Abstract BackgroundTriple-negative breast cancer (TNBC) has higher loco-regional recurrence and visceral metastasis compared to other breast cancer subtypes; however, little is known about the molecular pathogenesis and therapeutic targets of TNBC. Therefore, we compared the mutation profiles of early TNBC with those of hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2) breast cancer using a customized next-generation sequencing capture panel.MethodsDNA was obtained from the primary tumor tissues of 34 patients diagnosed with pT2N0-1M0 HR+/HER2 breast cancer or TNBC. To enrich the 48 breast cancer-associated genes, 21,192 probes were designed using the SureSelect design tool. After library preparation using the SureSelect XT kit (Agilent), paired-end DNA sequencing was performed on a HiSeq platform (Illumina). The mean depth of the target regions was 1,766 (×). The subsequent output containing genetic variation was analyzed using a pipeline of bioinformatics tools. Significant mutations with allele frequencies of more than 30% were checked for their germline counterparts in the peripheral blood. Circulating cell-free nucleic acids were extracted and analyzed with a therascreen® PIK3CA RGQ PCR kit (QIAGEN).ResultsSignificant mutations were found in TP53, PIK3CA, AR, BRCA1, PTEN, BRCA2, BRIP2, KIT, MET, AKT1, ALK, BARD1, BRAF, CD274, ERBB2, FGFR1, IDH2, NOTCH1, RET, and STK11 (in descending order of occurrence). TP53 mutations were identified in the TNBC group more frequently than in the HR+/HER2 group (p=0.003). The presence of TP53 mutations was associated with a higher tumor grade (p=0.008), p53 positivity (p<0.0001), and a higher (≥15) Ki-67 index (p=0.004). PIK3CA was the most frequently mutated gene in HR+/HER2 breast cancer (8/22, 36.4%), but not in TNBC (1/12, 8.3%). However, circulating cell-free PIK3CA mutations were not detected in either group. ConclusionsThe TP53 mutation is associated with higher tumor grade and Ki-67 expression in both groups, and with larger tumor size in TNBC, but not in HR+/HER2– breast cancer. In the foundation of TP53 mutation, concomitant mutation numbers are proportional to tumor size, reflecting clonal progression. Breast cancer-associated mutations such as those in TP53 and PIK3CA have different biological implications for the proliferation and clonal diversification of these two distinct groups of breast cancer.

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Radiomics for Tumor Characterization in Breast Cancer Patients: A Feasibility Study Comparing Contrast-Enhanced Mammography and Magnetic Resonance Imaging

Diagnostics ◽

10.3390/diagnostics10070492 ◽

2020 ◽

Vol 10 (7) ◽

pp. 492

Author(s):

Maria Adele Marino ◽

Doris Leithner ◽

Janice Sung ◽

Daly Avendano ◽

Elizabeth A. Morris ◽

...

Keyword(s):

Breast Cancer ◽

Magnetic Resonance Imaging ◽

Tumor Grade ◽

Hormone Receptor Status ◽

Breast Cancers ◽

Resonance Imaging ◽

Dce Mri ◽

Tumor Invasiveness ◽

Non Invasive ◽

Contrast Enhanced

The aim of our intra-individual comparison study was to investigate and compare the potential of radiomics analysis of contrast-enhanced mammography (CEM) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast for the non-invasive assessment of tumor invasiveness, hormone receptor status, and tumor grade in patients with primary breast cancer. This retrospective study included 48 female patients with 49 biopsy-proven breast cancers who underwent pretreatment breast CEM and MRI. Radiomics analysis was performed by using MaZda software. Radiomics parameters were correlated with tumor histology (invasive vs. non-invasive), hormonal status (HR+ vs. HR−), and grading (low grade G1 + G2 vs. high grade G3). CEM radiomics analysis yielded classification accuracies of up to 92% for invasive vs. non-invasive breast cancers, 95.6% for HR+ vs. HR− breast cancers, and 77.8% for G1 + G2 vs. G3 invasive cancers. MRI radiomics analysis yielded classification accuracies of up to 90% for invasive vs. non-invasive breast cancers, 82.6% for HR+ vs. HR− breast cancers, and 77.8% for G1+G2 vs. G3 cancers. Preliminary results indicate a potential of both radiomics analysis of DCE-MRI and CEM for non-invasive assessment of tumor-invasiveness, hormone receptor status, and tumor grade. CEM may serve as an alternative to MRI if MRI is not available or contraindicated.

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Abstract 2550: Early 3 Hour Imaging Demonstrates Substantial Diffusion Reversal with Lower Infarction Risk Compared to Tissue without Diffusion Reversal

Stroke ◽

10.1161/str.43.suppl_1.a2550 ◽

2012 ◽

Vol 43 (suppl_1) ◽

Author(s):

Andria L Ford ◽

Hongyu An ◽

Gyanendra Kumar ◽

Katie D Vo ◽

William J Powers ◽

...

Keyword(s):

Lower Risk ◽

Brain Regions ◽

Lesion Volume ◽

Stroke Patients ◽

Infarct Core ◽

Adc Value ◽

Diffusion Weighted Images ◽

Apparent Diffusion ◽

Adc Values ◽

Abnormal Tissue

Background: Literature suggests that diffusion reversal--determined by visually inspecting diffusion-weighted images which reverse on subsequent imaging--is uncommon. However, these studies performed the initial scan 3 to 6 hrs from onset which may miss lesions that have already undergone reversal. We measured apparent diffusion coefficient (ADC) reversal between 2 scans obtained at 3 and 6 hrs from onset comparing infarct probability in reversed regions to brain regions with persistent ADC lesions. Methods: Ischemic stroke patients underwent 3 MRI’s: <4.5 hrs (tp1), at 6 hrs (tp2), and at 1 mo (tp3) after onset. Co-registered maps measured ADC lesions (tp1, tp2) and FLAIR infarct (tp3). Diffusion lesions were manually outlined as hypointense regions on ADC. A population-derived ADC threshold to distinguish abnormal from normal ADC was calculated based on the maximum ADC value capturing >90% of voxels within the outlined lesions. ADC values less than or greater than this threshold were defined as abnormal and normal, respectively. ADC “reversal” was defined as voxels with abnormal tp1 ADC and normal tp2 ADC, whereas ADC “non-reversal” was defined as abnormal ADC on both tp1 and tp2. Final infarcts were outlined as hyperintense regions on tp3 FLAIR. Infarct probability (% of the tp1 ADC lesion which infarcted on tp3) was compared between reversed and non-reversed tissue using a Mann-Whitney test. Leukoariosis or CSF voxels due to infarct atrophy were excluded from the infarct analysis. Results: 39 patients were prospectively scanned at 2.8hr (tp1), 6.4hr (tp2), and 1mo (tp3) after stroke onset (NIHSS=14, 74% received tPA). The population-derived ADC threshold to distinguish between abnormal and normal was 71 × 10 -5 mm 2 /s. Median ADC lesion volume at tp1 was 34ml [15, 70] and at tp2 was 34ml [14, 65]. Median ADC reversal volume was 6.6ml [5, 17], accounting for 34% [11, 44] of the tp1 ADC lesion volume (ADC non-reversal volume was 21ml [6, 50]). 31 of 39 (79%) and 20 of 39 (51%) patients had reversal volumes >10% and >33% of their initial ADC lesion, respectively. Infarct probability was lower (57%) in ADC reversal tissue compared to tissue with non-reversal (82%, p<0.0001) ( Figure ). To confirm that the derived ADC threshold distinguished abnormal tissue on tp1 from normal tissue on tp2, ADC tp1 and tp2 values were compared and differed (66 vs. 77, p<0.0001). Conclusion: While ADC closely approximates infarct core, during early ischemia, a substantial proportion of the initial ADC lesion may reverse. Brain tissue with this MR signature carries a significantly lower risk of infarction than tissue without ADC reversal.

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Histopathological Characteristics of Triple-Negative Breast Cancer: An Iranian Issue

Galen Medical Journal ◽

10.31661/gmj.v3i3.146 ◽

2014 ◽

Vol 3 (3) ◽

pp. 145-52

Author(s):

Mehrnoosh Etemadi ◽

Mohammad Mahdi Zamani ◽

Amir Masoud Nazemi ◽

Afsaneh Rajabiani ◽

Alireza Abdollahi

Keyword(s):

Breast Cancer ◽

Triple Negative Breast Cancer ◽

Triple Negative ◽

Growth Factor Receptor ◽

Tumor Grade ◽

Tumor Location ◽

Breast Cancers ◽

Ki 67 ◽

Appropriate Treatment ◽

Type Size

Background: Breast cancer is one of the most frequent malignancies among Iranian women. Triple-negative breast cancer (TNBC) is referred to a type of breast cancer which three biomarkers of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 (HER2), are negative.Materials and Methods: In this case control study, immunohistopathologic data of patients with TNBC were compared with non-TNBC patients. According to pathological reports, frequency, age, gender, type, size, and tumor grade, involvement and the number of involved lymph nodes, mitosis, Ki-67, necrosis, nuclear grade, tumor side, involvement of the margins, skin involvement, nipple involvement, tumor location, vascular invasion, perineural invasion, presence of in-situ compartment and the benign accompanied tumors, granulomatosis reaction, and calcification were compared between both groups.Results: Two hundred fourteen pathological samples of patients with breast cancer were evaluated. TNBC was seen in about 14% of breast cancers in this study on Iranian population. The mean age of TNBC group was 43±12 years and non-TNBC was 50±12 years (p=0.03). TNBC had significantly higher grade, high mitotic indices, more possibility of P53 positivity and higher level of Ki-67. Presence of vascular and nerve invasion and involvement of the margins at the time of diagnosis were seen in the TNBC group comparing with the non-TNBC group.Conclusion: Younger age, higher grading, neurovascular invasion, P53 positivity, and high levels of Ki-67, lead clinicians to evaluate the biomarkers of TNBC, and in case of confirming TNBC diagnosis, appropriate treatment methods should be added to the routine ones in breast cancer.

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Association of DW/DCE-MRI Features with Prognostic Factors in Breast Cancer

The International Journal of Biological Markers ◽

10.5301/jbm.5000230 ◽

2017 ◽

Vol 32 (1) ◽

pp. 118-125 ◽

Cited By ~ 3

Author(s):

Guoliang Shao ◽

Linyin Fan ◽

Juan Zhang ◽

Gang Dai ◽

Tieming Xie

Keyword(s):

Breast Cancer ◽

Prognostic Factors ◽

Ductal Carcinoma ◽

Dynamic Imaging ◽

Breast Lesions ◽

Adc Value ◽

Dce Mri ◽

Mri Features ◽

Adc Values ◽

Malignant Lesions

Background Through analyzing apparent diffusion coefficient (ADC) values and morphological evaluations, this research aimed to study how magnetic resonance imaging (MRI)-based breast lesion characteristics can enhance the diagnosis and prognosis of breast cancer. Methods A total of 118 breast lesions, including 50 benign and 68 malignant lesions, from 106 patients were analyzed. All lesions were measured with both diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI. The average ADC of breast lesions was analyzed at b values of 600, 800 and 1,000 s/mm2. Lesion margins, lesion enhancement patterns, and dynamic curves were also investigated. The relations between MRI-based features and molecular prognostic factors were evaluated using Spearman's rank correlation analysis. Results A b value of 800 s/mm2 was used to distinguish malignant from benign breast lesions, with an ADC cutoff value of 1.365 × 10−3 mm2/s. The average ADC value between invasive ductal carcinoma (IDC) and ductal carcinoma in situ (DCIS) was significantly different. Malignant lesions were more likely to have spiculated margins, heterogeneous enhancement and washout curves. On the other hand, DCIS was more likely to have spiculated margins, heterogeneous/rim enhancement and plateau/washout dynamic curves. A significant negative correlation was found between progesterone receptor (PR) status and dynamic imaging (p = 0.027), while a significant positive correlation was found between Ki-67 status and lesion enhancement (p = 0.045). Conclusions Both ADC values and MRI morphological assessment could be used to distinguish malignant breast lesions from benign ones.

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Pre-operative Prediction of Ki-67 Expression in Various Histological Subtypes of Lung Adenocarcinoma Based on CT Radiomic Features

Frontiers in Surgery ◽

10.3389/fsurg.2021.736737 ◽

2021 ◽

Vol 8 ◽

Author(s):

Zhiwei Huang ◽

Mo Lyu ◽

Zhu Ai ◽

Yirong Chen ◽

Yuying Liang ◽

...

Keyword(s):

Risk Factors ◽

Feature Selection ◽

Lung Adenocarcinoma ◽

Roc Curves ◽

Ct Images ◽

Expression Level ◽

Receiver Operating Curve ◽

Ki 67 ◽

Non Invasive ◽

Lung Adenocarcinomas

Purpose: The aims of this study were to combine CT images with Ki-67 expression to distinguish various subtypes of lung adenocarcinoma and to pre-operatively predict the Ki-67 expression level based on CT radiomic features.Methods: Data from 215 patients with 237 pathologically proven lung adenocarcinoma lesions who underwent CT and immunohistochemical Ki-67 from January 2019 to April 2021 were retrospectively analyzed. The receiver operating curve (ROC) identified the Ki-67 cut-off value for differentiating subtypes of lung adenocarcinoma. A chi-square test or t-test analyzed the differences in the CT images between the negative expression group (n = 132) and the positive expression group (n = 105), and then the risk factors affecting the expression level of Ki-67 were evaluated. Patients were randomly divided into a training dataset (n = 165) and a validation dataset (n = 72) in a ratio of 7:3. A total of 1,316 quantitative radiomic features were extracted from the Analysis Kinetics (A.K.) software. Radiomic feature selection and radiomic classifier were generated through a least absolute shrinkage and selection operator (LASSO) regression and logistic regression analysis model. The predictive capacity of the radiomic classifiers for the Ki-67 levels was investigated through the ROC curves in the training and testing groups.Results: The cut-off value of the Ki-67 to distinguish subtypes of lung adenocarcinoma was 5%. A comparison of clinical data and imaging features between the two groups showed that histopathological subtypes and air bronchograms could be used as risk factors to evaluate the expression of Ki-67 in lung adenocarcinoma (p = 0.005, p = 0.045, respectively). Through radiomic feature selection, eight top-class features constructed the radiomic model to pre-operatively predict the expression of Ki-67, and the area under the ROC curves of the training group and the testing group were 0.871 and 0.8, respectively.Conclusion: Ki-67 expression level with a cut-off value of 5% could be used to differentiate non-invasive lung adenocarcinomas from invasive lung adenocarcinomas. It is feasible and reliable to pre-operatively predict the expression level of Ki-67 in lung adenocarcinomas based on CT radiomic features, as a non-invasive biomarker to predict the degree of malignant invasion of lung adenocarcinoma, and to evaluate the prognosis of the tumor.

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