Features Of Microcalcifications Research Articles

Susceptibility-Weighted MRI for Predicting NF-2 Mutations and S100 Protein Expression in Meningiomas.

S100 protein expression levels and neurofibromatosis type 2 (NF-2) mutations result in different disease courses in meningiomas. This study aimed to investigate non-invasive biomarkers of NF-2 copy number loss and S100 protein expression in meningiomas using morphological, radiomics, and deep learning-based features of susceptibility-weighted MRI (SWI). This retrospective study included 99 patients with S100 protein expression data and 92 patients with NF-2 copy number loss information. Preoperative cranial MRI was conducted using a 3T clinical MR scanner. Tumor volumes were segmented on fluid-attenuated inversion recovery (FLAIR) and subsequent registration of FLAIR to high-resolution SWI was performed. First-order textural features of SWI were extracted and assessed using Pyradiomics. Morphological features, including the tumor growth pattern, peritumoral edema, sinus invasion, hyperostosis, bone destruction, and intratumoral calcification, were semi-quantitatively assessed. Mann-Whitney U tests were utilized to assess the differences in the SWI features of meningiomas with and without S100 protein expression or NF-2 copy number loss. A logistic regression analysis was used to examine the relationship between these features and the respective subgroups. Additionally, a convolutional neural network (CNN) was used to extract hierarchical features of SWI, which were subsequently employed in a light gradient boosting machine classifier to predict the NF-2 copy number loss and S100 protein expression. NF-2 copy number loss was associated with a higher risk of developing high-grade tumors. Additionally, elevated signal intensity and a decrease in entropy within the tumoral region on SWI were observed in meningiomas with S100 protein expression. On the other hand, NF-2 copy number loss was associated with lower SWI signal intensity, a growth pattern described as "en plaque", and the presence of calcification within the tumor. The logistic regression model achieved an accuracy of 0.59 for predicting NF-2 copy number loss and an accuracy of 0.70 for identifying S100 protein expression. Deep learning features demonstrated a strong predictive capability for S100 protein expression (AUC = 0.85 ± 0.06) and had reasonable success in identifying NF-2 copy number loss (AUC = 0.74 ± 0.05). In conclusion, SWI showed promise in identifying NF-2 copy number loss and S100 protein expression by revealing neovascularization and microcalcification characteristics in meningiomas.

Translating microcalcification biomarker information into the laboratory: A preliminary assessment utilizing core biopsies obtained from sites of mammographic calcification

Rationale and objectivesThe potential of breast microcalcification chemistry to provide clinically valuable intelligence is being increasingly studied. However, acquisition of crystallographic details has, to date, been limited to high brightness, synchrotron radiation sources. This study, for the first time, evaluates a laboratory-based system that interrogates histological sections containing microcalcifications. The principal objective was to determine the measurement precision of the laboratory system and assess whether this was sufficient to provide potentially clinical valuable information. Materials and methodsSections from 5 histological specimens from breast core biopsies obtained to evaluate mammographic calcification were examined using a synchrotron source and a laboratory-based instrument. The samples were chosen to represent a significant proportion of the known breast tissue, mineralogical landscape. Data were subsequently analysed using conventional methods and microcalcification characteristics such as crystallographic phase, chemical deviation from ideal stoichiometry and microstructure were determined. ResultsThe crystallographic phase of each microcalcification (e.g., hydroxyapatite, whitlockite) was easily determined from the laboratory derived data even when a mixed phase was apparent. Lattice parameter values from the laboratory experiments agreed well with the corresponding synchrotron values and, critically, were determined to precisions that were significantly greater than required for potential clinical exploitation. ConclusionIt has been shown that crystallographic characteristics of microcalcifications can be determined in the laboratory with sufficient precision to have potential clinical value. The work will thus enable exploitation acceleration of these latent microcalcification features as current dependence upon access to limited synchrotron resources is minimized.

Microcalcification crystallography as a potential marker of DCIS recurrence

Ductal carcinoma in-situ (DCIS) accounts for 20–25% of all new breast cancer diagnoses. DCIS has an uncertain risk of progression to invasive breast cancer and a lack of predictive biomarkers may result in relatively high levels (~ 75%) of overtreatment. To identify unique prognostic biomarkers of invasive progression, crystallographic and chemical features of DCIS microcalcifications have been explored. Samples from patients with at least 5-years of follow up and no known recurrence (174 calcifications in 67 patients) or ipsilateral invasive breast cancer recurrence (179 microcalcifications in 57 patients) were studied. Significant differences were noted between the two groups including whitlockite relative mass, hydroxyapatite and whitlockite crystal maturity and, elementally, sodium to calcium ion ratio. A preliminary predictive model for DCIS to invasive cancer progression was developed from these parameters with an AUC of 0.797. These results provide insights into the differing DCIS tissue microenvironments, and how these impact microcalcification formation.

Clinical Study of Ultrasonographic Risk Factors for Central Lymph Node Metastasis of Papillary Thyroid Carcinoma

BackgroundThyroid cancer is the most common malignancy of the endocrine system worldwide. Papillary thyroid cancer (PTC) is the most common pathologic type. The preoperative diagnosis of PTC and central lymph node metastasis (CLNM) or metastatic tendency is of great clinical significance to the diagnosis, treatment and prognosis of these patients. This study was conducted to investigate the correlation between ultrasound features and central CLNM of PTC.MethodsThis study retrospectively analyzed patients who underwent PTC surgery and central lymph node dissection in the Department of Surgery, Beijing Tiantan Hospital, from January 2019 to February 2020. According to the inclusion and exclusion criteria, data from 136 patients were ultimately included, and the clinical and ultrasonic data of the patients were analyzed by multivariate regression to evaluate the correlation among grayscale ultrasound (US), superb microvascular imaging (SMI) and contrast-enhanced ultrasound (CEUS) features of thyroid nodules and CLNM of PTCs.ResultsThe multivariate analysis showed that tumor size, multifocality, microcalcification characteristics, SMI vascularization, and CEUS evaluation of contact with the adjacent capsule were correlated with PTC metastasis (P=0.008, P=0.001, P=0.028, P=0.041, and P< 0.001, respectively). Comparisons of the area under the ROC curves revealed that the area under the ROC curve of the degree of nodular invasion into the thyroid capsule was the largest (AUC: 0.754). The sensitivity and specificity for evaluating CLNM of PTC were 67.7% and 83.1%, respectively.ConclusionsUltrasound characteristics of the following features are associated with a high risk of lymph node metastasis in PTCs: maximum diameter of nodules ≥1 cm, multifocality, ≥5 microcalcifications, abundant blood flow of SMI in nodules and nodule contact with the thyroid capsule ≥25% under CEUS. Ultrasound has clinical value in the preoperative evaluation of CLNM of PTCs.

Microcalcification-Based Tumor Malignancy Evaluation in Fresh Breast Biopsies with Hyperspectral Stimulated Raman Scattering.

Precise evaluation of breast tumor malignancy based on tissue calcifications has important practical value in the disease diagnosis, as well as the understanding of tumor development. Traditional X-ray mammography provides the overall morphologies of the calcifications but lacks intrinsic chemical information. In contrast, spontaneous Raman spectroscopy offers detailed chemical analysis but lacks the spatial profiles. Here, we applied hyperspectral stimulated Raman scattering (SRS) microscopy to extract both the chemical and morphological features of the microcalcifications, based on the spectral and spatial domain analysis. A total of 211 calcification sites from 23 patients were imaged with SRS, and the results were analyzed with a support vector machine (SVM) based classification algorithm. With optimized combinations of chemical and geometrical features of microcalcifications, we were able to reach a precision of 98.21% and recall of 100.00% for classifying benign and malignant cases, significantly improved from the pure spectroscopy or imaging based methods. Our findings may provide a rapid means to accurately evaluate breast tumor malignancy based on fresh tissue biopsies.

A risk stratification algorithm for lesions of uncertain malignant potential diagnosed by vacuum-assisted breast biopsy (VABB) of mammographic microcalcifications

PurposeTo investigate a risk stratification strategy for lesions of uncertain malignant potential (B3) diagnosed by vacuum-assisted breast biopsy (VABB) of mammographic microcalcifications. MethodsPatients who underwent VABB for microcalcification-only lesions with a diagnosis of B3 and subsequent surgery were included in this retrospective, IRB-approved study. Seventy-six B3-lesions (final histology: 66 benign, 10 malignant) were included (Tr). Data on B3 lesion type and presence of atypia, microcalcification characteristics (BI-RADS), removal at biopsy and concomitant lesions were collected. After univariate analysis (Chi-square test), data were combined into a risk stratification algorithm by using a ten-fold, cross-validated Classification and Regression Tree analysis (CRT). The algorithm was tested on a testing dataset (Te) of 23 B3-lesions (six malignant, 17 benign). ResultsMalignancy was more frequent in women with a concomitant cancer (P < 0.001) and highly suspicious microcalcifications (P < 0.001). The CRT algorithm retained three characteristics: morphology; presence of atypia; presence of concomitant cancer. The algorithm identified 25/76 (32.9 %,Tr) and 6/23 (26.1 %,Te) lesions at low risk of malignancy. No malignant cases were identified at surgery (0/31). There were 3/76 (3.9 %,Tr) and 1/23 (4.3 %,Te) lesions assigned as high-risk by the algorithm and confirmed at surgery (4/4). In the remaining lesions (48/76, 63.1 %,Tr; 16/23, 69.6 %,Te), malignancy rates varied between 9% and 88.4 %; thus, surgery could not have been avoided. ConclusionWe constructed and tested a risk stratification algorithm for B3 microcalcifications, including clinical, imaging, and pathological features, to assign probabilities of malignancy, which has the potential to reduce unnecessary surgeries.

Is There Any Association Between Mammographic Features of Microcalcifications and Breast Cancer Subtypes in Ductal Carcinoma In Situ?

To analyze the association between mammographic features of microcalcifications and histopathological prognostic factors based on estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2/neu) in ductal carcinoma in situ (DCIS). We retrospectively determined 66 patients with microcalcification-associated pure DCIS. Distribution and morphological features of the microcalcifications were described using Breast Imaging Reporting and Data System lexicon. All patients were divided into three subgroups: ER-positive, HER-2 positive, and triple-negative according to the immunohistochemical findings. The morphological features of microcalcifications and receptor subtypes were significantly correlated (p = 0.026). Fine pleomorphic and fine linear branching microcalcifications were observed in 85.2% of HER-2 positive cases, whereas this ratio was 71.4 % in ER-positive and 25% in the triple-negative group. Fine linear branching microcalcifications with linear or segmental distribution were more frequently found with comedo necrosis (p < 0.05). Larger tumour sizes were also associated with microcalcification distribution (p < 0.001). Segmental microcalcifications more likely associated with larger tumour sizes. Mammographic features in DCIS correlated with immunohistochemical and histopathological prognostic factors.

Raman Spectroscopy Reveals That Biochemical Composition of Breast Microcalcifications Correlates with Histopathologic Features.

Breast microcalcifications are a common mammographic finding. Microcalcifications are considered suspicious signs of breast cancer and a breast biopsy is required, however, cancer is diagnosed in only a few patients. Reducing unnecessary biopsies and rapid characterization of breast microcalcifications are unmet clinical needs. In this study, 473 microcalcifications detected on breast biopsy specimens from 56 patients were characterized entirely by Raman mapping and confirmed by X-ray scattering. Microcalcifications from malignant samples were generally more homogeneous, more crystalline, and characterized by a less substituted crystal lattice compared with benign samples. There were significant differences in Raman features corresponding to the phosphate and carbonate bands between the benign and malignant groups. In addition to the heterogeneous composition, the presence of whitlockite specifically emerged as marker of benignity in benign microcalcifications. The whole Raman signature of each microcalcification was then used to build a classification model that distinguishes microcalcifications according to their overall biochemical composition. After validation, microcalcifications found in benign and malignant samples were correctly recognized with 93.5% sensitivity and 80.6% specificity. Finally, microcalcifications identified in malignant biopsies, but located outside the lesion, reported malignant features in 65% of in situ and 98% of invasive cancer cases, respectively, suggesting that the local microenvironment influences microcalcification features. This study confirms that the composition and structural features of microcalcifications correlate with breast pathology and indicates new diagnostic potentialities based on microcalcifications assessment. SIGNIFICANCE: Raman spectroscopy could be a quick and accurate diagnostic tool to precisely characterize and distinguish benign from malignant breast microcalcifications detected on mammography.

Integration of Sonoelastography Into the TIRADS Lexicon Could Influence the Classification.

Aim: Numerous TIRADS (Thyroid Image Reporting and Data System) classifications have been developed, and various ultrasound (US) parameters are employed in different countries. The aim of our study was to introduce risk classification and management in a native population based on the Guidelines of Polish National Societies Diagnostics and Treatment of Thyroid Carcinoma but with the addition of sonoelastography.Materials and Methods: We examined prospectively 208 patients with 305 thyroid lesions employing B-mode ultrasound and sonoelastography (SE). Nodule composition, echogenicity, margins, shape, presence or absence of calcifications, thyroid capsule, nodule size were assessed using B-mode ultrasound. Moreover, sonoelastography results were presented using the Asteria scale.Results: In univariate analysis, the following US features were significantly associated with malignancy: >50% solid /solid component, marked hypoechogenicity, ill-defined margins, micro and macrocalcification, taller-than wide shape, no/partial halo pattern, infiltration of the capsule and an Asteria score of 4. Multivariate logistic regression analysis of B-mode features revealed that ill-defined margins (OR 10.77), markedly hypoechogenicity (OR 5.12), microcalcifications (OR 4.85), thyroid capsule infiltrations (OR 3.2), macrocalcifications (OR 3.01), and hard lesion in SE (OR 6.85) were associated with a higher Odds Ratio (OR) for malignancy. Multivariate logistic regression analysis revealed that combining two features increases the OR and the best combination was irregular margins and Asteria scale 4 (OR 20.21). Adding a third feature did not increase the OR.Conclusions: Sonoelastography increases the value risk of predicted malignancy, with consequent different approach to further clinical investigation and management. A solitary feature (Asteria 4) in a solid tumor can result in its categorization as TIRADS 4, but coexistence with high risk features allows it to be upgraded to TIRADS 5. The irregular margin was the strongest single feature which allowed for the assignment of a solid tumor into TIRADS 5 category. The highest accuracy was found by combining the features of age, margin, echogenicity (markedly hypoechoic), capsule infiltration, microcalcifications and sonoelastography (Asteria 3,4) of the tumors.

Features of Microcalcifications on Screening Mammography in Young Women

Background:There is no decrease in the number of breast cancer deaths if screening mammography is performed in women aged <40 years. However, NCCN guidelines recommend screening mammography in young women at risk of hereditary breast cancer. Therefore, more accurate screening mammography for young women is needed.Objective:To evaluate the features of screening mammographic findings, particularly microcalcifications, in women aged <50 years to increase the positive predictive value of screening mammography in young women.Methods:We retrospectively reviewed the data of consecutive women who underwent opportunistic and organized breast cancer screening at the Sakuragaoka Hospital (Shizuoka, Japan) between April 2013 and March 2015. We compared the mammographic findings and features of microcalcifications between women aged <40 and 40–49 years and those aged 50–74 years.Results:The study included 3645 women. Of these 3645 women, 415 (11.4%) were aged <40 years, 1219 (33.4%) were aged 40–49 years, and 2011 (55.2%) were aged 50–74 years. Women aged <50 years were more likely to be recalled for microcalcifications than those aged 50–74 years (<40 years, 4.8%; 40–49 years, 4.3%; 50–74 years, 3.3%). Young women were more likely to be recalled for small round and segmental microcalcifications [<40 years, odds ratio (OR): 1.799 (95% CI: 0.751–2.846); 40–49 years, OR: 1.394 (95% CI: 0.714–2.074)] and less likely to be recalled for small round and grouped microcalcifications [<40 years, OR: 0.603 (95% CI: 0.181–1.025); 40–49 years, OR: 0.961 (95% CI: 0.496–1.428)] compared with women aged 50–74 years.Conclusions:On screening mammography, women aged <50 years had a higher tendency to be recalled for microcalcifications, particularly small round and segmental microcalcifications. False-positive results may be reduced by reflecting the characteristics of microcalcification findings among young women without breast cancer in the future.

Radiological, Histological and Chemical Analysis of Breast Microcalcifications: Diagnostic Value and Biological Significance.

Classification of mammary microcalcifications is based on radiological and histological characteristics that are routinely evaluated during the diagnostic path for the identification of breast cancer, or in patients at risk of developing breast cancer. The main aim of this study was to explore the relationship between the imaging parameters most commonly used for the study of mammary microcalcifications and the corresponding histological and chemical properties. To this end, we matched the radiographic characteristics of microcalcifications to breast lesion type, histology of microcalcifications and elemental composition of microcalcifications as obtained by energy dispersive x ray (EDX)-microanalysis. In addition, we investigated the properties of breast cancer microenvironment, under the hypothesis that microcalcification formation could result from a mineralization process similar to that occurring during bone osteogenesis. In this context, breast lesions with and without microcalcifications were compared in terms of the expression of the main molecules detected during bone mineralization (BMP-2, BMP-4, PTX3, RANKL OPN and RUNX2). Our data indicate that microcalcifications classified by mammography as "casting type" are prevalently made of hydroxyapatite magnesium substituted and are associated with breast cancer types with the poorest prognosis. Moreover, breast cancer cells close to microcalcifications expressed higher levels of bone mineralization markers as compared to cells found in breast lesions without microcalcifications. Notably, breast lesions with microcalcifications were characterized by the presence of breast-osteoblast-like cells. In depth studies of microcalcifications characteristics could support a new interpretation about the genesis of ectopic calcification in mammary tissue. Candidating this phenomenon as an integral part of the tumorigenic process therefore has the potential to improve the clinical management of patients early during their diagnostic path.

Sonographic features of papillary thyroid microcarcinoma predicting high-volume central neck lymph node metastasis

ObjectiveTo study the correlations between the sonographic features of papillary thyroid microcarcinoma (PTMC) and the presence of high-volume lymph node metastasis. MethodMedical records of 2363 PTMC patients were reviewed form October 2013 to December 2015. All the patients with lymph node metastasis identified by histopathology were included. Preoperative sonographic features, such as multifocality, tumour size, echogenicity, calcification, vascularity of papillary microcarcinoma, and capsule invasion, were recorded. Univariate and multivariate analyses were performed to investigate the relationships between sonographic features and high-volume lymph node metastasis (number of metastatic lymph nodes >5). ResultsIn total, 152 patients had high-volume central lymph node metastasis (6.4%, 152/2363). Multiple logistic regression analysis showed that the preoperative ultrasonic features of microcalcifications (OR = 3.33, p = 0.022), larger tumour size (>7 mm) (OR = 2.802, p < 0.001), and capsule invasion (OR = 2.141, p = 0.006) were independent risk factors for high-volume lymph node metastasis in the central compartment of PTMC. ConclusionThe sonographic features of primary papillary microcarcinoma of the thyroid are correlated with high-volume central lymph node metastasis.

Distribution patterns of microcalcifications in suspected thyroid carcinoma: a classification method helpful for diagnosis.

The aim of this study was to compare the distribution patterns of microcalcifications in thyroid cancers with benign cases. In total, 358 patients having microcalcifications on ultrasonography were analysed. Microcalcifications were categorised according to the distribution patterns: (I) microcalcifications inside one (a) or more (b) suspected nodules, (II) microcalcifications not only inside but also surrounding a suspected single (a) or multiple (b) nodules, and (III) focal (a) or diffuse (b) microcalcifications in the absence of any suspected nodule. Differences in distribution patterns of microcalcifications in benign and malignant thyroid lesions were compared. We found that the distribution patterns of microcalcifications differed between malignant (n = 325) and benign lesions (n = 117) (X 2 = 9.926, p < 0.01). Benign lesions were classified as type Ia (66.7%), type Ib (29.1%) or type IIIa (4.3%). The specificity of type II and type IIIb in diagnosing malignant cases was 100%. Among malignant lesions, 172 locations were classified as type Ia, 106 as type Ib, 12 as type IIa, 7 as IIb, 7 as type IIIa and 19 as type IIIb. Accompanying Hashimoto thyroiditis was most frequent in type III (51.6%). Types II and IIIb are highly specific for cancer detection. Microcalcifications outside a nodule and those detected in the absence of any nodule should therefore be reviewed carefully in clinical practice. • A method to classify distribution patterns of thyroid microcalcifications is presented. • Distribution features of microcalcifications are useful for diagnosing thyroid cancers. • Microcalcifications outside a suspicious nodule are highly specific for thyroid cancers. • Microcalcifications without suspicious nodules should also alert the physician to thyroid cancers.

A pure mucocele-like lesion of the breast diagnosed on ultrasonography-guided core-needle biopsy: is imaging follow-up sufficient?

Purpose:To evaluate the upgrade rate of ultrasonography (US)-guided core-needle biopsy (CNB) of the breast for a pure mucocele-like lesion (MLL), to evaluate the clinical and radiologic features, and to correlate the image-pathologic features further on to guide the management of MLL.Methods:Between January 2003 and February 2013, 14-gauge US-guided CNB was performed in 18,111 cases. Thirty-two cases associated with MLL were identified, and five cases of MLLs associated with breast carcinoma or with other high-risk breast lesions (i.e., atypical ductal hyperplasia [ADH], papillary lesions, lobular carcinoma in situ, and radial scar complex) were excluded. Among these 27 pure MLLs, 21 cases with surgical or vacuum-assisted excision (VAE) pathology were included in our study. Medical records, mammograms, and ultrasonograms were reviewed for the clinical and radiologic features of the cases.Results:Among the 21 cases with pure MLLs at CNB, the final pathology showed a 0% proportion of cases upgraded to malignancy. All the 21 cases with either surgical or VAE pathology were benign MLLs including three cases of focal involvement of ADH (14.3%). The common features were mammographic features of microcalcifications that were round in shape and had a grouped distribution. The US features included oval shape, circumscribed margin, parallel orientation, complex solid and cystic echo pattern, no posterior feature, and complex solid and cystic echoic masses. The predominant Breast Imaging Reporting and Data System (BIRADS) category was 4A. All the lesions showed image-pathologic concordance.Conclusion:For pure MLL on US-guided CNB with image-pathologic concordance, close imaging follow-up might be considered instead of surgical excision.

Retrieval Rate and Accuracy of Ultrasound-Guided 14-G Semi-Automated Core Needle Biopsy of Breast Microcalcifications

ObjectiveTo evaluate the retrieval rate and accuracy of ultrasound (US)-guided 14-G semi-automated core needle biopsy (CNB) for microcalcifications in the breast.Materials and MethodsUS-guided 14-G semi-automated CNB procedures and specimen radiography were performed for 33 cases of suspicious microcalcifications apparent on sonography. The accuracy of 14-G semi-automated CNB and radiology-pathology concordance were analyzed and the microcalcification characteristics between groups with successful and failed retrieval were compared.ResultsThirty lesions were successfully retrieved and the microcalcification retrieval rate was 90.9% (30/33). Thirty lesions were successfully retrieved. Twenty five were finally diagnosed as malignant (10 invasive ductal carcinoma, 15 ductal carcinoma in situ [DCIS]) and five as benign. After surgery and mammographic follow-up, the 25 malignant lesions comprised 12 invasive ductal carcinoma and 13 DCIS. Three lesions in the failed retrieval group (one DCIS and two benign) were finally diagnosed as two DCIS and one benign after surgery. The accuracy of 14-G semi-automated CNB was 90.9% (30/33) because of two DCIS underestimates and one false-negative diagnosis. The discordance rate was significantly higher in the failed retrieval group than in the successful retrieval group (66.7% vs. 6.7%; p < 0.05). Punctate calcifications were significantly more common in the failed retrieval group than in the successful retrieval group (66.7% vs. 3.7%; p < 0.05).ConclusionUS-guided 14-G semi-automated CNB could be a useful procedure for suspicious microcalcifications in the breast those are apparent on sonography.

Combining Feature Methods for Content-Based Classification of Mammogram Images

Breast cancer is among the leading cause of death among females. Studies show that early detection allows for a better prognosis. Mammography is one of the successful ways for early detection of breast cancer. It mostly involves manual reading of mammograms, a process that is difficult and error-prone. This paper discusses a classification model for mammograms based on microcalcification characteristics, as a way of helping radiologists make quick and accurate diagnostic decisions by availing to them similar past cases. The images are pre-processed by Gaussian smoothing and median filtering with 5 x 5 and 3 x 3 kernels respectively. Gabor and Haralick features are then extracted to form the image signatures over which similarity measurements are made. Experimental results show an average precision value between 0.5 and 0.61 using Haralick features, 0.49 and 0.57 using Gabor features, and 0.51 and 0.78 using combination of Gabor and Haralick features.

Downgrading BIRADS 3 to BIRADS 2 category using a computer-aided microcalcification analysis and risk assessment system for early breast cancer

This paper explores the potential of a computer-aided diagnosis system to discriminate the real benign microcalcifications among a specific subset of 109 patients with BIRADS 3 mammograms who had undergone biopsy, thus making it possible to downgrade them to BIRADS 2 category. The system detected and quantified critical features of microcalcifications and classified them on a risk percentage scale for malignancy. The system successfully detected all cancers. Nevertheless, it suggested biopsy for 11/15 atypical lesions. Finally, the system characterized as definitely benign (BIRADS 2) 29/88 benign lesions, previously assigned to BIRADS 3, and thus achieved a reduction of 33% in unnecessary biopsies.

Computer-Aided Diagnosis Scheme for Identifying Histological Classification of Clustered Microcalcifications by Use of Follow-up Magnification Mammograms

Our purpose in this study was to investigate the usefulness of follow-up magnification mammograms (i.e., both current and previous magnification mammograms) in a computer-aided diagnosis (CAD) scheme for identifying the histological classification of clustered microcalcifications. Our database consisted of current and previous magnification mammograms obtained from 93 patients before and after 3-month follow-up: 11 invasive carcinomas, 19 noninvasive carcinomas of the comedo type, 25 noninvasive carcinomas of the noncomedo type, 23 mastopathies, and 15 fibroadenomas. In our CAD scheme, we extracted five objective features of clustered microcalcifications from each of the current and previous magnification mammograms by taking into account image features that experienced radiologists commonly use to identify histological classifications. These features were then merged by a modified Bayes discriminant function for distinguishing among five histological classifications. For the input of the modified Bayes discriminant function, we used five objective features obtained from the previous magnification mammogram (previous features), five objective features obtained from the current magnification mammogram (current features), and the set of the five previous features and the five current features. The classification accuracies with the five current features were higher than those with the five previous features. These classification accuracies were improved substantially by using the set of the five previous features and the five current features. For the set of the five previous features and the five current features, the classification accuracies of our CAD scheme were 81.8% (9 of 11) for invasive carcinoma, 84.2% (16 of 19) for noninvasive carcinoma of the comedo type, 76.0% (19 of 25) for noninvasive carcinoma of the noncomedo type, 73.9% (17 of 23) for mastopathy, and 86.8% (13 of 15) for fibroadenoma. Our CAD scheme with use of follow-up magnification mammograms improved classification performance for mammographic clustered microcalcifications.

Adaptation of multifractal analysis to segmentation of microcalcifications in digital mammograms

A method for detecting microcalcifications in digital mammograms is proposed. After recognizing basic features of microcalcifications we introduced several modifications in multifractal analysis, obtaining an efficient method adapted to enhance only small light parts not belonging to surrounding tissue, possibly microcalcifications. Started with a mammogram image, a method creates corresponding multifractal image from which a radiologist has the freedom to change the level of segmentation in an interactive manner and to find suspicious regions, which may contain microcalcifications. Additional postprocessing, based on mathematical morphology, refines the procedure by selecting and outlining regions that contain clusters with microcalcifications. The proposed method was tested through referent mammograms from MiniMIAS database, which is available at public domain. The proposed method successfully extracted microcalcifications in all (clinically approved) cases belonging to this database.

Factores predictivos de malignidad en microcalcificaciones de mama sin lesiones asociadas

Screening mammography allows the early detection and treatment of nonpalpable carcinomas. Microcalcifications are highly important for the detection of many of these malignancies but are also present in benign breast disease. In the present study we analyzed the radiologic and clinical factors associated with malignancy. We retrospectively reviewed 133 patients who underwent open biopsy after a mammographic finding of microcalcifications without an associated lesion. Clinical and radiologic characteristics were correlated with histologic findings. A total of 28.6% of the lesions analyzed were malignant. Of these, 65.8% were ductal carcinoma in situ. Among invasive carcinomas, 23.1% presented lymph node metastasis. No clinical criterion was significant for malignancy. On univariate analysis six radiologic criteria were significant: morphologic type (Le Gal's classification), irregularity of size, irregularity of density, number of microcalcifications per cluster, diameter of the lesion, and the presence of more than one cluster. On multivariate analysis the factors with independent predictive value were: irregularity of density, > or = 10 microcalcifications per cluster, the presence of more than one cluster, and diameter of the cluster > or = 10 mm. Although none of the clinical factors analyzed was predictive for malignancy, the radiological characteristics of microcalcifications were determining factors in the indication for biopsy.