Characterisation of breast papillary neoplasm on automated breast ultrasound.
Ontology highlight
ABSTRACT:
SUBMITTER: Zhu QL
PROVIDER: S-EPMC3755396 | biostudies-other | 2013 Sep
REPOSITORIES: biostudies-other
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Project description:BACKGROUND:Our aims were to determine if features derived from texture analysis (TA) can distinguish normal, benign, and malignant tissue on automated breast ultrasound (ABUS); to evaluate whether machine learning (ML) applied to TA can categorise ABUS findings; and to compare ML to the analysis of single texture features for lesion classification. METHODS:This ethically approved retrospective pilot study included 54 women with benign (n = 38) and malignant (n = 32) solid breast lesions who underwent ABUS. After manual region of interest placement along the lesions' margin as well as the surrounding fat and glandular breast tissue, 47 texture features (TFs) were calculated for each category. Statistical analysis (ANOVA) and a support vector machine (SVM) algorithm were applied to the texture feature to evaluate the accuracy in distinguishing (i) lesions versus normal tissue and (ii) benign versus malignant lesions. RESULTS:Skewness and kurtosis were the only TF significantly different among all the four categories (p < 0.000001). In subsets (i) and (ii), a maximum area under the curve of 0.86 (95% confidence interval [CI] 0.82-0.88) for energy and 0.86 (95% CI 0.82-0.89) for entropy were obtained. Using the SVM algorithm, a maximum area under the curve of 0.98 for both subsets was obtained with a maximum accuracy of 94.4% in subset (i) and 90.7% in subset (ii). CONCLUSIONS:TA in combination with ML might represent a useful diagnostic tool in the evaluation of breast imaging findings in ABUS. Applying ML techniques to TFs might be superior compared to the analysis of single TF.
| S-EPMC6825080 | biostudies-literature
Project description:Digital breast tomosynthesis (DBT) offers poor image quality along the depth direction. This paper presents a new method that improves the image quality of DBT considerably through the a priori information from automated ultrasound (AUS) images.DBT and AUS images of a complex breast-mimicking phantom are acquired by a DBT/AUS dual-modality system. The AUS images are taken in the same geometry as the DBT images and the gradient information of the in-slice AUS images is adopted into the new loss functional during the DBT reconstruction process. The additional data allow for new iterative equations through solving the optimization problem utilizing the gradient descent method. Both visual comparison and quantitative analysis are employed to evaluate the improvement on DBT images. Normalized line profiles of lesions are obtained to compare the edges of the DBT and AUS-corrected DBT images. Additionally, image quality metrics such as signal difference to noise ratio (SDNR) and artifact spread function (ASF) are calculated to quantify the effectiveness of the proposed method.In traditional DBT image reconstructions, serious artifacts can be found along the depth direction (Z direction), resulting in the blurring of lesion edges in the off-focus planes parallel to the detector. However, by applying the proposed method, the quality of the reconstructed DBT images is greatly improved. Visually, the AUS-corrected DBT images have much clearer borders in both in-focus and off-focus planes, fewer Z direction artifacts and reduced overlapping effect compared to the conventional DBT images. Quantitatively, the corrected DBT images have better ASF, indicating a great reduction in Z direction artifacts as well as better Z resolution. The sharper line profiles along the Y direction show enhancement on the edges. Besides, noise is also reduced, evidenced by the obviously improved SDNR values.The proposed method provides great improvement on the quality of DBT images. This improvement makes it easier to locate and to distinguish a lesion, which may help improve the accuracy of the diagnosis using DBT imaging.
| S-EPMC4032424 | biostudies-other
Project description:Adrenal oncocytoma (AO) is an extremely rare adrenocortical neoplasm and little is known about its malignant potential, secretory properties, and hereditary origin. We present the case of a benign AO with concomitant incidentally found papillary thyroid cancer (PTC) and review similar cases in the literature. Immunohistochemistry and next-generation sequencing (NGS) were performed. A 66-year-old women was incidentally found to have a large, androgen-secreting right adrenal mass. 18F-Fluorodeoxyglucose positron emission tomography showed intense uptake (SUVmax 88.7) of this mass and found a hypermetabolic right thyroid mass. Open adrenalectomy was performed for this highly suspicious adrenal mass. Histopathology revealed benign AO that was BRAFV600E negative, with low Ki-67, and no somatic mutation found on NGS. Thyroidectomy revealed invasive, BRAFV600E-positive PTC. At 6?months follow-up, androgen levels returned to normal, and no recurrence was seen on imaging. To our knowledge, this is the first report of an androgen-secreting AO with concomitant PTC. Possibly the simultaneous discovery of two independent neoplasms was observed. In conclusion, this case highlights that care should be given to exclude concomitant neoplasms. Long-term and regular imaging with biochemical follow-up is warranted, since the outcome and clinical behavior of AO remains uncertain.
| S-EPMC5786566 | biostudies-literature
Project description:PURPOSE:To develop and evaluate the accuracy of a three-dimensional (3D) US method for assessing unilateral breast reconstruction and discuss the feasibility of breast ultrasound 3D reconstruction of the unilateral breast compared with 3D MRI. METHODS:Sixty-four breast lesions were collected for surgical resection. (1) MRI and US imaging were used to reconstruct the 3D models of the breast neoplasm. The diameters for maximum length, width, and depth of the negative tumor margins were used as the primary standards for comparison. (2) The measurement direction was determined by the largest gravity change between the two body positions. (3) The vertical distance from the midpoint of breast neoplasm to the ipsilateral nipple was calculated via MRI and US reconstruction. RESULTS:(1) Comparison of the measured size and histopathology of the breast neoplasm showed that US, MRI, and histopathology were highly correlated (p?<?0.001). (2) When compared with the other two vertical directions, the direction with the largest gravity change had the greatest difference between MRI and US measurements. (3) The vertical distance from the breast neoplasm to the ipsilateral nipple and skin junction was significantly different (p?>?0.05). CONCLUSIONS:We have presented a novel US 3D reconstruction method for evaluating tumor size, which can provide a basis for investigated advanced visualization techniques for assessing breast tissue such as holographic presentation of 3D image data. These methods can provide physicians with a novel approach for making accurate surgical plans, for better communication with patients, and for more effective navigating throughout the operation.
| S-EPMC6548752 | biostudies-literature
Project description:Photoacoustic tomography (PAT) is a promising emergent modality for the screening and staging of breast cancer. To minimize barriers to clinical translation, it is common to develop PAT systems based upon existing ultrasound hardware, which can entail significant design challenges in terms of light delivery. This often results in inherently non-uniform fluence within the tissue and should be accounted for during image reconstruction. We aim to integrate PAT into an automated breast ultrasound scanner with minimal change to the existing system. We designed and implemented an illuminator that directs spatially non-uniform light to the tissue near the acquisition plane of the imaging array. We developed a graphics processing unit-accelerated reconstruction method, which accounts for this illumination geometry by modeling the structure of the light in the sample. We quantified the performance of this system using a custom, modular photoacoustic phantom and graphite rods embedded in chicken breast tissue. Our illuminator provides a fluence of 2.5 mJ cm - 2 at the tissue surface, which was sufficient to attain a signal-to-noise ratio (SNR) of 8 dB at 2 cm in chicken breast tissue and image 0.25-mm features at depths of up to 3 cm in a medium with moderate optical scattering. Our reconstruction scheme is 200 × faster than a CPU implementation; it provides a 25% increase in SNR at 2 cm in chicken breast tissue and lowers image error by an average of 31% at imaging depths >1.5 cm compared with a method that does not account for the inhomogeneity of the illumination or the transducer directivity. A fan-shaped illumination geometry is feasible for PAT; however, it is important to account for non-uniform fluence in illumination scenarios such as this. Future work will focus on increasing fluence and further optimizing the ultrasound hardware to improve SNR and overall image quality.
| S-EPMC7675066 | biostudies-literature
Project description:Intraductal papillary mucinous neoplasms are classified into gastric, intestinal, pancreatobiliary, and oncocytic subtypes where morphology portends disease prognosis. The study aim was to demonstrate EUS-guided needle-based confocal laser endomicroscopy imaging features of intraductal papillary mucinous neoplasm subtypes. Four subjects, each with a specific intraductal papillary mucinous neoplasm subtype were enrolled. An EUS-guided needle-based confocal laser endomicroscopy miniprobe was utilized for image acquisition. The mean cyst size from the 4 subjects (2 females; mean age = 65.3±12 years) was 36.8±12 mm. All lesions demonstrated mural nodules and focal dilation of the main pancreatic duct. EUS-nCLE demonstrated characteristic finger-like papillae with inner vascular core for all subtypes. The image patterns of the papillae for the gastric, intestinal, and pancreatobiliary subtypes were similar. However, the papillae in the oncocytic subtype were thick and demonstrated a fine scale-like or honeycomb pattern with intraepithelial lumina correlating with histopathology. There was significant overlap in the needle-based confocal laser endomicroscopy findings for the different intraductal papillary mucinous neoplasm subtypes; however, the oncocytic subtype demonstrated distinct patterns. These findings need to be replicated in larger multicenter studies.
| S-EPMC5558896 | biostudies-literature
Project description:PurposeMammography, the standard method of breast cancer screening, misses many cancers, especially in dense-breasted women. We compared the performance and diagnostic yield of mammography alone versus an automated whole breast ultrasound (AWBU) plus mammography in women with dense breasts and/or at elevated risk of breast cancer.MethodsAWBU screening was tested in 4,419 women having routine mammography (Trial registrationClinicalTrials.gov Identifier: NCT00649337). Cancers occurring during the study and subsequent 1-year follow-up were evaluated. Sensitivity, specificity and positive predictive value (PPV) of biopsy recommendation for mammography alone, AWBU and mammography with AWBU were calculated.ResultsBreast cancer detection doubled from 23 to 46 in 6,425 studies using AWBU with mammography, resulting in an increase in diagnostic yield from 3.6 per 1,000 with mammography alone to 7.2 per 1,000 by adding AWBU. PPV for biopsy based on mammography findings was 39.0% and for AWBU 38.4%. The number of detected invasive cancers 10 mm or less in size tripled from 7 to 21 when AWBU findings were added to mammography.ConclusionAWBU resulted in significant cancer detection improvement compared with mammography alone. Additional detection and the smaller size of invasive cancers may justify this technology's expense for women with dense breasts and/or at high risk for breast cancer.
| S-EPMC2822222 | biostudies-literature
Project description:BackgroundMixed neuroendocrine-non-neuroendocrine neoplasms (MiNEN) of the pancreas are extremely rare. Their pathogenesis and molecular landscape are largely unknown. Here, we report a case of mixed pancreatic intraductal papillary mucinous neoplasm (IPMN) and well-differentiated neuroendocrine tumor (NET) and identify its genetic alterations by next-generation sequencing (NGS).Case presentationA fifty-year-old male was admitted into the hospital for evaluation of a pancreatic lesion detected during a routine examination. Abdominal ultrasound indicated a hypoechoic mass of 2.6 cm at the head of the pancreas. Malignancy was suspected and partial pancreatectomy was performed. Thorough histopathological examination revealed a mixed IPMN-NET. In some areas, the two components were relatively separated, whereas in other areas IPMN and NET grew in a composite pattern: The papillae were lined with epithelial cells of IPMN, and there were clusters of NET nests in the stroma of papillary axis. NGS revealed shared somatic mutations (KRAS, PCK1, MLL3) in both components. The patient has been uneventful 21 months after the surgery.ConclusionsOur case provides evidence of a common origin for mixed IPMN-NET with composite growth features. Our result and literature review indicate that KRAS mutation might be a driver event underlying the occurrence of MiNEN. We also recommend the inclusion of mixed non-invasive exocrine neoplasms and neuroendocrine neoplasms into MiNEN.
| S-EPMC8606070 | biostudies-literature
Project description:Recent studies have reported high frequencies of somatic mutations in the phosphoinositide-3-kinase catalytic-alpha (PIK3CA) gene in various human solid tumors. More than 75% of those somatic mutations are clustered in the helical (exon 9) and kinase domains (exon 20). The three hot-spot mutations, E542K, E545K, and H1047R, have been proven to elevate the lipid kinase activity of PIK3CA and activate the Akt signaling pathway. The mutational status of PIK3CA in intraductal papillary mucinous neoplasm/carcinoma (IPMN/IPMC) has not been evaluated previously.To evaluate a possible role for PIK3CA in the tumorigenesis of IPMN and IPMC, exons 1, 4, 5, 6, 7, 9, 12, 18, and 20 were analyzed in 36 IPMN/IPMC and two mucinous cystadenoma specimens by direct genomic DNA sequencing.We identified four missense mutations in the nine screened exons of PIK3CA from 36 IPMN/IPMC specimens (11%). One of the four mutations, H1047R, has been previously reported as a hot-spot mutation. The remaining three mutations, T324I, W551G, and S1015F, were novel and somatic.This is the first report of PIK3CA mutation in pancreatic cancer. Our data provide evidence that the oncogenic properties of PIK3CA contribute to the tumorigenesis of IPMN/IPMC.
| S-EPMC1780026 | biostudies-literature
Project description:ObjectiveEarly assessment of response to neoadjuvant chemotherapy (NAC) for breast cancer allows therapy to be individualized. The optimal assessment method has not been established. We investigated the accuracy of automated breast ultrasound (ABUS) to predict pathological outcomes after NAC.MethodsA total of 290 breast cancer patients were eligible for this study. Tumor response after 2 cycles of chemotherapy was assessed using the product change of two largest perpendicular diameters (PC) or the longest diameter change (LDC). PC and LDC were analyzed on the axial and the coronal planes respectively. Receiver operating characteristic (ROC) curves were used to evaluate overall performance of the prediction methods. Youden's indexes were calculated to select the optimal cut-off value for each method. Sensitivity, specificity, positive and negative predictive values (PPV and NPV) and the area under the ROC curve (AUC) were calculated accordingly.ResultsypT0/is was achieved in 42 patients (14.5%) while ypT0 was achieved in 30 patients (10.3%) after NAC. All four prediction methods (PC on axial planes, LDC on axial planes, PC on coronal planes and LDC on coronal planes) displayed high AUCs (all>0.82), with the highest of 0.89 [95% confidence interval (95% CI), 0.83-0.95] when mid-treatment ABUS was used to predict final pathological complete remission (pCR). High sensitivities (85.7%-88.1%) were observed across all four prediction methods while high specificities (81.5%-85.1%) were observed in two methods used PC. The optimal cut-off values defined by our data replicate the WHO and the RECIST criteria. Lower AUCs were observed when mid-treatment ABUS was used to predict poor pathological outcomes.ConclusionsABUS is a useful tool in early evaluation of pCR after NAC while less reliable when predicting poor pathological outcomes.
| S-EPMC5101221 | biostudies-literature