Search Results (351)

Breast cancer is the leading cause of cancer-related mortality among women world-wide, and early screening is critical for improving patient survival. Medical imaging plays a central role in breast cancer screening, diagnosis, and treatment monitoring. However, conventional imaging modalities—including mammography, ultrasound, and magnetic resonance imaging—face limitations such as low diagnostic specificity, relatively slow imaging speed, ionizing radiation exposure, and dependence on exogenous contrast agents. Photoacoustic imaging (PAI), a novel hybrid imaging technique that combines optical contrast with ultrasonic spatial resolution, has shown great promise in addressing these challenges. By revealing anatomical, functional, and molecular features of the breast tumor microenvironment, PAI offers high spatial resolution, rapid imaging, and minimal operator dependence. This review outlines the fundamental principles of PAI and systematically examines recent advances in its application to breast cancer screening, diagnosis, and therapeutic evaluation. Furthermore, we discuss the translational potential of PAI as an emerging breast imaging modality, complementing existing clinical techniques. Full article

Introduction: Breast density is a well-recognized factor in breast cancer risk assessment, with higher density linked to increased malignancy risk and reduced sensitivity of conventional mammography. Background parenchymal enhancement (BPE), observed in contrast-enhanced imaging, reflects physiological contrast uptake in non-pathologic breast tissue. While extensively characterized in breast MRI, the role of BPE in contrast-enhanced mammography (CEM) remains uncertain due to inconsistent findings regarding its correlation with breast density and cancer risk. Unlike breast density—standardized through the ACR BI-RADS lexicon—BPE lacks a uniform classification system in CEM, leading to variability in clinical interpretation and research outcomes. To address this gap, we introduce the BPE-CEM Standard Scale (BCSS), a structured four-tiered classification system specifically tailored to the two-dimensional characteristics of CEM, aiming to improve consistency and diagnostic alignment in BPE evaluation. Materials and Methods: In this retrospective single-center study, 213 patients who underwent mammography (MG), ultrasound (US), and contrast-enhanced mammography (CEM) between May 2022 and June 2023 at the “A. Perrino” Hospital in Brindisi were included. Breast density was classified according to ACR BI-RADS (categories A–D). BPE was categorized into four levels: Minimal (< 10% enhancement), Light (10–25%), Moderate (25–50%), and Marked (> 50%). Three radiologists independently assessed BPE in a subset of 50 randomly selected cases to evaluate inter-observer agreement using Cohen’s kappa. Correlations between BPE, breast density, and age were examined through regression analysis. Results: BPE was Minimal in 57% of patients, Light in 31%, Moderate in 10%, and Marked in 2%. A significant positive association was found between higher breast density (BI-RADS C–D) and increased BPE (p < 0.05), whereas lower-density breasts (A–B) were predominantly associated with minimal or light BPE. Regression analysis confirmed a modest but statistically significant association between breast density and BPE (R² = 0.144), while age showed no significant effect. Inter-observer agreement for BPE categorization using the BCSS was excellent (κ = 0.85; 95% CI: 0.78–0.92), supporting its reproducibility. Conclusions: Our findings indicate that breast density is a key determinant of BPE in CEM. The proposed BCSS offers a reproducible, four-level framework for standardized BPE assessment tailored to the imaging characteristics of CEM. By reducing variability in interpretation, the BCSS has the potential to improve diagnostic consistency and facilitate integration of BPE into personalized breast cancer risk models. Further prospective multicenter studies are needed to validate this classification and assess its clinical impact. Full article

Background and Objectives: The aim of our study was to assess the diagnostic accuracy of four imaging modalities—digital mammography (DM), digital breast tomosynthesis (DBT), ultrasound (US), and breast magnetic resonance imaging (MRI)—applied individually and in combination in early cancer detection in women with dense breasts. Methods: This single-center retrospective study was conducted from January 2021 to September 2024 at the Oncology Institute of Vojvodina in Serbia and included 168 asymptomatic and symptomatic women with dense breasts. Based on the exclusion criteria, the final number of women who were screened with all four imaging methods was 156. The reference standard for checking the diagnostic accuracy of these methods is the result of a histopathological examination, if a biopsy is performed, or a stable radiological finding in the next 12–24 months. Results: The findings underscore the superior diagnostic performance of breast MRI with the highest sensitivity (95.1%), specificity (78.7%), and overall accuracy (87.2%). In contrast, DM showed the lowest sensitivity (87.7%) and low specificity (49.3%). While the combination of DM + DBT + US demonstrated improved sensitivity to 96.3%, its specificity drastically decreased to 32%, illustrating as ensitivity–specificity trade-off. Notably, the integration of all four modalities increased sensitivity to 97.5% but decreased specificity to 29.3%, suggesting an overdiagnosis risk. DBT significantly improved performance over DM alone, likely due to enhanced tissue differentiation. US proved valuable in dense breast tissue but was associated with a high false-positive rate. Breast MRI, even when used alone, confirmed its status as the gold standard for dense breast imaging. However, its widespread use is constrained by economic and logistical barriers. ROC curve analysis further emphasized MRI’s diagnostic superiority (AUC = 0.958) compared with US (0.863), DBT (0.828), and DM (0.820). Conclusions: This study provides a unique, comprehensive comparison of all four imaging modalities within the same patient cohort, offering a rare model for optimizing diagnostic pathways in women with dense breasts. The findings support the strategic integration of complementary imaging approaches to improve early cancer detection while highlighting the risk of increased false-positive rates. In settings where MRI is not readily accessible, a combined DM + DBT + US protocol may serve as a pragmatic alternative, though its limitations in specificity must be carefully considered. Full article

Breast cancer accounts for one in four new malignant tumors in women, and misdiagnosis can lead to severe consequences, including delayed treatment. Among patients classified with a BI-RADS 3 rating, the risk of very early-stage malignancy remains over 2%. However, due to the benign imaging characteristics of these lesions, radiologists often recommend follow-up rather than immediate biopsy, potentially missing critical early interventions. This study aims to develop a deep learning (DL) model to accurately identify very early-stage malignancies in BI-RADS 3 lesions using ultrasound (US) images, thereby improving diagnostic precision and clinical decision-making. A total of 852 lesions (256 malignant and 596 benign) from 685 patients who underwent biopsies or 3-year follow-up were collected by Southwest Hospital (SW) and Tangshan People’s Hospital (TS) to develop and validate a deep learning model based on a novel transfer learning method. To further evaluate the performance of the model, six radiologists independently reviewed the external testing set on a web-based rating platform. The proposed model achieved an area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of 0.880, 0.786, and 0.833 in predicting BI-RADS 3 malignant lesions in the internal testing set. The proposed transfer learning method improves the clinical AUC of predicting BI-RADS 3 malignancy from 0.721 to 0.880. In the external testing set, the model achieved AUC, sensitivity, and specificity of 0.910, 0.875, and 0.786 and outperformed the radiologists with an average AUC of 0.653 (p = 0.021). The DL model could detect very early-stage malignancy of BI-RADS 3 lesions in US images and had higher diagnostic capability compared with experienced radiologists. Full article

Background and Objectives: The accuracy of breast cancer diagnosis depends on the concordance between imaging features and pathological findings. While BI-RADS (Breast Imaging Reporting and Data System) provides standardized risk stratification, its correlation with histologic grade and immunohistochemical markers remains underexplored. This study assessed the diagnostic performance of BI-RADS 3, 4, and 5 classifications and their association with tumor grade and markers such as ER, PR, HER2, and Ki-67. Materials and Methods: In this prospective study, 67 women aged 33–82 years (mean 56.4) underwent both mammography and ultrasound. All lesions were biopsied using ultrasound-guided 14G core needles. Imaging characteristics (e.g., margins, echogenicity, calcifications), histopathological subtype, and immunohistochemical data were collected. Statistical methods included logistic regression, Chi-square tests, and Spearman’s correlation to assess associations between BI-RADS, histology, and immunohistochemical markers. Results: BI-RADS 5 lesions showed a 91% malignancy rate. Evaluated features included spiculated margins, pleomorphic microcalcifications, and hypoechoic masses with posterior shadowing, and were correlated with histological and immunohistochemical results. Invasive tumors typically appeared as irregular, hypoechoic masses with posterior shadowing, while mucinous carcinomas mimicked benign features. Higher BI-RADS scores correlated significantly with increased Ki-67 index (ρ = 0.76, p < 0.001). Logistic regression yielded an AUC of 0.877, with 93.8% sensitivity and 80.0% specificity. Conclusions: BI-RADS scoring effectively predicts malignancy and correlates with tumor proliferative markers. Integrating imaging, histopathology, and molecular profiling enhances diagnostic precision and supports risk-adapted clinical management in breast oncology. Full article

Background: A breast hamartoma or fibroadenolipoma is a rare, benign mass consisting of disorganized mature breast tissue elements. Surgical excision is recommended if the lesion exhibits rapid progressive growth. However, incomplete excision may result in recurrence. The objective of this study is to provide comprehensive insights into the characteristics of breast hamartomas and to conduct a thorough investigation into their clinical presentation, diagnostic procedures, and management strategies. Methods: We report on 13 cases of breast hamartomas treated surgically between January 2018 and June 2023 at the Obstetrics and Gynecology Hospital “Cuza Vodă” in Iași. We analyzed their histological images and immunohistochemical evaluations. Results: The mean age of the patients was 33.35 years, ranging from 22 to 57 years. Clinically, all patients presented with a painless mass. The diagnosis was confirmed through ultrasound examination, which revealed that hamartomas appeared as well-circumscribed, oval, and heterogeneous in echotexture. The tumor sizes ranged from 1 to 17 cm, with an average size of 6.75 cm. Surgical treatment involved lumpectomy with the excision of a small portion of normal tissue surrounding the tumor. The histological variability of these tumors poses diagnostic challenges for pathologists, potentially leading to underdiagnosis. Conclusions: Most hamartomas exhibit characteristic features on ultrasound attributable to their fibrous, glandular, and adipose tissue composition. Accurate identification of hamartomas is crucial due to the potential for recurrence. Notably, none of the women in our study experienced recurrence during the follow-up period. Full article

Background/Objectives: Accurately correlating mammographic findings with corresponding histopathologic features is considered one of the essential aspects of mammographic evaluation, guiding the next steps in cancer management and preventing overdiagnosis. The objective of this study was to evaluate patterns of mammographic microcalcifications and their association with histopathological findings related to various breast tumors. Methods: 110 out of 3603 women had microcalcification of BIRADS 3 or higher and were subjected to stereotactic/ultrasound (USG) guided biopsies, and hook-wire localization excision procedures. Ultrasound and mammography images were reviewed by experienced radiologists using the standard American College of Radiology Breast-Imaging Reporting and Data System (ACR BI-RADS). Results: Our study showed that features with a high positive predictive value (PPV) of breast malignancy were heterogeneous (75%), fine linear/branching pleomorphic microcalcifications (66.7%), linear (100%), and segmental distributions (57.1%). Features that showed a higher risk of association with ductal carcinoma in situ (DCIS) were fine linear/branching pleomorphic (odds ratio (OR): 3.952), heterogeneous microcalcifications (OR: 3.818), segmental (OR: 5.533), linear (OR: 3.696), and regional (OR: 2.929) distributions. Furthermore, the features with higher risks associated with invasive carcinoma had heterogeneous (OR: 2.022), fine linear/branching pleomorphic (OR: 1.187) microcalcifications, linear (OR: 6.2), and regional (OR: 2.543) distributions. The features of associated masses in mammograms that showed a high PPV of malignancy had high density (75%), microlobulation (100%), and spiculated margins (75%). Conclusions: We concluded that specific patterns and distributions of microcalcifications were indeed associated with a higher risk of malignancy. Those with fine linear or branching pleomorphic and segmental distribution were at a higher risk of DCIS, whereas those with heterogeneous morphology with a linear distribution were at a higher risk of invasive carcinoma. Full article

Background/Objectives: Higher percent body fat (BF) is associated with worse outcomes after treatment for breast cancer (BC). While ultrasound (US) imaging is a reliable method for analyzing body composition, it requires trained individuals for utilization. As such, bioelectrical impedance analysis (BIA) has been suggested as an alternative. Therefore, the goal of this study was to compare BIA with US. Methods: Women from three prospective exercise BC studies were analyzed with US and BIA before an exercise intervention. Spearman’s correlation was used as a nonparametric measure to examine bivariate relationships between percent body fat measured by BIA and US. Results: In total, 106 women with BC had their body composition measured using both US and BIA. Despite a strong correlation between the two methods (r = 0.8, p < 0.01), US reported lower mean percent BF vs. BIA (34.6 ± 0.7% vs. 38.0 ± 0.8%, p < 0.01). In a subgroup analysis, concordance was seen in women with a body mass index below (BMI) ≤ 26 kg/m². BIA overreported percent BF compared to US in women with a BMI > 26 kg/m². Conclusions: In women with BC and BMI ≤ 26, US and BIA are in concordance when measuring BF. In women with a BMI > 26, BIA reports a higher BF than US. Overall, there was a strong correlation between modalities, while BMI can be used to guide the utilization of BIA as an alternative to US for assessing body composition. Full article

In this article, we present a case of a 49-year-old woman presenting with a recurrent metastatic neuroendocrine tumor. Background: Insulinomas are neuroendocrine tumors derived from beta cells of the pancreas that secrete insulin. Usually, they are benign tumors; however, metastatic insulinomas are an extremely rare malignant form of these tumors, carrying a significantly worse prognosis. Case Presentation: A 49-year-old woman, a patient in the University Hospital in Wroclaw in the Department of Endocrinology, Diabetes and Isotope Therapy, first presented with abdominal pain in 2009, when ultrasound and further examination led to the diagnosis of a tumor in the pancreas (a solid pseudopapillary tumor of the pancreas—meta NET G2), and the patient underwent distal pancreatectomy with splenectomy. For ten years, she was under observation, and her symptoms, such as abdominal pain, nausea, weight loss, and general weakness, reappeared in 2019. Then, magnetic resonance imaging (MRI) showed a lesion in the liver, and further histopathology revealed neuroendocrine tumor (NET) metastasis to the liver. In 2022, the patient presented with loss of consciousness and convulsion, loss of weight, and hypoglycemia after meals. In April 2022, the daily glycemic profile was recorded and a 72 h fasting test was performed; however, their results excluded insulinoma. Positron emission tomography–computed tomography (PET-CT) with 18F-fluorodeoxyglucose (18F-FDG) and PET with gallium-68-DOTA-(Tyr3)-octreotate (68Ga-DOTA-TATE) showed a metastatic proliferative process in the liver. Persistent hypoglycemia led to another hospitalization in May 2022, and repeated tests allowed for the diagnosis of insulinoma. Treatment with somatostatin analogs and diazoxide was started. A CT scan in November 2022 and a PET scan in January 2023 showed new metastases to the liver, bones, and cervical lymph nodes, and it was decided to intensify the treatment. In May 2023, the patient was qualified for Lutathera treatment for insulinoma at the University Clinical Hospital in Poznań. In June 2023, another disturbing symptom was reported by the patient, a painful lump in the breast. During diagnostics, metastases with high proliferation markers were found in both breasts. Two months later, in August 2023, the patient received another dose of Lutathera. In October 2023, significant progression of liver lesions, metastases to bones of the spine, ribs, and pelvis, and periaortic and pelvic lymphadenopathy were found as well as elevated values of neuron-specific enolase and calcitonin. The patient was also referred to the Palliative Medicine Home Hospice. In consultation with the Lower Silesian Cancer Center, the decision was made to forgo further treatment with PRRT and initiate systemic chemotherapy. Despite the chosen treatment, the patient died on 27/DEC/2023. Conclusions: This case report can serve clinicians, as it presents a case of an extremely rare and insidious tumor, metastatic insulinoma. Full article

The ACOSOG Z0011 and IBCSG 23-01 trials demonstrated that axillary lymph node dissection (ALND) offers no prognostic benefit in breast cancer patients with clinically negative axillae and low disease burden (one to two positive nodes) on sentinel lymph node biopsy (SLNB). However, uncertainty remains regarding the management of patients with clinically negative axillae (cN0) who are found to have suspicious lymph nodes on imaging that are subsequently confirmed positive by biopsy. The current practice often directs these patients to upfront ALND, potentially exposing them to unnecessary surgical morbidity. This study aimed to assess the role of axillary ultrasound in predicting high axillary nodal burden and guiding surgical management. Using the Alberta Cancer Registry, we identified 107 cN0 breast cancer patients from 2010 to 2017 who underwent preoperative axillary ultrasound with positive biopsy followed by ALND. Our findings reveal that 42% of these patients had low axillary nodal burden on final pathology, meeting Z0011 criteria, and might potentially have avoided ALND. Furthermore, axillary ultrasound findings were not predictive of high axillary burden. These results highlight that many patients undergoing upfront ALND based on positive ultrasound-guided biopsy could benefit from SLNB alone. This supports the 2023 NCCN guidelines advocating for more selective use of ALND to minimize overtreatment and associated morbidity. Full article

Background/Objectives: Granular cell tumors (GCTs) are rare neurogenic tumors with Schwann cell differentiation. Although most are benign, 1–2% exhibit malignant behavior. The imaging features of GCTs remain poorly characterized due to their rarity and anatomic variability. This study aims to elucidate the manifestations of GCTs in multimodal imaging across different anatomic locations. Methods: We retrospectively analyzed 66 histopathologically confirmed GCT cases (2011–2024), assessing their clinical presentations, pathological characteristics, and imaging findings from ultrasound (n = 31), CT (n = 14), MRI (n = 8), and endoscopy (n = 15). Two radiologists independently reviewed the imaging features (location, size, morphology, signal/density, and enhancement). Results: The cohort (mean age: 42 ± 12 years; 72.7% female) showed tendency in location towards soft tissue (48.4%), the digestive tract (30.3%), the respiratory system (7.6%), the breasts (7.6%), and the sellar region (6.1%). Six cases (9.1%) were malignant. The key imaging findings by modality were as follows: Ultrasound: Well-circumscribed hypoechoic masses in soft tissue (96.1%) and irregular margins in the breasts (80%, BI-RADS 4B) were found. MRI: The sellar GCTs exhibited T1-isointensity, variable T2-signals (with 50% showing “star-like crack signs”), and heterogeneous enhancements. The soft tissue GCTs were T1-hypointense (75%) with variable T2-signals. CT: Pulmonary/laryngeal GCTs appeared as well-defined hypodense masses with mild/moderate enhancements. Endoscopy: Submucosal/muscularis hypoechoic nodules with smooth surfaces were found. Malignant GCTs were larger (mean: 93 mm vs. 30 mm) but lacked pathognomonic imaging features. Three malignant cases demonstrated metastases. Conclusions: GCTs exhibit distinct imaging patterns based on their anatomical location. While certain features (e.g., star-like crack signs) are suggestive, imaging cannot reliably differentiate benign from malignant variants. Histopathological confirmation remains essential to diagnosis, particularly given the potential for malignant transformations (at 9.1% in our series). Multimodal imaging guides the localization and biopsy planning, but clinical–radiological–pathological correlation is crucial for the optimal management. Full article

Background/Objectives: Accurate assessment of tumor response to neoadjuvant chemotherapy (NAC) in breast cancer is critical for optimizing treatment strategies. While magnetic resonance imaging (MRI) and mammography are commonly used for response evaluation, they have inherent limitations. Ultrasound (US) has emerged as a promising, cost-effective, and real-time alternative. This study aimed to evaluate the effectiveness of US in tracking tumor regression during NAC and its correlation with pathologic tumor regression grade (TRG). Methods: This study included 282 breast cancer patients undergoing NAC. Tumor size was measured using ultrasound at three key time points: pre-chemotherapy, after four cycles, and post-chemotherapy. Spearman’s correlation was used to assess the relationship between US-measured tumor changes and TRG. Multinomial logistic regression and receiver operating characteristic (ROC) curve analyses were performed to determine the predictive accuracy of the measurements from our US in identifying pathologic complete response (pCR). Conclusions: Ultrasound is a reliable, real-time imaging tool for monitoring NAC response in breast cancer patients. Its ability to predict pCR and track tumor shrinkage highlights its potential for treatment adaptation. Standardization of US protocols and integration with AI-based analysis may further improve its clinical utility, making it a valuable adjunct in breast cancer treatment monitoring. Full article

Background: The superficial vessel system in the lower abdomen, including the superficial circumflex iliac artery (SCIA) and superficial inferior epigastric artery (SIEA), is widely used in reconstructive microsurgery. Preoperative ultrasonography, particularly ultra-high-frequency ultrasound (UHFUS), enhances surgical planning by providing high-resolution imaging. This study aimed to utilize UHFUS to examine the SCIA, SCIV, SIEA, and SIEV for reconstructive surgery planning. Methods: This prospective study included 25 patients undergoing free DIEP flap breast reconstruction. Patients with horizontal lower abdominal scars were excluded. Preoperative UHFUS, using a 48 MHz transducer, was performed to map and measure the superficial branch of SCIA (sSCIA), SCIV, SIEA, and SIEV. The vessel location, diameter, depth, and course were documented and analyzed. Results: Twenty-five female patients (50 hemiabdomens) aged 41 to 66 were included. The mean BMI was 21.6 kg/m² (range: 18.4–30.4 kg/m²). At the ASIS level, the mean diameter of the sSCIA, SIEA, SCIV, and SIEV were 0.76 mm, 0.63 mm, 1.72 mm, and 2.18 mm, respectively. A superior lateral pedicle course was observed in 98% of the sSCIA. All patients had at least one detectable superficial artery, with 96% showing detectable arteries on both sides of the lower abdomen. Conclusions: UHFUS effectively maps superficial vessels in the lower abdomen for reconstructive surgery. The SCIA and SCIV are reliably detectable, while the SIEA is less consistently identified. UHFUS enhances flap design by providing precise vessel localization and sizing, leading to safer and more efficient surgeries. Full article

Breast cancer remains one of the leading causes of death among women globally. Early detection is critical for improving patient outcomes, making the development of accurate and efficient detection methods essential for facilitating timely treatment and enhancing patients’ quality of life. Lesion sites are often associated with localized temperature increases, which can be identified by characterizing thermal gradients using thermometry tools. Ultrasound-based techniques are preferred for obtaining thermal patterns due to their noninvasive, non-ionizing nature and cost-effectiveness compared to methods like magnetic resonance imaging. This study focuses on developing breast tissue models with varying acoustic properties, specifically the speed of sound across temperatures ranging from 32 °C to 36 °C in increments of 0.5 °C for ultrasonic inspection and diagnostic applications. These models simulate healthy and tumorous breast tissue, including the fat, gland, and tumor layers. Signal variations were analyzed using cross-correlation methods to assess the changes in the speed of sound as a function of temperature. The proposed methodology offers a cost-effective, rapid, and precise approach to phantom production, facilitating the detection of temperature changes in 0.5 °C intervals through cross-correlation analysis of the acquired signals. Full article

Previous work has demonstrated quantitative ultrasound (QUS) analysis techniques for extracting features and texture features from ultrasound radiofrequency data which can be used to distinguish between benign and malignant breast masses. It is desirable that there be good agreement between estimates of such features acquired using different ultrasound devices. Handheld ultrasound imaging systems are of particular interest as they are compact, relatively inexpensive, and highly portable. This study investigated the agreement between QUS parameters and texture features estimated from clinical ultrasound images of breast tumors acquired using two different ultrasound scanners: a traditional cart-based system and a wireless handheld ultrasound system. The 28 patients who participated were divided into two groups (benign and malignant). The reference phantom technique was used to produce functional estimates of the normalized power spectra and backscatter coefficient for each image. Root mean square differences of feature estimates were calculated for each cohort to quantify the level of feature variation attributable to tissue heterogeneity and differences in system imaging parameters. Cross-system statistical testing using the Mann–Whitney U test was performed on benign and malignant patient cohorts to assess the level of feature estimate agreement between systems, and the Bland–Altman method was employed to assess feature sets for systematic bias introduced by differences in imaging method. The range of p-values was 1.03 × 10⁻⁴ to 0.827 for the benign cohort and 3.03 × 10⁻¹⁰ to 0.958 for the malignant cohort. For both cohorts, all five of the primary QUS features (MBF, SS, SI, ASD, AAC) were found to be in agreement at the 5% confidence level. A total of 13 of the 20 QUS texture features (65%) were determined to exhibit statistically significant differences in the sample medians of estimates between systems at the 5% confidence level, with the remaining 7 texture features being in agreement. The results showed a comparable magnitude of feature variation between tissue heterogeneity and system effects, as well as a moderate level of statistical agreement between feature sets. Full article