Search Results (29)

Background/Objectives: The iBreast Exam (iBE) electronically palpates the breast to identify possible abnormalities. The purpose of this study was to assess iBE feasibility and compare it to Clinical Breast Exam (CBE) for breast lesion detection. Methods: Prospective evaluation of 300 asymptomatic women, ≥18 years old, with CBE, iBE, and mammography was performed. Sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV) of iBE and CBE for detecting suspicious breast lesions were calculated using breast imaging as the reference standard. For women with one year follow up, the sensitivity, specificity, PPV, and NPV for cancer detection were calculated. Results: 300 women (mean age 58.9 years) underwent CBE, iBE, and mammography. In 2/300 (0.7%), CBE was positive; in 1/300 (0.3%), iBE was positive; and in 24/300 (8%), screening mammograms were positive. Nine had suspicious imaging findings with biopsy (three malignant and six benign). Of three cancers, all visualized mammographically, CBE and iBE detected an ipsilateral breast abnormality in one woman and missed two cancers (<2 cm). Sensitivity, specificity, NPV, and PPV of iBE and CBE were similar, with no statistically significant difference in NPV or PPV for detection of suspicious breast findings or breast cancer (p > 0.05). Conclusions: Mammography detected all breast cancers in our cohort and remains the standard of care. iBE is feasible to perform. Our pilot data demonstrates iBE performed similarly to CBE by trained nurse practitioners. Given our small study population, further investigation is warranted into the potential use of iBE where trained healthcare practitioners are not readily available. Full article

Background/Objectives: Breast cancer was the leading cause of malignant tumors among women in 2022. About two-thirds of breast cancer cases are hormone-receptor-positive. In these patients, aromatase inhibitors are a mainstay of treatment, but associated musculoskeletal symptoms can negatively affect patient compliance. Aromatase-inhibitor-induced carpal tunnel syndrome represents one of the main causes of aromatase inhibitor discontinuation, with a non-compliance rate of up to 67%, potentially leading to increased cancer mortality. This study investigates estrogen receptor expression in aromatase-inhibitor-induced carpal tunnel syndrome tissues, in order to better define its etiopathogenesis and derive preventive or therapeutic measures that can improve aromatase inhibitor patient compliance. To our knowledge, there is no study on this subject in the literature. Methods: Between 2023 and 2024, we recruited 14 patients at the Jewish Hospital of Rome, including seven patients with aromatase-inhibitor-induced carpal tunnel syndrome (study group) and seven with postmenopausal idiopathic carpal tunnel syndrome (control group). Each patient was evaluated based on a clinical visit, a questionnaire, instrumental exams, and serum hormone dosages and were treated with open carpal tunnel release surgery, during which transverse carpal ligament and flexor tenosynovium samples were collected. For immunohistochemical experiments, sections were treated with anti-estrogen receptor α and anti-estrogen receptor β antibodies. Results: The immunohistochemical features in the study and control groups were similar, demonstrating that tissues affected by aromatase-inhibitor-induced carpal tunnel syndrome are targets of direct estrogen action and that estrogen deprivation is correlated with disease etiogenesis. Surgery was effective in patient treatment. Conclusions: Aromatase-inhibitor-induced carpal tunnel syndrome represents a newly defined form of the disease. This syndrome represents one of the main causes of aromatase inhibitor discontinuation, due to its negative impact on the patient’s quality of life. The identification by clinicians of aromatase inhibitor use as a possible risk factor for carpal tunnel syndrome development is of essential importance, as early diagnosis and prompt management can improve patient compliance and overall breast cancer treatment outcomes. Full article

Interoperator variability in the reproducibility of breast lesions found by handheld ultrasound (HHUS) can significantly interfere with clinical care. This study analyzed the features associated with breast mass position differences during HHUS. The ability of operators to reproduce the position of small masses and the time required to generate annotations with and without a computer-assisted scanning device (DEVICE) were also evaluated. This prospective study included 28 patients with 34 benign or probably benign small breast masses. Two operators generated manual and automated position annotations for each mass. The probe and body positions were systematically varied during scanning with the DEVICE, and the features describing mass movement were used in three logistic regression models trained to discriminate small from large breast mass displacements (cutoff: 10 mm). All models successfully discriminated small from large breast mass displacements (areas under the curve: 0.78 to 0.82). The interoperator localization precision was 6.6 ± 2.8 mm with DEVICE guidance and 19.9 ± 16.1 mm with manual annotations. Computer-assisted scanning reduced the time to annotate and reidentify a mass by 33 and 46 s on average, respectively. The results demonstrated that breast mass location reproducibility and exam efficiency improved by controlling operator actionable features with computer-assisted HHUS. Full article

Breast cancer, affecting both genders, but mostly females, exhibits shifting demographic patterns, with an increasing incidence in younger age groups. Early identification through mammography, clinical examinations, and breast self-exams enhances treatment efficacy, but challenges persist in low- and medium-income countries due to limited imaging resources. This review assesses the feasibility of employing breast ultrasound as the primary breast cancer screening method, particularly in resource-constrained regions. Following the PRISMA guidelines, this study examines 52 publications from the last five years. Breast ultrasound, distinct from mammography, offers advantages like radiation-free imaging, suitability for repeated screenings, and preference for younger populations. Real-time imaging and dense breast tissue evaluation enhance sensitivity, accessibility, and cost-effectiveness. However, limitations include reduced specificity, operator dependence, and challenges in detecting microcalcifications. Automatic breast ultrasound (ABUS) addresses some issues but faces constraints like potential inaccuracies and limited microcalcification detection. The analysis underscores the need for a comprehensive approach to breast cancer screening, emphasizing international collaboration and addressing limitations, especially in resource-constrained settings. Despite advancements, notably with ABUS, the primary goal is to contribute insights for optimizing breast cancer screening globally, improving outcomes, and mitigating the impact of this debilitating disease. Full article

Glioblastoma (GB) is the most aggressive and common type of cancer within the central nervous system (CNS). Despite the vast knowledge of its physiopathology and histology, its etiology at the molecular level has not been completely understood. Thus, attaining a cure has not been possible yet and it remains one of the deadliest types of cancer. Usually, GB is diagnosed when some symptoms have already been presented by the patient. This diagnosis is commonly based on a physical exam and imaging studies, such as computed tomography (CT) and magnetic resonance imaging (MRI), together with or followed by a surgical biopsy. As these diagnostic procedures are very invasive and often result only in the confirmation of GB presence, it is necessary to develop less invasive diagnostic and prognostic tools that lead to earlier treatment to increase GB patients’ quality of life. Therefore, blood-based biomarkers (BBBs) represent excellent candidates in this context. microRNAs (miRNAs) are small, non-coding RNAs that have been demonstrated to be very stable in almost all body fluids, including saliva, serum, plasma, urine, cerebrospinal fluid (CFS), semen, and breast milk. In addition, serum-circulating and exosome-contained miRNAs have been successfully used to better classify subtypes of cancer at the molecular level and make better choices regarding the best treatment for specific cases. Moreover, as miRNAs regulate multiple target genes and can also act as tumor suppressors and oncogenes, they are involved in the appearance, progression, and even chemoresistance of most tumors. Thus, in this review, we discuss how dysregulated miRNAs in GB can be used as early diagnosis and prognosis biomarkers as well as molecular markers to subclassify GB cases and provide more personalized treatments, which may have a better response against GB. In addition, we discuss the therapeutic potential of miRNAs, the current challenges to their clinical application, and future directions in the field. Full article

Thermography has found extensive application as a supplementary diagnostic tool in breast cancer diagnosis, notably complementing the clinical breast exam (CBE). Within dynamic thermography, matrix factorization methods have demonstrated their utility in accentuating thermal heterogeneities by generating thermal basis vectors. A significant challenge in such approaches is to identify the leading thermal basis vector that effectively captures predominant thermal patterns. Embedding methods are used to fuse multiple projected basis vectors onto a single basis for the extraction of the thermal features, known as thermomics. In this study, we introduce Rayleigh embedding to project thermal basis vectors obtained from factorization techniques into a lower-dimensional space, highlighting thermal patterns. This enhances the reliability of the thermal system, thereby assisting in CBE. The best results of the embedding method combining clinical information and demographics yield 82.9% (66.7%, 86.7%) using a random forest. The results demonstrated promising preliminary outcomes, leading to the early detection of breast abnormalities, and can serve as a non-invasive tool to aid CBE. Full article

Deep learning (DL) reconstruction techniques to improve MR image quality are becoming commercially available with the hope that they will be applicable to multiple imaging application sites and acquisition protocols. However, before clinical implementation, these methods must be validated for specific use cases. In this work, the quality of standard-of-care (SOC) T2w and a high-spatial-resolution (HR) imaging of the breast were assessed both with and without prototype DL reconstruction. Studies were performed using data collected from phantoms, 20 retrospectively collected SOC patient exams, and 56 prospectively acquired SOC and HR patient exams. Image quality was quantitatively assessed via signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and edge sharpness. Qualitatively, all in vivo images were scored by either two or four radiologist readers using 5-point Likert scales in the following categories: artifacts, perceived sharpness, perceived SNR, and overall quality. Differences in reader scores were tested for significance. Reader preference and perception of signal intensity changes were also assessed. Application of the DL resulted in higher average SNR (1.2–2.8 times), CNR (1.0–1.8 times), and image sharpness (1.2–1.7 times). Qualitatively, the SOC acquisition with DL resulted in significantly improved image quality scores in all categories compared to non-DL images. HR acquisition with DL significantly increased SNR, sharpness, and overall quality compared to both the non-DL SOC and the non-DL HR images. The acquisition time for the HR data only required a 20% increase compared to the SOC acquisition and readers typically preferred DL images over non-DL counterparts. Overall, the DL reconstruction demonstrated improved T2w image quality in clinical breast MRI. Full article

There is a lack of evidence regarding the clinical impact of [¹⁸F]fluorodeoxyglucose positron emission tomography/computed tomography ([¹⁸F]FDG-PET/CT, hereinafter referred to as PET/CT), especially regarding management changes and their link to overall survival. We analyzed 52 PET/CTs in 47 stage I-IV breast cancer patients, selected from a prospective oncological PET/CT registry. Indications for PET/CT were primary staging (n = 15), restaging (n = 17), and suspected recurrence (n = 20). PET/CT-induced management changes were categorized as major or minor. PET/CT-induced management changes in 41 of 52 scans (78.8%; 38 of 47 patients (80.9%)), of which major changes were suggested in 18 of 52 scans (34.6%, 17 of 47 patients, 36.2%). PET/CT downstaged 6 of 15 primary staging patients, excluding distant metastases. Major management changes were documented in 3 of 17 restaging exams. PET/CT ruled out clinically suspected recurrence in 6 of 20 cases and confirmed it in 11 of 20. In three cases, locoregional recurrence had already been diagnosed via biopsy. In 30 of 52 exams, additional diagnostic tests were avoided, of which 13 were invasive. PET/CT-based management changes resulted in a 5-year survival rate of 72.3% for the whole study group, 93.3% for the staging group, 53.8% for the restaging group, and 68.4% for the recurrence group. This study shows that PET/CT significantly impacts clinical management decisions in breast cancer patients in different clinical scenarios, potentially determining the patient’s tumor stage as the basis for further therapy more reliably and by avoiding unnecessary diagnostic tests. Full article

Novel techniques, such as microwave imaging, have been implemented in different prototypes and are under clinical validation, especially for breast cancer detection, due to their harmless technology and possible clinical advantages over conventional imaging techniques. In the prospective study presented in this work, we aim to investigate through a multicentric European clinical trial (ClinicalTrials.gov Identifier NCT05300464) the effectiveness of the MammoWave microwave imaging device, which uses a Huygens-principle-based radar algorithm for image reconstruction and comprises dedicated image analysis software. A detailed clinical protocol has been prepared outlining all aspects of this study, which will involve adult females having a radiologist study output obtained using conventional exams (mammography and/or ultrasound and/or magnetic resonance imaging) within the previous month. A maximum number of 600 volunteers will be recruited at three centres in Italy and Spain, where they will be asked to sign an informed consent form prior to the MammoWave scan. Conductivity weighted microwave images, representing the homogeneity of the tissues’ dielectric properties, will be created for each breast, using a conductivity = 0.3 S/m. Subsequently, several microwave image parameters (features) will be used to quantify the images’ non-homogenous behaviour. A selection of these features is expected to allow for distinction between breasts with lesions (either benign or malignant) and those without radiological findings. For all the selected features, we will use Welch’s t-test to verify the statistical significance, using the gold standard output of the radiological study review. Full article

Purpose: This study aimed to investigate the use of contrast-free magnetic resonance imaging (MRI) as an innovative screening method for detecting breast cancer in high-risk asymptomatic women. Specifically, the researchers evaluated the diagnostic performance of diffusion-weighted imaging (DWI) in this population. Methods: MR images from asymptomatic women, carriers of a germline mutation in either the BRCA1 or BRCA2 gene, collected in a single center from January 2019 to December 2021 were retrospectively evaluated. A radiologist with experience in breast imaging (R1) and a radiology resident (R2) independently evaluated DWI/ADC maps and, in case of doubts, T2-WI. The standard of reference was the pathological diagnosis through biopsy or surgery, or ≥1 year of clinical and radiological follow-up. Diagnostic performances were calculated for both readers with a 95% confidence interval (CI). The agreement was assessed using Cohen’s kappa (κ) statistics. Results: Out of 313 women, 145 women were included (49.5 ± 12 years), totaling 344 breast MRIs with DWI/ADC maps. The per-exam cancer prevalence was 11/344 (3.2%). The sensitivity was 8/11 (73%; 95% CI: 46–99%) for R1 and 7/11 (64%; 95% CI: 35–92%) for R2. The specificity was 301/333 (90%; 95% CI: 87–94%) for both readers. The diagnostic accuracy was 90% for both readers. R1 recalled 40/344 exams (11.6%) and R2 recalled 39/344 exams (11.3%). Inter-reader reproducibility between readers was in moderate agreement (κ = 0.43). Conclusions: In female carriers of a BRCA1/2 mutation, breast DWI supplemented with T2-WI allowed breast cancer detection with high sensitivity and specificity by a radiologist with extensive experience in breast imaging, which is comparable to other screening tests. The findings suggest that DWI and T2-WI have the potential to serve as a stand-alone method for unenhanced breast MRI screening in a selected population, opening up new perspectives for prospective trials. Full article

Graphically prescribed patient-specific imaging volumes and local pre-scan volumes are routinely placed by MRI technologists to optimize image quality. However, manual placement of these volumes by MR technologists is time-consuming, tedious, and subject to intra- and inter-operator variability. Resolving these bottlenecks is critical with the rise in abbreviated breast MRI exams for screening purposes. This work proposes an automated approach for the placement of scan and pre-scan volumes for breast MRI. Anatomic 3-plane scout image series and associated scan volumes were retrospectively collected from 333 clinical breast exams acquired on 10 individual MRI scanners. Bilateral pre-scan volumes were also generated and reviewed in consensus by three MR physicists. A deep convolutional neural network was trained to predict both the scan and pre-scan volumes from the 3-plane scout images. The agreement between the network-predicted volumes and the clinical scan volumes or physicist-placed pre-scan volumes was evaluated using the intersection over union, the absolute distance between volume centers, and the difference in volume sizes. The scan volume model achieved a median 3D intersection over union of 0.69. The median error in scan volume location was 2.7 cm and the median size error was 2%. The median 3D intersection over union for the pre-scan placement was 0.68 with no significant difference in mean value between the left and right pre-scan volumes. The median error in the pre-scan volume location was 1.3 cm and the median size error was −2%. The average estimated uncertainty in positioning or volume size for both models ranged from 0.2 to 3.4 cm. Overall, this work demonstrates the feasibility of an automated approach for the placement of scan and pre-scan volumes based on a neural network model. Full article

The diagnosis of PE remains difficult in 2023 because the signs and symptoms are not sensible nor specific. The consequences of potential diagnostic errors can be dramatic, whether by default or by excess. Furthermore, the achievement of a simple diagnostic strategy, based on clinical probability assessment, D-dimer measurement and computed tomography pulmonary angiography (CTPA) leads to a new challenge for PE diagnosis: over-testing. Indeed, since the 2000s, the wide availability of CTPA resulted in a major increase in investigations with a mod I confirm erate increase in PE diagnosis, without any notable improvement in patient outcomes. Quite the contrary, the complications of anticoagulation for PE increased significantly, and the long-term consequences of imaging diagnostic radiation is an important concern, especially the risk of breast cancer for young women. As a result, several strategies have been proposed to fight over-testing. They are mostly based on defining a subgroup of patients for whom no specific exam should be required to rule-out PE and adjusting the D-dimer cutoff to allow the exclusion of PE without performing CTPA. This narrative review presents the advantages and limitations of these different strategies as well as the perspective in PE diagnosis. Full article

The low attendance rate for cancer screening tests in Poland is a major healthcare concern that requires specific analysis and the development of implementation recommendations for prevention, and both actions are likely to benefit culturally similar countries. Four female cancers account for approximately 20% of all cancer cases—breast cancer, cervical cancer, endometrial cancer, and ovarian cancer—suggesting that gynecologists have a significant preventative role. Of the four, breast cancer and cervical cancer are among the 10 most common malignant neoplasms globally, regardless of gender, occur only in women and are known to have effective screening measures. Our research aims to create a screening model that combines cervical cancer and breast cancer to maximize health outcomes for women at risk of both cancers. In the study protocol, we have created a model that maximizes benefits for patients with minimal additional costs to the health care system. To achieve the set goal, instead of regular clinical breast exams as recommended by the gynecological societies, we proposed an ultrasound examination, during which palpation may also be performed (in the absence of elastography). We present a scheme for such a protocol that takes into consideration all types of prevention in both cancers, and that emphasizes breast ultrasound as the most frequently missing element. Our study includes a discussion of the strengths and weaknesses of our strategy, and the crucial need for infrastructure and education for the successful implementation of the program. We conclude that our model merits consideration and discussion among health-care decision makers, as the screening changes we propose have significant potential benefits for the female population. Full article

Radiology reports are one of the main forms of communication between radiologists and other clinicians, and contain important information for patient care. In order to use this information for research and automated patient care programs, it is necessary to convert the raw text into structured data suitable for analysis. State-of-the-art natural language processing (NLP) domain-specific contextual word embeddings have been shown to achieve impressive accuracy for these tasks in medicine, but have yet to be utilized for section structure segmentation. In this work, we pre-trained a contextual embedding BERT model using breast radiology reports and developed a classifier that incorporated the embedding with auxiliary global textual features in order to perform section segmentation. This model achieved 98% accuracy in segregating free-text reports, sentence by sentence, into sections of information outlined in the Breast Imaging Reporting and Data System (BI-RADS) lexicon, which is a significant improvement over the classic BERT model without auxiliary information. We then evaluated whether using section segmentation improved the downstream extraction of clinically relevant information such as modality/procedure, previous cancer, menopausal status, purpose of exam, breast density, and breast MRI background parenchymal enhancement. Using the BERT model pre-trained on breast radiology reports, combined with section segmentation, resulted in an overall accuracy of 95.9% in the field extraction tasks. This is a 17% improvement, compared to an overall accuracy of 78.9% for field extraction with models using classic BERT embeddings and not using section segmentation. Our work shows the strength of using BERT in the analysis of radiology reports and the advantages of section segmentation by identifying the key features of patient factors recorded in breast radiology reports. Full article

In Saudi Arabia, colon cancer (CC) is the most prevalent cancer in men and the third most common cancer in women. Rather than being detected through screening programs, most CC cases are diagnosed mainly during clinical exams. Because of the slow growth of CC and its ability to be treated at an early stage, screening for CC can reduce the incidence of death and mortality. Consequently, there is an urgent need to identify a potential new cancer-specific biomarker for detecting early illness. Much research has been conducted on distinct antigen classes as potential new cancer-specific biomarkers for the early identification of malignancy. The cancer-testis antigens (CTAs) are one such category of antigens, with protein presence largely normally confined to human germ line cells in the testis and aberrantly produced in some cancer cells. CTAs are potentially valuable for use as cancer biomarkers and in cancer therapeutics due to their distinctive expression pattern. The aim of this current study was to identify potential cancer-testis (CT) gene biomarkers in Saudi Arabian CC patients. In this study, a total of 20 matching CC and normal colon (NC) tissues were obtained from the Saudi population. Any genes that showed expression in CC tissues but not in matching NC tissues were subsequently verified for mRNA expression in eight breast and eight leukemia malignancies using RT-PCR to determine the specificity of any CC biomarkers. CTAG1A, SPZ1, LYZL6, SCP2D1, TEX33, and TKTL2 genes were expressed in varying numbers of CC tissues compared to no measurable expressions in all NC tissue specimens, making these genes suitable potential candidates for CC markers. The most frequently expressed CT genes in CC patients were CTAG1A (35%) and SCP2D1 (35%), followed by TKTL2 (25%), SPZ1 (20%), LYZL6 (15%), and TEX33 (5%). The LYZL6 gene shows a weak RT-PCR product in 25% of breast cancer (BC) patients but not in leukemia patients. The SCP2D1 gene appears to display expression in all leukemia patients but not in the BC patients. TKTL2 expression was also observed in 50% of leukemia samples but not in the BC samples. More experiments at the protein level and with a larger cohort of patients are required to evaluate this finding. Full article