The potential for liquid biopsies in the precision medical treatment of breast cancer.

Currently the clinical management of breast cancer relies on relatively few prognostic/predictive clinical markers (estrogen receptor, progesterone receptor, HER2), based on primary tumor biology. Circulating biomarkers, such as circulating tumor DNA (ctDNA) or circulating tumor cells (CTCs) may enhance our treatment options by focusing on the very cells that are the direct precursors of distant metastatic disease, and probably inherently different than the primary tumor's biology. To shift the current clinical paradigm, assessing tumor biology in real time by molecularly profiling CTCs or ctDNA may serve to discover therapeutic targets, detect minimal residual disease and predict response to treatment. This review serves to elucidate the detection, characterization, and clinical application of CTCs and ctDNA with the goal of precision treatment of breast cancer

Histopathological image analysis : a review

Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe

Genomic biomarkers in prostate cancer.

Prostate cancer is the most common non-cutaneous cancer among men in the United States. In the last decade there has been a rapid expansion in the field of biomarker assays for diagnosis, prognosis, and treatment prediction in prostate cancer. The evidence base for these assays is rapidly evolving. With several commercial assays available at each stage of the disease, deciding which genomic assays are appropriate for which patients can be nuanced for physicians. In an effort to help guide these decisions in clinical practice, we aim to give an update on the current status of the biomarker field of prostate cancer

Role of noninvasive molecular imaging in determining response

The intersection of immunotherapy and radiation oncology is a rapidly evolving area of preclinical and clinical investigation. The strategy of combining radiation and immunotherapy to enhance local and systemic antitumor immune responses is intriguing yet largely unproven in the clinical setting because the mechanisms of synergy and the determinants of therapeutic response remain undefined. In recent years, several noninvasive molecular imaging approaches have emerged as a platform to interrogate the tumor immune microenvironment. These tools have the potential to serve as robust biomarkers for cancer immunotherapy and may hold several advantages over conventional anatomic imaging modalities and contemporary invasive tissue acquisition techniques. Given the key and expanding role of precision imaging in radiation oncology for patient selection, target delineation, image guided treatment delivery, and response assessment, noninvasive molecular-specific imaging may be uniquely suited to evaluate radiation/immunotherapy combinations. Herein, we describe several experimental imaging-based strategies that are currently being explored to characterize in vivo immune responses, and we review a growing body of preclinical data and nascent clinical experience with immuno-positron emission tomography molecular imaging as a putative biomarker for cancer immunotherapy. Finally, we discuss practical considerations for clinical translation to implement noninvasive molecular imaging of immune checkpoint molecules, immune cells, or associated elements of the antitumor immune response with a specific emphasis on its potential application at the interface of radiation oncology and immuno-oncology

Prevention and early detection of prostate cancer

This Review was sponsored and funded by the International Society of Cancer Prevention (ISCaP), the European Association of Urology (EAU), the National Cancer Institute, USA (NCI) (grant number 1R13CA171707-01), Prostate Cancer UK, Cancer Research UK (CRUK) (grant number C569/A16477), and the Association for International Cancer Research (AICR

A Rapid Segmentation-Insensitive "Digital Biopsy" Method for Radiomic Feature Extraction: Method and Pilot Study Using CT Images of Non-Small Cell Lung Cancer.

Quantitative imaging approaches compute features within images' regions of interest. Segmentation is rarely completely automatic, requiring time-consuming editing by experts. We propose a new paradigm, called "digital biopsy," that allows for the collection of intensity- and texture-based features from these regions at least 1 order of magnitude faster than the current manual or semiautomated methods. A radiologist reviewed automated segmentations of lung nodules from 100 preoperative volume computed tomography scans of patients with non-small cell lung cancer, and manually adjusted the nodule boundaries in each section, to be used as a reference standard, requiring up to 45 minutes per nodule. We also asked a different expert to generate a digital biopsy for each patient using a paintbrush tool to paint a contiguous region of each tumor over multiple cross-sections, a procedure that required an average of <3 minutes per nodule. We simulated additional digital biopsies using morphological procedures. Finally, we compared the features extracted from these digital biopsies with our reference standard using intraclass correlation coefficient (ICC) to characterize robustness. Comparing the reference standard segmentations to our digital biopsies, we found that 84/94 features had an ICC >0.7; comparing erosions and dilations, using a sphere of 1.5-mm radius, of our digital biopsies to the reference standard segmentations resulted in 41/94 and 53/94 features, respectively, with ICCs >0.7. We conclude that many intensity- and texture-based features remain consistent between the reference standard and our method while substantially reducing the amount of operator time required

The Advanced Applications For Optical Coherence Tomography In Skin Imaging

Optical coherence tomography (OCT), based on the principle of interferometry, is a fast and non-invasive imaging modality, which has been approved by FDA for dermatologic applications. OCT has high spatial resolution up to micrometer scale compared to traditional ultrasound imaging. In addition, OCT can provide real-time cross-sectional images with 1 to 2 mm penetration depth, which makes it an ideal imaging technique to assess the skin micro-morphology and pathology without any tissue removal. Many studies have investigated the possibilities of using OCT to evaluate dermatologic conditions, such as skin cancer, dermatitis, psoriasis, and skin damages. Hence, OCT has tremendous potential to provide skin histological and pathological information and assist differential diagnosis of various skin diseases. In this study, we used a swept-source OCT with 1305 nm central wavelength to explore its advanced applications in dermatology. This dissertation consists of four major research projects. First, we explored the feasibility of OCT imaging for assisting real-time visualization in skin biopsy. We showed that OCT could be used to guide and track a needle insertion in mouse skin in real-time. The structure of skin and the movement of needle can be clearly seen on the OCT images without any time delay during the procedures. Next, we tested the concept of performing the punch biopsy using OCT hand-held probe attached to a piercing tip in a phantom. We proved that using the OCT is a reliable technique to delineate the margin of lesion in phantom. And it is possible to perform the punch biopsy with the OCT probe. Second, we tested the performance of contrast-enhanced OCT in melanoma detection in an in vitro study. Melanoma is the most lethal type of skin cancer. Early detection could significantly improve the long-term survival rate of patients. In this initial study, a contrast agent (Gal3-USGNPs) is developed by conjugating melanoma biomarker (Gal3) to ultra-small gold nanoparticles (USGNPs). We showed that the contrast agent can differentiate B16 melanoma cells from normal skin keratinocytes in vitro. To avoid systemic administration of USGNPs, the third project continues to explore the enhanced topical delivery of USGNPs. In this study, we used OCT to monitor the topical delivery of nanoparticles on pig skin over time. And the diffusion and penetration of USGNPs in skin can be improved by applying chemical and physical enhancers such as DMSO and sonophoresis. Finally, in addition to image the cross-sectional structure of skin, we also aim to extract quantitative information from OCT images. The skin optical properties such as attenuation coefficient can be measured from OCT images. We measured and compared the skin attenuation coefficient in the skin of forehead and lateral hip, the skin of three different age groups, and the skin of three different Fitzpatrick types. The statistical analysis showed that epidermis has much higher attenuation coefficient than dermis. And the skin type V & VI have a relatively lower attenuation coefficient than the other skin types. These studies could aid the detection of skin cancer using imaging techniques and provide some new insights into the future applications of OCT in dermatology

Virtual biopsy in abdominal pathology: where do we stand?

In recent years, researchers have explored new ways to obtain information from pathological tissues, also exploring non-invasive techniques, such as virtual biopsy (VB). VB can be defined as a test that provides promising outcomes compared to traditional biopsy by extracting quantitative information from radiological images not accessible through traditional visual inspection. Data are processed in such a way that they can be correlated with the patient’s phenotypic expression, or with molecular patterns and mutations, creating a bridge between traditional radiology, pathology, genomics, and artificial intelligence (AI). Radiomics is the backbone of VB, since it allows the extraction and selection of features from radiological images, feeding them into AI models in order to derive lesions' pathological characteristics and molecular status. Presently, the output of VB provides only a gross approximation of the findings of tissue biopsy. However, in the future, with the improvement of imaging resolution and processing techniques, VB could partially substitute the classical surgical or percutaneous biopsy, with the advantage of being non-invasive, comprehensive, accounting for lesion heterogeneity, and low cost. In this review, we investigate the concept of VB in abdominal pathology, focusing on its pipeline development and potential benefits

Prostate cancer radiogenomics—from imaging to molecular characterization

Radiomics and genomics represent two of the most promising fields of cancer research, designed to improve the risk stratification and disease management of patients with prostate cancer (PCa). Radiomics involves a conversion of imaging derivate quantitative features using manual or automated algorithms, enhancing existing data through mathematical analysis. This could increase the clinical value in PCa management. To extract features from imaging methods such as magnetic resonance imaging (MRI), the empiric nature of the analysis using machine learning and artificial intelligence could help make the best clinical decisions. Genomics information can be explained or decoded by radiomics. The development of methodologies can create more-efficient predictive models and can better characterize the molecular features of PCa. Additionally, the identification of new imaging biomarkers can overcome the known heterogeneity of PCa, by non-invasive radio-logical assessment of the whole specific organ. In the future, the validation of recent findings, in large, randomized cohorts of PCa patients, can establish the role of radiogenomics. Briefly, we aimed to review the current literature of highly quantitative and qualitative results from well-de-signed studies for the diagnoses, treatment, and follow-up of prostate cancer, based on radiomics, genomics and radiogenomics research