https://ctep.cancer.gov/protocolDevelopment/docs/recist_guideline.pdf

New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1)

Background: Thyroid nodules are a common clinical problem, and differentiated thyroid cancer is becoming increasingly prevalent. Since the American Thyroid Association's (ATA's) guidelines for the management of these disorders were revised in 2009, significant scientific advances have occurred in the field. The aim of these guidelines is to inform clinicians, patients, researchers, and health policy makers on published evidence relating to the diagnosis and management of thyroid nodules and differentiated thyroid cancer. Methods: The specific clinical questions addressed in these guidelines were based on prior versions of the guidelines, stakeholder input, and input of task force members. Task force panel members were educated on knowledge synthesis methods, including electronic database searching, review and selection of relevant citations, and critical appraisal of selected studies. Published English language articles on adults were eligible for inclusion. The American College of Physicians Guideline Gr...

/pdf/2015-american-thyroid-association-management-guidelines-for-32kri8vrhd.pdf

2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer.

Data Mining Practical Machine Learning Tools and Techniques

Hypoxia-inducible factor 1 (HIF-1) activates the transcription of genes that are involved in crucial aspects of cancer biology, including angiogenesis, cell survival, glucose metabolism and invasion. Intratumoral hypoxia and genetic alterations can lead to HIF-1alpha overexpression, which has been associated with increased patient mortality in several cancer types. In preclinical studies, inhibition of HIF-1 activity has marked effects on tumour growth. Efforts are underway to identify inhibitors of HIF-1 and to test their efficacy as anticancer therapeutics.

Targeting HIF-1 for cancer therapy

In the past decade, the field of medical image analysis has grown exponentially, with an increased number of pattern recognition tools and an increase in data set sizes. These advances have facilitated the development of processes for high-throughput extraction of quantitative features that result in the conversion of images into mineable data and the subsequent analysis of these data for decision support; this practice is termed radiomics. This is in contrast to the traditional practice of treating medical images as pictures intended solely for visual interpretation. Radiomic data contain first-, second-, and higher-order statistics. These data are combined with other patient data and are mined with sophisticated bioinformatics tools to develop models that may potentially improve diagnostic, prognostic, and predictive accuracy. Because radiomics analyses are intended to be conducted with standard of care images, it is conceivable that conversion of digital images to mineable data will eventually become routine practice. This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer.

https://pubs.rsna.org/doi/pdf/10.1148/radiol.2015151169

Radiomics: Images Are More than Pictures, They Are Data.

Probe-based dynamic (4-D) imaging modalities capture breast intratumor heterogeneity both spatially and kinetically. Characterizing heterogeneity through tumor sub-populations with distinct functional behavior may elucidate tumor biology to improve targeted therapy specificity and enable precision clinical decision making. We propose an unsupervised clustering algorithm for 4-D imaging that integrates Markov-Random Field (MRF) image segmentation with time-series analysis to characterize kinetic intratumor heterogeneity. We applied this to dynamic FDG PET scans by identifying distinct time-activity curve (TAC) profiles with spatial proximity constraints. We first evaluated algorithm performance using simulated dynamic data. We then applied our algorithm to a dataset of 50 women with locally advanced breast cancer imaged by dynamic FDG PET prior to treatment and followed to monitor for disease recurrence. A functional tumor heterogeneity (FTH) signature was then extracted from functionally distinct sub-regions within each tumor. Cross-validated time-to-event analysis was performed to assess the prognostic value of FTH signatures compared to established histopathological and kinetic prognostic markers. Adding FTH signatures to a baseline model of known predictors of disease recurrence and established FDG PET uptake and kinetic markers improved the concordance statistic (C-statistic) from 0.59 to 0.74 (p = 0.005). Unsupervised hierarchical clustering of the FTH signatures identified two significant (p < 0.001) phenotypes of tumor heterogeneity corresponding to high and low FTH. Distributions of FDG flux, or Ki, were significantly different (p = 0.04) across the two phenotypes. Our findings suggest that imaging markers of FTH add independent value beyond standard PET imaging metrics in predicting recurrence-free survival in breast cancer and thus merit further study.

/pdf/functional-4-d-clustering-for-characterizing-intratumor-3oxjn4zrjs.pdf

Functional 4-D clustering for characterizing intratumor heterogeneity in dynamic imaging: evaluation in FDG PET as a prognostic biomarker for breast cancer

Multi-frame studies using cameras with fine spatial sampling and many possible coincidence lines create large memory requirements. To reduce these requirements and enable the PENN-PET scanner to perform gated cardiac studies, a microprocessor-based system for on-line preprocessing of raw data into sinograms was designed, built and evaluated.

Multi-Frame Data Acquisition for PET Camera Using an On-Line Microprocessor-Based System

11075 Background: Early decline in proliferative index (Ki-67) predicts response to endocrine therapy. For estrogen receptor positive (ER+) tumors, a low Ki-67 two weeks into endocrine therapy also predicts response (Dowsett JNCI 2007). FDG PET is promising for evaluating early response to systemic therapy and has the advantage of being non-invasive and of providing simultaneous quantitative measures at multiple tumor sites in vivo. We tested the association between FDG PET SUV and Ki-67 after two weeks of aromatase inhibitor (AI) therapy, and their prediction of response. Methods: Patients undergoing AI therapy were eligible for enrollment in the imaging study, and underwent a two week “run-in” of AI monotherapy prior to continued monotherapy or the addition of chemotherapy. Patients underwent baseline FDG PET, and Ki-67 was measured in tumor biopsy specimens. Following two weeks of therapy FDG PET and biopsy were again performed. Patients on AI therapy only were followed for clinical response. Results: ...

David A. Mankoff

Papers

Functional 4-D clustering for characterizing intratumor heterogeneity in dynamic imaging: evaluation in FDG PET as a prognostic biomarker for breast cancer

Multi-Frame Data Acquisition for PET Camera Using an On-Line Microprocessor-Based System

Early assessment of response to aromatase inhibitor (AI) therapy

Diagnostic Applications of Nuclear Medicine: Breast Cancer

Radiotracer breast cancer imaging: Beyond FDG and MIBI.