The purpose of this pictorial essay is to illustrate several clinical situations in which SPECT/CT can be effectively applied in nuclear radiology practice.SPECT/CT has recently emerged as a valuable adjunct to standard techniques in clinical nuclear radiology. This technique provides significantly improved scintigraphic localization and characterization of disease, increasingly important in this era of minimally invasive surgery and targeted radiotherapy.
Abstract Accurate detection of minimal residual disease (MRD) can guide individualized management of early stage cancer patients, but current diagnostic approaches lack adequate sensitivity. Circulating tumor DNA (ctDNA) analysis has shown promise for recurrence monitoring but MRD detection immediately after neoadjuvant therapy or surgical resection has remained challenging. We have developed TARgeted DIgital Sequencing (TARDIS) to simultaneously analyze multiple patient-specific cancer mutations in plasma and improve sensitivity for minute quantities of residual tumor DNA. In 77 reference samples at 0.03%-1% mutant allele fraction (AF), we observed 93.5% sensitivity. Using TARDIS, we analyzed ctDNA in 34 samples from 13 patients with stage II/III breast cancer treated with neoadjuvant therapy. Prior to treatment, we detected ctDNA in 12/12 patients at 0.002%-1.04% AF (0.040% median). After completion of neoadjuvant therapy, we detected ctDNA in 7/8 patients with residual disease observed at surgery and in 1/5 patients with pathological complete response (odds ratio, 18.5, Fisher’s exact p=0.032). These results demonstrate high accuracy for a personalized blood test to detect residual disease after neoadjuvant therapy. With additional clinical validation, TARDIS could identify patients with molecular complete response after neoadjuvant therapy who may be candidates for nonoperative management. One Sentence Summary A personalized ctDNA test achieves high accuracy for residual disease.
Abstract Background: Next generation sequencing (NGS) has revealed that the genetic profiles of individual tumors are highly heterogeneous due to their subclonal composition. Tumor heterogeneity has profound clinical implications affecting differences in treatment response and therapeutic resistance. Methods: An estrogen receptor positive, Her2 normal breast cancer patient underwent definitive surgical treatment with modified radical mastectomy. Multiple samples were obtained from the primary cancer and metastatic lymph nodes. Flow cytometry based methods were used to isolate and classify distinct cell subpopulations according to their ploidy, and samples were processed for whole exome sequencing (WES). Comparative Genomic Hybridization (CGH) methods were used to identify somatic unique copy-number alterations (CNAs). WES-Single Nucleotide Variations (SNVs) were used to infer subclonal phylogenetic relationships using Maximum Parsimony methods and annotated with variation-cluster-barcodes (vc-barcodes) generated using a variation Bayesian mixture model (VBMM) approach that focuses on copy-number neutral sequence variations for subclone identification (SciClone). Our comparative phylogenetic-VBMM clustering method was used to identify CNA and/or SNV drivers that are key in differentiating subclonal populations at multiple tumor sites. Results: CNA-neutral WES-SNVs from 25 subclonal populations (isolated from 4 distinct sites) clustered into 6 major groups and were used to generate vc-barcodes. A phylogenetic reconstruction of subclonal architecture annotated with vc-barcode information expedited identification of key variations underlying the differentiation of subclones at distinct tumor sites. For example, we identified an amplification event involving the Anaplastic Lymphoma Kinase (ALK) gene that was more frequent in primary biopsy subclones (12/17, ∼71%) in comparison to metastatic subclones (2/6, ∼34%). As the ALK amplification is lost, we find that most of the metastatic subclones also acquire a predicted damaging mutation in this oncogene (4/6, ∼67%). In addition, we identified a potential driver metastatic cell lineage that carries the ALK amplification in the absence of the nonsynonymous mutation. Conclusions: We developed a hybrid clustering methodology and used it to reconstruct the subclonal architecture in primary and metastatic tumors from a single breast cancer patient. Our methods have identified several CNAs and/or SNVs underlying subclonal differentiation, as well as potential biomarkers of disease progression and indicators of emerging resistance. Application of these methods to larger cohorts and types of tumors should be conducted to ascertain more precise estimates of the predictive accuracy of our processes. Citation Format: Mia D. Champion, Princy Francis, Barbara A. Pockaj, Michael T. Barrett. Hybrid clustering methodologies to distinguish CNAs and/or SNVs that drive subclonal differentiation in samples from a breast cancer patient primary tumor and metastatic lymph nodes. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4861. doi:10.1158/1538-7445.AM2015-4861
9034 Background: Routine imaging for staging of early stage cutaneous melanoma is not recommended by National Comprehensive Cancer Network (NCCN) guidelines. Besides the low probability of finding metastatic disease, detrimental aspects include false-positives and additive cost. We sought to investigate the use of imaging for staging of cutaneous melanoma in the United States. Methods: Patients with newly diagnosed clinically node negative cutaneous melanoma between 2000-2007 were identified from the Surveillance Epidemiology End Results-Medicare registry. Any imaging performed within 90 days following diagnosis was considered a staging study. Patients with metastatic disease were excluded. Results: A total of 25,643 patients were identified, of whom 10,775 (42%) underwent imaging. The mean age was 76.1 years, with the majority being male (61.8%) and Caucasian (98.4%). Breakdown by T classification of the primary was as follows: T1 (63%), T2 (17%), T3 (12%), and T4 (8%). A chest Xray was performed for 9,737 (38.0%), while 3,176 (12.4%) underwent advanced staging imaging studies; PET (7.2%), CT (5.9%), MRI (0.6%), and Ultrasound (0.4%). The use of advanced imaging steadily increased over the period of our study from 9.0% in 2000 to 16.3% in 2007 (p<0.001). When stratified by T classification, advanced imaging was used for 8.9% of T1, 14.5% of T2, 18.8% of T3 and 27.0% of T4 tumors (p<0.001). Similarly, node positive patients (4.7%) underwent advanced imaging 33.4% of the time compared to 11.3% for node negative patients (p<0.001). On multivariate analysis, factors predictive of advanced imaging include higher T classification (OR 3.12 T4 vs. T1, CI 2.77-3.52, p<0.001), node positivity (OR 2.70, CI 2.36-3.09, p<0.001), more recent year of diagnosis (OR 2.01 2007 vs. 2000, CI 1.71-2.37, p=0.006), high school education (OR 1.62, CI 1.43-1.83, p<0.001), non-Caucasian race (OR 1.37, CI 1.05-1.77, p=0.018), and male gender (OR 1.12, CI 1.03-1.21, p=0.006). Conclusions: Contrary to current recommendations, performance of advanced imaging for staging of early stage cutaneous melanoma is increasing in the Medicare population. Further research is needed to identify factors driving this increase.
