Screening the Implant-Augmented Breast with Digital Breast Tomosynthesis: Is Tomosynthesis Necessary for Non-implant-Displaced Views?

OBJECTIVE: To determine cancer visualization utility and radiation dose for non-implant-displaced (ID) views using standard protocol with digital breast tomosynthesis (DBT) vs alternative protocol with 2D only when screening women with implant augmentation. METHODS: This retrospective cohort study identified women with implants who underwent screening DBT examinations that had abnormal findings from July 28, 2014, to December 31, 2021. Three fellowship-trained breast radiologists independently reviewed examinations retrospectively to determine if the initially identified abnormalities could be visualized on standard protocol (DBT with synthesized 2D (S2D) for ID and non-ID views) and alternate protocol (DBT with S2D for ID and only the S2D images for non-ID views). Estimated exam average glandular dose (AGD) and associations between cancer visualization with patient and implant characteristics for both protocols were evaluated. RESULTS: The study included 195 patients (mean age 55 years ± 10) with 223 abnormal findings. Subsequent biopsy was performed for 86 abnormalities: 59 (69%) benign, 8 (9%) high risk, and 19 (22%) malignant. There was no significant difference in malignancy visualization rate between standard (19/223, 8.5%) and alternate (18/223, 8.1%) protocols (P =.92), but inclusion of the DBT for non-ID views found one additional malignancy. Total examination AGD using standard protocol (21.9 mGy ± 5.0) was significantly higher than it would be for estimated alternate protocol (12.6 mGy ± 5.0, P <.001). This remained true when stratified by breast thickness: 6.0-7.9 cm, 8.0-9.9 cm, >10.0 cm (all P <.001). CONCLUSION: The inclusion of DBT for non-ID views did not significantly increase the cancer visualization rate but did significantly increase overall examination AGD.

High-plex imaging of RNA and proteins at subcellular resolution in fixed tissue by spatial molecular imaging.

Resolving the spatial distribution of RNA and protein in tissues at subcellular resolution is a challenge in the field of spatial biology. We describe spatial molecular imaging, a system that measures RNAs and proteins in intact biological samples at subcellular resolution by performing multiple cycles of nucleic acid hybridization of fluorescent molecular barcodes. We demonstrate that spatial molecular imaging has high sensitivity (one or two copies per cell) and very low error rate (0.0092 false calls per cell) and background (~0.04 counts per cell). The imaging system generates three-dimensional, super-resolution localization of analytes at ~2 million cells per sample. Cell segmentation is morphology based using antibodies, compatible with formalin-fixed, paraffin-embedded samples. We measured multiomic data (980 RNAs and 108 proteins) at subcellular resolution in formalin-fixed, paraffin-embedded tissues (nonsmall cell lung and breast cancer) and identified >18 distinct cell types, ten unique tumor microenvironments and 100 pairwise ligand-receptor interactions. Data on >800,000 single cells and ~260 million transcripts can be accessed at http://nanostring.com/CosMx-dataset .

Spatially resolved whole transcriptome profiling in human and mouse tissue using Digital Spatial Profiling.

Emerging spatial profiling technology has enabled high-plex molecular profiling in biological tissues, preserving the spatial and morphological context of gene expression. Here, we describe expanding the chemistry for the Digital Spatial Profiling platform to quantify whole transcriptomes in human and mouse tissues using a wide range of spatial profiling strategies and sample types. We designed multiplexed in situ hybridization probes targeting the protein-coding genes of the human and mouse transcriptomes, referred to as the human or mouse Whole Transcriptome Atlas (WTA). Human and mouse WTAs were validated in cell lines for concordance with orthogonal gene expression profiling methods in regions ranging from ∼10-500 cells. By benchmarking against bulk RNA-seq and fluorescence in situ hybridization, we show robust transcript detection down to ∼100 transcripts per region. To assess the performance of WTA across tissue and sample types, we applied WTA to biological questions in cancer, molecular pathology, and developmental biology. Spatial profiling with WTA detected expected gene expression differences between tumor and tumor microenvironment, identified disease-specific gene expression heterogeneity in histological structures of the human kidney, and comprehensively mapped transcriptional programs in anatomical substructures of nine organs in the developing mouse embryo. Digital Spatial Profiling technology with the WTA assays provides a flexible method for spatial whole transcriptome profiling applicable to diverse tissue types and biological contexts.

Automated quality control in nuclear medicine using the structured noise index.

PURPOSE: Daily flood-field uniformity evaluation serves as the central element of nuclear medicine (NM) quality control (QC) programs. Uniformity images are traditionally analyzed using pixel value-based metrics, that is, integral uniformity (IU), which often fail to capture subtle structure and patterns caused by changes in gamma camera performance, requiring visual inspections which are subjective and time demanding. The goal of this project was to implement an advanced QC metrology for NM to effectively identify nonuniformity issues, and report issues in a timely manner for efficient correction prior to clinical use. The project involved the implementation of the program over a 2-year period at a multisite major medical institution. METHODS: Using a previously developed quantitative uniformity analysis metric, the structured noise index (SNI) [Nelson et al. (2014), \textit{J Nucl Med.}, \textbf{55}:169-174], an automated QC process was developed to analyze, archive, and report on daily NM QC uniformity images. Clinical implementation of the newly developed program ran in parallel with the manufacturer's reported IU-based QC program. The effectiveness of the SNI program was evaluated over a 21-month period using sensitivity and coefficient of variation statistics. RESULTS: A total of 7365 uniformity QC images were analyzed. Lower level SNI alerts were generated in 12.5% of images and upper level alerts in 1.7%. Intervention due to image quality issues occurred on 26 instances; the SNI metric identified 24, while the IU metric identified eight. The SNI metric reported five upper level alerts where no clinical engineering intervention was deemed necessary. CONCLUSION: An SNI-based QC program provides a robust quantification of the performance of gamma camera uniformity. It operates seamlessly across a fleet of multiple camera models and, additionally, provides effective workflow among the clinical staff. The reliability of this process could eliminate the need for visual inspection of each image, saving valuable time, while enabling quantitative analysis of inter- and intrasystem performance.

How does c-view image quality compare with conventional 2D FFDM?

PURPOSE: The FDA approved the use of digital breast tomosynthesis (DBT) in 2011 as an adjunct to 2D full field digital mammography (FFDM) with the constraint that all DBT acquisitions must be paired with a 2D image to assure adequate interpretative information is provided. Recently manufacturers have developed methods to provide a synthesized 2D image generated from the DBT data with the hope of sparing patients the radiation exposure from the FFDM acquisition. While this much needed alternative effectively reduces the total radiation burden, differences in image quality must also be considered. The goal of this study was to compare the intrinsic image quality of synthesized 2D c-view and 2D FFDM images in terms of resolution, contrast, and noise. METHODS: Two phantoms were utilized in this study: the American College of Radiology mammography accreditation phantom (ACR phantom) and a novel 3D printed anthropomorphic breast phantom. Both phantoms were imaged using a Hologic Selenia Dimensions 3D system. Analysis of the ACR phantom includes both visual inspection and objective automated analysis using in-house software. Analysis of the 3D anthropomorphic phantom includes visual assessment of resolution and Fourier analysis of the noise. RESULTS: Using ACR-defined scoring criteria for the ACR phantom, the FFDM images scored statistically higher than c-view according to both the average observer and automated scores. In addition, between 50% and 70% of c-view images failed to meet the nominal minimum ACR accreditation requirements-primarily due to fiber breaks. Software analysis demonstrated that c-view provided enhanced visualization of medium and large microcalcification objects; however, the benefits diminished for smaller high contrast objects and all low contrast objects. Visual analysis of the anthropomorphic phantom showed a measureable loss of resolution in the c-view image (11 lp/mm FFDM, 5 lp/mm c-view) and loss in detection of small microcalcification objects. Spectral analysis of the anthropomorphic phantom showed higher total noise magnitude in the FFDM image compared with c-view. Whereas the FFDM image contained approximately white noise texture, the c-view image exhibited marked noise reduction at midfrequency and high frequency with far less noise suppression at low frequencies resulting in a mottled noise appearance. CONCLUSIONS: Their analysis demonstrates many instances where the c-view image quality differs from FFDM. Compared to FFDM, c-view offers a better depiction of objects of certain size and contrast, but provides poorer overall resolution and noise properties. Based on these findings, the utilization of c-view images in the clinical setting requires careful consideration, especially if considering the discontinuation of FFDM imaging. Not explicitly explored in this study is how the combination of DBT + c-view performs relative to DBT + FFDM or FFDM alone.

Improved nuclear medicine uniformity assessment with noise texture analysis.

UNLABELLED: Because γ cameras are generally susceptible to environmental conditions and system vulnerabilities, they require routine evaluation of uniformity performance. The metrics for such evaluations are commonly pixel value-based. Although these metrics are typically successful at identifying regional nonuniformities, they often do not adequately reflect subtle periodic structures; therefore, additional visual inspections are required. The goal of this project was to develop, test, and validate a new uniformity analysis metric capable of accurately identifying structures and patterns present in nuclear medicine flood-field uniformity images. METHODS: A new uniformity assessment metric, termed the structured noise index (SNI), was based on the 2-dimensional noise power spectrum (NPS). The contribution of quantum noise was subtracted from the NPS of a flood-field uniformity image, resulting in an NPS representing image artifacts. A visual response filter function was then applied to both the original NPS and the artifact NPS. A single quantitative score was calculated on the basis of the magnitude of the artifact. To verify the validity of the SNI, an observer study was performed with 5 expert nuclear medicine physicists. The correlation between the SNI and the visual score was assessed with Spearman rank correlation analysis. The SNI was also compared with pixel value-based assessment metrics modeled on the National Electrical Manufacturers Association standard for integral uniformity in both the useful field of view (UFOV) and the central field of view (CFOV). RESULTS: The SNI outperformed the pixel value-based metrics in terms of its correlation with the visual score (ρ values for the SNI, integral UFOV, and integral CFOV were 0.86, 0.59, and 0.58, respectively). The SNI had 100% sensitivity for identifying both structured and nonstructured nonuniformities; for the integral UFOV and CFOV metrics, the sensitivities were only 62% and 54%, respectively. The overall positive predictive value of the SNI was 87%; for the integral UFOV and CFOV metrics, the positive predictive values were only 67% and 50%, respectively. CONCLUSION: The SNI accurately identified both structured and nonstructured flood-field nonuniformities and correlated closely with expert visual assessment. Compared with traditional pixel value-based analysis, the SNI showed superior performance in terms of its correlation with visual perception. The SNI method is effective for detecting and quantifying visually apparent nonuniformities and may reduce the need for more subjective visual analyses.

N3'-->P5' Oligodeoxyribonucleotide Phosphoramidates: A New Method of Synthesis Based on a Phosphoramidite Amine-Exchange Reaction.

A new method for the synthesis of N3'-->P5' phosphoramidate oligodeoxynucleotides is demonstrated. Described herein is the synthesis of the monomers utilized in the phosphoramidite amine-exchange process and the experimental details pertaining to this new mode of chain assembly. The phosphoramidite amine-exchange method generates coupling yields in the 92-95% range per cycle and further enables the synthesis of chimeric phosphoramidate/phosphodiester or phosphoramidate/phosphorothioate oligonucleotides with no instrument modifications.