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The primary aim of ACRIN 6698 was the evaluation of breast diffusion weighted imaging (DWI) for the prediction of response to neoadjuvant chemotherapy (NAC) for invasive breast cancer. For this purpose, serial MRI studies were acquired over the course of treatment. The study schema for the ACRIN 6698 Trial is shown in Figure 1.

MRI studies were performed at up to four time points in the course of NAC:

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For patients randomized onto a treatment arm of I‑SPY 2 subsequent MRI studies with the same required acquisitions were performed:

2. Early-treatment (T1, optional test/retest visit)
After 3 weeks of regimen 1 treatment (Paclitaxel with or without an experimental agent).

3. Mid-treatment (T2)
Between Paclitaxel and Anthracycline (AC) treatment regimens.

4. Post-treatment (T3)
Following 4 cycles AC and prior to surgery.

“Coffee-break” style test/retest studies were done on a subset of patients under a separate informed consent. These were by preference done at the baseline visit but were also allowed at visit T1. A given patient could only have the test/retest scans at a single visit, and total number of test/retest cases at any given site were limited (maximum 14) to ensure a wide representation of different scanners, sites and field strengths in the test/retest cohort.

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Derived objects from the DWI and DCE acquisitions are included for the convenience of the user. Some of these are not strictly DICOM compliant and may not be readable by all DICOM software packages. Parametric maps and segmentations are believed to be identical to those utilized in the primary analysis and test/retest repeatability analyses of the 6698 Trial, but in isolated cases modifications may have occurred in subsequent processing.

DWI “Package” for each study with analyzable diffusion scan

  1. 4 b-value DW Trace Images
    1. Multiple 2-b MSMB DWI acquisitions were combined (1 site)
    2. 3 directional DW images were geometrically averaged to generate trace images for studies where directional DWI data was saved
  2. 4-b value ADC maps
    1. A low threshold (b=0 image > 10) was applied to all studies
    2. ADC calculated as linear fit to log(S(b)) = log(S(0)) – ADC * b
    3. Voxels below threshold or with ADC < 0.0 are set to 0
  3. Manually defined multi-slice tumor segmentations
    1. ROIs defined for published primary analysis
    2. Tumor segmented on all slices with identifiable tumor referencing high-b image, ADC map, and DCE subtraction image (for localization)
    3. The segmentations are provided both as DICOM SEG objects and as DICOM MRI objects on TCIA

These DWI derived series can be identified either by Series Description (0008,103e) or by Series Number (0020,0011). See Table 1 for series identification details.

Manual DWI Whole-Tumor Segmentation Method

The segmentations provided in the derived diffusion objects are those generated for and used in the primary analysis and test/retest analyses for the ACRIN-6698 study. Tumor was identified on post-contrast DCE subtraction images and then localized on the ADC map. (apparent diffusion coefficient) Multi-slice, whole-tumor regions of interest (ROIs) were manually defined by selecting regions with low ADC and hyperintensity on a high b-value DWI (b=600 or 800 s/mm2) while avoiding adjacent adipose and fibroglandular tissue, biopsy clip artifacts, and regions of high T2 signal (e.g., seroma and necrosis). For multicentric/multifocal disease, all disease regions were included in the ROI. Region definition was done at the UCSF processing lab using in-house software tools developed with IDL (Exelis Visual Information Solutions, Boulder, Colorado).

DCE “Package” for each study

  1. Single-breast ipsilateral (same side) cropped DCE images
    1. As this was done primarily for computational efficiency, low matrix-sized images (<384 voxels per row) were stored and processed without cropping
  2. Enhancement maps
    1. PEearly: Enhancement at effective post-contrast time 120-150 sec
    2. PElate: Enhancement at effective post-contrast time ~450 sec
    3. SER: Signal enhancement ratio    SER =  PEearly / PElate
      Note: SER values were scaled by 1000 for integer storage. DICOM software utilizing the rescale slope and intercept fields [ DICOM fields (0028, 1052-1054)] should return the original SER values in the range from 0.0 – 3.0.
    4. All maps were stored as DICOM MRI objects
  3. Functional Tumor Volume (FTV) analysis mask
    1. Segmentation storing FTV masking. Encodes:
      1. Pre-contrast background threshold
      2. Minimum PE threshold (70% nom.)
      3. Manually defined rectangular volume of interest (VOI) for enhancing tumor analysis
      4. Manually defined “OMIT” regions used to exclude non-tumor enhancing regions that encroached on the rectangular VOI
    2. Stored as DICOM SEG object
    3. See this document for further information: <Analysis mask files description.docx>

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Calculation parameters and DCE volume analysis results are included in private attributes in some of the derived objects. A DICOM dictionary [[XXX link]] is provided for download for researchers wishing to use these parameters and/or results from the primary analyses. Note: the DCE functional tumor volume (FTV) results stored in the SER derived objects are NOT identical to those used in the I‑SPY 2 study due to differences in implementations on different platforms (UCSF in-house software vs. Hologic Inc. AEGIS system). While the differences are generally small and the AEGIS system was validated against the UCSF results in the prior I‑SPY 1 TRIAL, identical results cannot be guaranteed.

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ACRIN 6698 analysis included use of an image quality control system developed specifically for determination of the analyzability of breast DWI for quantitative cancer treatment monitoring. The image quality control system was comprised of three sequential but independent assessment stages: protocol compliance, image quality and usability, and ROI confidence. Since protocol compliance, image quality, and ROI confidence varied between exams for the same patient, each step was performed independently for each MRI exam.

Protocol Compliance Assessment

First, image metadata in DICOM tags was assessed for compliance with specified imaging parameters. Deviations from the specified imaging protocol were documented and classified into minor (non-critical to study aims) and major (critical to the study aims). Images exhibiting major protocol deviations were flagged and omitted from further analysis.

Image Quality and Usability Assessment

Next, the overall image quality and the usability of images for the study endpoints were evaluated. Readers scored image quality using a standard letter grading scale of A (best), B (good), C (average), D (poor) and F (worst) on fat suppression, severity of artifacts (displacement, ghosts, and distortions) and signal-to-noise ratio (SNR). These metrics were selected to reflect the most common and debilitating limitations in breast DWI. Fat suppression and SNR were scored using only the b=0 images while the severity of artifacts was evaluated using all DWI images. Scores were assigned numeric values (A=4 to F=0) and the geometric mean of the scores for fat suppression, artifacts and SNR was computed to yield a composite quality score. Each composite quality score was classified into overall high-, moderate-, or low-quality categories.

Separate from this image quality assessment, a subjective pass/fail assessment was made of image usability for evaluating diffusion parameters such as lesion ADC. This criterion was established to ensure that images of sufficient quality to address the scientific aim of the study were not rejected, e.g., a poor quality score due to excessive imaging artefacts might not result in rejection if the artefacts did not encroach on the region of the enhancing tumor.

ROI Confidence Assessment

After the full multi-slice/multi-region ROIs were placed, they were scored qualitatively based on reader confidence that the ROI faithfully represented the tissue of interest. The goal was to characterize the whole tumor while excluding fat, tissue, and tumor necrosis. ROIs were scored on a numerical scale of 3 for high confidence, 2 for moderate confidence and 1 for low confidence. Inclusion in the primary analysis was determined based on the image quality and ROI confidence assessments.

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Figure 2 shows the enrollment numbers and exclusions used to determine the analysis cohort for the primary analysis. For this TCIA collection we include MRI studies from 385 of the 388 eligible subjects, three being excluded due to having no analyzable MRI studies received by the central imaging lab. The 116 patients excluded from the primary analysis as “Not Randomized” were those screened out of I‑SPY 2, most commonly due to being in the low-risk category (HR+/HER2- subtype with low MammaPrint score). Note that all these patients have baseline MRI studies included in this collection, and some were included in the ACRIN-6698 test/retest repeatability arm. A separate TCIA download option is provided for researchers who wish to focus on the 242-patient cohort used in the primary analysis. These subjects all had MRI studies with DWI scans that passed the QC evaluations at baseline and at least one later time point. One other download option is provided for the 71-patient cohort with analyzable test/retest. The primary aim and test/retest studies are the only ones guaranteed to have tumor segmentations and DWI derived objects in this collection.

Image Added

Figure 2. Derivation of the primary analysis cohort for ACRIN 6698. To be included in the primary analysis patients were required to have analyzable DW-MRI acquisitions at baseline (T0, pre-treatment) and for at least 1 subsequent study time point.

This collection will be sequestered initially for use in the NCI QIN sponsored BMMR2 challenge (Breast Multiparametric MRI for prediction of NAC Response Challenge). For this period data will only be available to researchers registered for this challenge, and will be limited to a reduced set of MRI studies from 191 subjects with analyzable data at all of the 1st three timepoints (i.e. T0, T1, and T2). If you are interested in participating in the BMMR2 challenge please contact David Newitt at david.newitt@ucsf.edu .

Processing and transfer history for MRI studies in this collection

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While every effort was made to preserve the integrity of both the original image data and image meta-data (DICOM attributes, public and private), multiple file transfers and strict adherence to HIPAA guidelines for patient confidentiality may have resulted in loss of some data. If any questions arise, or if any patient PHI is found in any data on this collection, please contact the UCSF Breast Imaging Research Program (BIRP).

Ancillary files for the ACRIN-6698 collection

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  • BMMR2 Challenge patient demographic, clinical and outcome data files for the training and test cohorts (comma-separated text files).
    Due to the ongoing nature of the I‑SPY 2 Trial only this limited set of patient data can be released at this time. Further information will become available with release of further I‑SPY 2 imaging data.
    Training set: <QINChallenge_CaselistTrain_20210108wClinicalData.csv>
    Test set; <QINChallenge_CaselistTest_20210108wClinicalData.csv>

  • Full collection ancillary patient information file (comma-separated text file). Includes clinical and outcome data, DWI Quality Control ratings, and cohort identification.
    This file will be made available at the conclusion of the BMMR2
    <ACRIN_6698_Patient_Cohorts_ClinicalData.csv>
  • ACRIN 6698 MRI protocol parameter specifications

  • DCE analysis mask description. This file provides usage information for the functional tumor volume analysis masks provided as part of the DCE derived objects package
    <Analysis mask files description.docx>

  • DICOM Dictionary for UCSF private attributes
    [[[XXX need to finalize ]]]