Surgeon Attitudes and Use of MRI in Patients Newly Diagnosed with Breast Cancer

Morrow, Monica; Hawley, Sarah T.; McLeod, M. Chandler; Hamilton, Ann S.; Ward, Kevin C.; Jagsi, Reshma

doi:10.1245/s10434-017-5840-4

Cited by 10 publications

(1 citation statement)

References 24 publications

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“…However, MRI accuracy is still below 80% for predicting pathologic response, and MRI use in earlier stage breast cancer is variable across treatment centers (22). Further, the use of MRI in early-stage breast cancer remains controversial because of unclear effects on long term outcomes and concerns about over diagnosis of incidental indolent lesions (23,24).…”

Section: Introductionmentioning

confidence: 99%

Reconstructing tumor trajectories during therapy through integration of multiple measurement modalities

Griffiths

Chen

O’Dea

et al. 2021

Preprint

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BackgroundAccurately determining changes in tumor size during therapy is essential to evaluating response or progression. However, individual imaging methodologies often poorly reflect pathologic response and long-term treatment efficacy in patients with estrogen receptor positive (ER+) early-stage breast cancer. Mathematical models that measure tumor progression over time by integrating diverse imaging and tumor measurement modalities are not currently used but could increase accuracy in measuring response and provide biological insights into cancer evolution.MethodsFor ER+ breast cancer patients enrolled on a neoadjuvant clinical trial, we reconstructed their tumor size trajectories during therapy by combining all available information on tumor size, including different imaging modalities, physical examinations and pathological assessment data. Tumor trajectories during six months of treatment were generated, using a Gaussian process and the most probable trajectories were evaluated, based on clinical data, using measurement models that account for biases and differences in precision between tumor measurement methods, such as MRI, ultrasound and mammograms.ResultsReconstruction of tumor trajectories during treatment identified five distinct patterns of tumor size changes, including rebound growth not evident from any single modality. These results increase specificity to distinguish innate or acquired resistance compared to using any single measurement alone. The speed of therapeutic response and extent of subsequent rebound tumor growth quantify sensitivity or resistance in this patient population.ConclusionsTumor trajectory reconstruction integrating multiple modalities of tumor measurement accurately describes tumor progression on therapy and reveals various patterns of patient responses. Mathematical models can integrate diverse response assessments and account for biases in tumor measurement, thereby providing insights into the timing and rate at which resistance emerges.

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Section: Introductionmentioning

confidence: 99%