Diagnostic Clinical Trials in Breast Cancer Brain Metastases

Barriers and Innovations

Jawad Fares, Deepak Kanojia, Aida Rashidi, Atique Uddin Ahmed, Irina V Balyasnikova, Maciej S Lesniak*

*Corresponding author for this work

Research output: Contribution to journalReview article

Abstract

Optimal treatment of breast cancer brain metastases (BCBM) is often hampered by limitations in diagnostic abilities. Developing innovative tools for BCBM diagnosis is vital for early detection and effective treatment. In this study we explored the advances in trial for the diagnosis of BCBM, with review of the literature. On May 8, 2019, we searched ClinicalTrials.gov for interventional and diagnostic clinical trials involving BCBM, without limiting for date or location. Information on trial characteristics, experimental interventions, results, and publications were collected and analyzed. In addition, a systematic review of the literature was conducted to explore published studies related to BCBM diagnosis. Only 9 diagnostic trials explored BCBM. Of these, 1 trial was withdrawn because of low accrual numbers. Three trials were completed; however, none had published results. Modalities in trial for BCBM diagnosis entailed magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), PET-CT, nanobodies, and circulating tumor cells (CTCs), along with a collection of novel tracers and imaging biomarkers. MRI continues to be the diagnostic modality of choice, whereas CT is best suited for acute settings. Advances in PET and PET-CT allow the collection of metabolic and functional information related to BCBM. CTC characterization can help reflect on the molecular foundations of BCBM, whereas cell-free DNA offers new genetic material for further exploration in trials. The integration of machine learning in BCBM diagnosis seems inevitable as we continue to aim for rapid and accurate detection and better patient outcomes.

Original languageEnglish (US)
JournalClinical breast cancer
DOIs
StatePublished - Jan 1 2019

Fingerprint

Brain Neoplasms
Clinical Trials
Breast Neoplasms
Neoplasm Metastasis
Circulating Neoplastic Cells
Single-Domain Antibodies
Magnetic Resonance Imaging
Positron-Emission Tomography
Publications
Biomarkers
Tomography
DNA

Keywords

  • Artificial intelligence
  • Circulating tumor cells
  • Magnetic resonance imaging
  • Nanobody
  • Positron emission tomography

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

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title = "Diagnostic Clinical Trials in Breast Cancer Brain Metastases: Barriers and Innovations",
abstract = "Optimal treatment of breast cancer brain metastases (BCBM) is often hampered by limitations in diagnostic abilities. Developing innovative tools for BCBM diagnosis is vital for early detection and effective treatment. In this study we explored the advances in trial for the diagnosis of BCBM, with review of the literature. On May 8, 2019, we searched ClinicalTrials.gov for interventional and diagnostic clinical trials involving BCBM, without limiting for date or location. Information on trial characteristics, experimental interventions, results, and publications were collected and analyzed. In addition, a systematic review of the literature was conducted to explore published studies related to BCBM diagnosis. Only 9 diagnostic trials explored BCBM. Of these, 1 trial was withdrawn because of low accrual numbers. Three trials were completed; however, none had published results. Modalities in trial for BCBM diagnosis entailed magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), PET-CT, nanobodies, and circulating tumor cells (CTCs), along with a collection of novel tracers and imaging biomarkers. MRI continues to be the diagnostic modality of choice, whereas CT is best suited for acute settings. Advances in PET and PET-CT allow the collection of metabolic and functional information related to BCBM. CTC characterization can help reflect on the molecular foundations of BCBM, whereas cell-free DNA offers new genetic material for further exploration in trials. The integration of machine learning in BCBM diagnosis seems inevitable as we continue to aim for rapid and accurate detection and better patient outcomes.",
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author = "Jawad Fares and Deepak Kanojia and Aida Rashidi and Ahmed, {Atique Uddin} and Balyasnikova, {Irina V} and Lesniak, {Maciej S}",
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Diagnostic Clinical Trials in Breast Cancer Brain Metastases : Barriers and Innovations. / Fares, Jawad; Kanojia, Deepak; Rashidi, Aida; Ahmed, Atique Uddin; Balyasnikova, Irina V; Lesniak, Maciej S.

In: Clinical breast cancer, 01.01.2019.

Research output: Contribution to journalReview article

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T1 - Diagnostic Clinical Trials in Breast Cancer Brain Metastases

T2 - Barriers and Innovations

AU - Fares, Jawad

AU - Kanojia, Deepak

AU - Rashidi, Aida

AU - Ahmed, Atique Uddin

AU - Balyasnikova, Irina V

AU - Lesniak, Maciej S

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