MR Correlated Spectroscopic Imaging for Diagnosing Breast Cancer

Early Phase 1CompletedNCT06090630

Jonsson Comprehensive Cancer Center83 enrolled

Overview

This trial studies how well an imaging technique called magnetic resonance (MR) spectroscopic imaging works in identifying breast cancer in women with benign or suspicious areas in the breast. Magnetic resonance imaging (MRI) is a diagnostic tool used to investigate the location of tumors in different organs. Since radiological pictures do not have sufficient information for tumor grades, invasive procedure such as biopsy is performed on patients with breast cancers for diagnosis. Breast tissue contains water, fat, and chemicals known as metabolites. MR spectroscopic imaging may help to characterize the various breast metabolite steady state levels and identify the differences between necrosis and tumor recurrence, which is difficult using radiological procedures such as MRI.

PRIMARY OBJECTIVES: I. Non-uniform undersampling schemes (NUS) will be combined with 5-dimensional (5D) echo-planar imaging based correlated spectroscopic imaging (EP-COSI) sequence. II. Group sparsity (GS)-based compressed-sensing (CS) reconstruction schemes will be developed for accelerated acquisition and optimized to reconstruct the NUS EP-COSI data with better reliability. III. Alterations in metabolite and lipid levels will be correlated with apparent diffusion coefficient (ADC) changes in breast cancer patients compared to healthy women which will improve the diagnostic accuracy. OUTLINE: Participants undergo diffusion weighted imaging (DWI)-MRI over 15 minutes and MR spectroscopic imaging over 45 minutes. After completion of study, participants are followed up for 6 months.

Study Type

INTERVENTIONAL

Allocation

Purpose

DIAGNOSTIC

Masking

NONE

Enrollment

Conditions

Eligibility

Sex: FEMALEMin age: 18 YearsMax age: 80 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: * Malignant tumor subjects must have malignant needle biopsy results with concordant imaging and pathological findings. * Benign tumor subjects must have benign needle biopsy results. Benign subjects will only include those with concordant benign imaging and pathological findings. * Control subjects: healthy and have no previous history of any type of cancers. * The women should be able to read and understand English. Hence, non-English speaking subjects will be excluded. However, if there will be a necessity of translating the written informed consent form in the subject's mother tongue (such as Hispanic, Chinese, Persian, Indian, etc.), the translated consent form will be submitted for expedited approval to the office of University of California, Los Angeles (UCLA) Institutional Review Board (IRB). Exclusion Criteria: * Pregnant women will be excluded. * Breast feeding women. * MR incompatible items: cardiac pacemaker, aneurysm clip, heart valve prosthesis, nitroglycerin transdermal patch, implanted cardiac defibrillator, implanted electrode, including pacing wires, cochlear implant, other, implanted drug infusion device, implanted insulin pump, intravascular coil, filter or stent: (e.g., Gianturco coil, Gunther inferior vena cava \[IVC\] filter, etc.), intraventricular shunt, neurostimulator/biostimulator, Swan-Ganz catheter, any type of electronic, mechanical or magnetic implant, any type of implant held in place by a magnet, artificial limb or joint, contraceptive device (e.g., intrauterine device \[IUD\], diaphragm), dentures, ear implant, eye/orbital implant, foreign body (e.g., shrapnel, bullet, etc.), halo vest or metallic cervical fixation device, orthopedic item (for example: pins, rods, screws, clips, plates, wires, etc.), surgical clip or staple, vascular access port, wire mesh, hearing aid (must remove prior to the exam), tattooed eyeliner (a small percentage of patients with tattooed eyeliner have experienced transient skin irritation in association with MRI). The patients using transdermal patches will be asked to remove the patch and will be excluded if the patch cannot be removed.

Outcomes

Primary Outcomes

Apparent diffusion coefficient (ADC) maps

ADC maps will be calculated from diffusion weighted (DW) images by using linear regression of logarithmic intensities by using software for combinations of two, three, four, and five DW images with different b values. ADC maps will also be calculated for the remaining combinations of up to 10 evenly distributed b values. In total, 501 value combinations will be automatically processed and analyzed.

Time frame: At the time of imaging