Prostate cancer is the most common form of cancer diagnosed in men, with roughly 241,740 new cases in 2012 in the United States [
1]. Furthermore, prostate cancer is the second leading cause of cancer death in males in the United States, with an estimated 28,170 deaths in 2012 [
1]. Given that the median patient survival time for metastatic prostate cancer ranges from 12.2 to 21.7 months [
2‐
6], early clinical diagnosis of prostate cancer is key to improve the treatment of patients affected by prostate cancer. Traditionally, clinical diagnosis of prostate cancer involves a prostate specific antigen (PSA) screening, where high PSA levels are considered indicative of possible signs of prostate cancer [
7]. However, PSA screening has resulted in significant over-diagnosis of men suspected of having prostate cancer but who do not actually require treatment. As a consequence, many men are over-treated with therapies that carry significant risks in themselves [
8]. Furthermore, there is still no reliable, widely accepted method of diagnostic imaging for prostate cancer. Although transrectal ultrasound (TRUS) is used routinely as a guide for biopsy, it cannot be used to visualize cancer foci because many tumours in the prostate gland are isoechoic and cannot be differentiated from surrounding tissue, resulting in sensitivity and specificity in the range of 40–50% [
9,
10]. Positron emission tomography (PET) have also been investigated as a potential imaging modality for prostate cancer detection, with a number of different tracers that have shown promise for identifying prostate cancer [
11‐
14]. However, the spatial resolution achieved using PET may not be adequate to properly localize and detect early stage prostate cancer [
15]. T2-weighted magnetic resonance imaging (MRI) has also been investigated for prostate cancer detection [
16‐
18], but currently requires highly-qualified subspecialty radiologists to interpret the data due to its weak delineation between cancerous tissue and healthy tissue. Furthermore, in the peripheral zone of the prostate gland, the low T2 signal intensity that is associated with prostate cancer may also be due to a number of noncancerous abnormal conditions such as inflammation and hemorrhaging [
19].
A promising imaging modality for diagnosing prostate cancer is diffusion imaging, where pairs of opposing magnetic field gradient pulses are applied to obtain sensitivity to the Brownian motion of water molecules in tissues [
20]. The differences in diffusion characteristics between tissue types facilitate for tissue characterization. As such, given the presumed high cellular density of prostate cancer, the associated tissues should exhibit restricted diffusion characteristics (and as such should have lower apparent diffusion coefficient (ADC) values). While diffusion imaging shows considerable promise [
21‐
23], particularly when used in multi-parametric imaging scenarios [
24,
25], delineating between cancerous tissue and healthy tissue in the prostate gland remains a challenge, due partly to the necessity for fine-tuning the strength, duration, and timing of the applied diffusion gradient pulses. Other challenges include the multifocality of prostate cancer [
26], as well as the relatively small size of a majority of prostate cancer tumors. Hence, the characteristics between cancerous tissue and healthy tissue may appear to have substantial overlap depending on the way the gradient pulses are applied, thus making it difficult to detect and localize prostate cancer. As such, an alternative form of magnetic resonance imaging that gets around this issue is highly desired.
The main contribution of this study is the introduction of a new form of diffusion magnetic resonance imaging called correlated diffusion imaging (CDI), which takes advantage of the joint correlation in signal attenuation across multiple gradient pulse strengths and timings to not only reduce the dependency on the way diffusion gradient pulses are applied, but also improve delineation between cancerous and healthy tissue. To the best of the authors’ knowledge, there are no previous imaging techniques that take this type of approach to prostate cancer assessment.