Probing structure of normal and malignant prostate tissue before and after radiation therapy with luminal water fraction and diffusion-weighted MRI

Emerging and anticipated innovations in prostate cancer MRI and their impact on patient care

Prostate cancer (PCa) remains the leading malignancy affecting men, with over 3 million men living with the disease in the US, and an estimated 288,000 new cases and almost 35,000 deaths in 2023 in the United States alone. Over the last few decades, imaging has been a cornerstone in PCa care, with a crucial role in the detection, staging, and assessment of PCa recurrence or by guiding diagnostic or therapeutic interventions. To improve diagnostic accuracy and outcomes in PCa care, remarkable advancements have been made to different imaging modalities in recent years. This paper focuses on reviewing the main innovations in the field of PCa magnetic resonance imaging, including MRI protocols, MRI-guided procedural interventions, artificial intelligence algorithms and positron emission tomography, which may impact PCa care in the future.

MRI-based virtual pathology of the prostate

Prostate cancer poses significant diagnostic challenges, with conventional methods like prostate-specific antigen (PSA) screening and transrectal ultrasound (TRUS)-guided biopsies often leading to overdiagnosis or miss clinically significant cancers. Multiparametric MRI (mpMRI) has emerged as a more reliable tool. However, it is limited by high inter-observer variability and radiologists missing up to 30% of clinically significant cancers. This article summarizes a few of these recent advancements in quantitative MRI techniques that look at the "Virtual Pathology" of the prostate with an aim to enhance prostate cancer detection and characterization. These techniques include T2 relaxation-based techniques such as luminal water imaging, diffusion based such as vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT) and restriction spectrum imaging or combined relaxation-diffusion techniques such as hybrid multi-dimensional MRI (HM-MRI), time-dependent diffusion imaging, and diffusion-relaxation correlation spectrum imaging. These methods provide detailed insights into underlying prostate microstructure and tissue composition and have shown improved diagnostic accuracy over conventional MRI. These innovative MRI methods hold potential for augmenting mpMRI, reducing variability in diagnosis, and paving the way for MRI as a 'virtual histology' tool in prostate cancer diagnosis. However, they require further validation in larger multi-center clinical settings and rigorous in-depth radiological-pathology correlation are needed for broader implementation.

The impeded diffusion fraction quantitative imaging assay demonstrated in multi-exponential diffusion phantom and prostate cancer

PURPOSE

To demonstrate a method for quantification of impeded diffusion fraction (IDF) using conventional clinical DWI protocols.

METHODS

The IDF formalism is introduced to quantify contribution from water coordinated by macromolecules to DWI voxel signal based on fundamentally different diffusion constants in vascular capillary, bulk free, and coordinated water compartments. IDF accuracy was studied as a function of b-value set. The IDF scaling with restricted compartment size and polyvinylpirrolidone (PVP) macromolecule concentration was compared to conventional apparent diffusion coefficient (ADC) and isotropic kurtosis model parameters for a diffusion phantom. An in vivo application was demonstrated for six prostate cancer (PCa) cases with low and high grade lesions annotated from whole mount histopathology.

RESULTS

IDF linearly scaled with known restricted (vesicular) compartment size and PVP concentration in phantoms and increased with histopathologic score in PCa (from median 9% for atrophy up to 60% for Gleason 7). IDF via non-linear fit was independent of b-value subset selected between b = 0.1 and 2 ms/µm² , including standard-of-care (SOC) PCa protocol. With maximum sensitivity for high grade PCa, the IDF threshold below 51% reduced false positive rate (FPR = 0/6) for low-grade PCa compared to apparent diffusion coefficient (ADC > 0.81 µm² /ms) of PIRADS PCa scoring (FPR = 3/6).

CONCLUSION

The proposed method may provide quantitative imaging assays of cancer grading using common SOC DWI protocols.

Artificial intelligence and imaging biomarkers for prostate radiation therapy during and after treatment

Magnetic resonance imaging (MRI) is increasingly used in the management of prostate cancer (PCa). Quantitative MRI (qMRI) parameters, derived from multi-parametric MRI, provide indirect measures of tumour characteristics such as cellularity, angiogenesis and hypoxia. Using Artificial Intelligence (AI), relevant information and patterns can be efficiently identified in these complex data to develop quantitative imaging biomarkers (QIBs) of tumour function and biology. Such QIBs have already demonstrated potential in the diagnosis and staging of PCa. In this review, we explore the role of these QIBs in monitoring treatment response during and after PCa radiotherapy (RT). Recurrence of PCa after RT is not uncommon, and early detection prior to development of metastases provides an opportunity for salvage treatments with curative intent. However, the current method of monitoring treatment response using prostate-specific antigen levels lacks specificity. QIBs, derived from qMRI and developed using AI techniques, can be used to monitor biological changes post-RT providing the potential for accurate and early diagnosis of recurrent disease.

New options for increasing the sensitivity, specificity and scope of synergistic contrast magnetic resonance imaging (scMRI) using Multiplied, Added, Subtracted and/or FiTted (MASTIR) pulse sequences

This paper reviews magnetic resonance (MR) pulse sequences in which the same or different tissue properties (TPs) such as T1 and T2 are used to contribute synergistically to lesion contrast. It also shows how synergistic contrast can be created with Multiplied, Added, Subtracted and/or fiTted Inversion Recovery (MASTIR) sequences, and be used to improve the sensitivity, specificity and scope of clinical magnetic resonance imaging (MRI) protocols. Synergistic contrast can be created from: (i) the same TP, e.g., T1 used twice or more in a pulse sequence; (ii) different TPs such as ρm, T1, T2, and D* used once or more within a sequence, and (iii) additional suppression or reduction of signals from tissues and/or fluids such as fat, long T2 tissues and cerebrospinal fluid (CSF). The short inversion time (TI) inversion recovery (IR) (STIR) and double IR (DIR) sequences usually show synergistic positive contrast for lesions which have increases in both T1 and T2. The diffusion weighted pulsed gradient spin echo (PGSE) sequence shows synergistic contrast for lesions which have an increase in T2 and a decrease in D*; the sequence is both positively weighted for T2 and negatively weighted for D*. In the brain, when an IR sequence nulling white matter has subtracted from it an IR sequence nulling gray matter to form the subtracted IR (SIR) sequence, increases in the single TP T1 between the two nulling points of the original two sequences generate high synergistic positive contrast. In addition, the subtraction to produce the SIR sequence reduces fat and CSF signals. To provide high sensitivity to changes in TPs in disease the SIR sequence can be used (i) alone to provide synergistic T1 contrast as above; (ii) with T2-weighting to provide synergistic T1 and T2 contrast, and (iii) with T2- and D*-weighting to provide synergistic T1, T2, and D* contrast. The SIR sequence can also be used in reversed form (longer TI form minus shorter TI form) to produce very high positive synergistic T1 contrast for reductions in T1, and so increase the positive contrast enhancement produced by clinical gadolinium-based contrast agents (GBCAs) when they reduce T1. The specificity of MRI examinations can be improved by using the reversed SIR sequence with a long echo time (TE) gradient echo as well as echo subtraction to show synergistic high contrast from T1 and T2* shortening produced by organic iron. Other added and subtracted forms of the MASTIR sequence can be used synergistically to selectively show myelin, myelin water and fluids including blood and CSF. Protocols using MASTIR sequences to provide synergistic contrast in MRI of the brain, prostate and articular cartilage are included as illustrative examples, and the features of synergistic contrast MRI (scMRI) are compared to those of multiparametric MRI (mpMRI) and functional MRI (fMRI).

Luminal Water Imaging: Comparison With Diffusion-Weighted Imaging (DWI) and PI-RADS for Characterization of Prostate Cancer Aggressiveness

BACKGROUND

Luminal water imaging (LWI), a multicomponent T₂ mapping technique, has shown promise for prostate cancer (PCa) detection and characterization.

PURPOSE

To 1) quantify LWI parameters and apparent diffusion coefficient (ADC) in PCa and benign peripheral zone (PZ) tissues; and 2) evaluate the diagnostic performance of LWI, ADC, and PI-RADS parameters for differentiation between low- and high-grade PCa lesions.

STUDY TYPE

Prospective.

SUBJECTS

Twenty-six PCa patients undergoing prostatectomy (mean age 59 years, range 46-72 years).

FIELD STRENGTH/SEQUENCE

Multiparametric MRI at 3.0T, including diffusion-weighted imaging (DWI) and LWI T₂ mapping.

ASSESSMENT

LWI parameters and ADC were quantified in index PCa lesions and benign PZ.

STATISTICAL TESTS

Differences in MRI parameters between PCa and benign PZ were assessed using Wilcoxon signed tests. Spearman correlation of pathological grade group (GG) with LWI parameters, ADC, and PI-RADS was evaluated. The utility of each of the parameters for differentiation between low-grade (GG ≤2) and high-grade (GG ≥3) PCa was determined by Mann-Whitney U tests and ROC analyses.

RESULTS

Twenty-six index lesions were analyzed (mean size 1.7 ± 0.8 cm, GG: 1 [n = 1; 4%], 2 [n = 14, 54%], 3 [n = 8, 31%], 5 [n = 3, 12%]). LWI parameters and ADC both showed high diagnostic performance for differentiation between benign PZ and PCa (highest area under the curve [AUC] for LWI parameter T_2,short [AUC = 0.98, P < 0.001]). The LWI parameters luminal water fraction (LWF) and amplitude of long T₂ component A_long significantly correlated with GG (r = -0.441, P = 0.024 and r = -0.414, P = 0.036, respectively), while PI-RADS, ADC, and the other LWI parameters did not (P = 0.132-0.869). LWF and A_long also showed significant differences between low-grade and high-grade PCa (AUC = 0.776, P = 0.008 and AUC = 0.758, P = 0.027, respectively). Maximum diagnostic performance for discrimination of high-grade PCa was found with combined LWI parameters (AUC 0.891, P = 0.001).

DATA CONCLUSION

LWI parameters, in particular in combination, showed superior diagnostic performance for differentiation between low-grade and high-grade PCa compared to ADC and PI-RADS assessment. J. Magn. Reson. Imaging 2020;52:271-279.