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This paper updates and extends three previous papers on tissue property filters (TP-filters), Multiplied, Added, Divided and/or Subtracted Inversion Recovery (MASTIR) pulse sequences and synergistic contrast MRI (scMRI). It does this by firstly adding the central contrast theorem (CCT) to TP-filters, secondly including division with MASTIR sequences to make them Multiplied, Added, Subtracted and/or Divided IR (MASDIR) sequences, and thirdly incorporating division into the image processing needed for scMR to increase synergistic T1 contrast. These updated concepts are then used to explain and improve contrast at tissue boundaries, as well as to develop imaging regimes to detect and monitor small changes to the brain over time and quantify T1. The CCT is in two parts: the first part states that contrast produced by each TP is the product of the change in TP multiplied by the TP sequence weighting which is the first partial derivative of the TP-filter. The second part states that the overall fractional contrast is the algebraic sum of the fractional contrasts produced by each of the TPs. Subtraction of two IR sequences alone about doubles contrast relative to a conventional single IR sequence. Division of this subtraction can amplify contrast 5-15 times compared with conventional IR sequences. Dividing sequences can be problematic in areas where the signal is zero but this is avoided by dividing the difference in signal of two magnitude reconstructed IR sequences by the sum of their signals. The basis for the production of high contrast, high spatial resolution boundaries at white-gray matter junctions, between cerebral cortex and cerebrospinal fluid (CSF) and at other sites with subtracted IR (SIR) and divided subtracted IR (dSIR) sequences is explained and examples are shown. A key concept is the tissue fraction f, which is the proportion of a tissue in a mixture of two tissues within a voxel. Contrast at boundaries is a function of the partial derivative of the TP-filter, the partial derivative of the relevant TP with respect to f, and the partial derivative of f with respect to distance, x. Location of tissue boundaries is important for segmentation and is helpful in determining if inversion times have been chosen correctly. In small change regimes, the high sensitivity to small changes in T1 provided by dSIR images, together with the high definition boundaries, afford mechanisms for detecting small changes due to contrast agents, disease, perfusion and other causes. 3D isotropic rigid body registration provides a technique for following these changes over time in serial studies. Images showing high lesion contrast, high definition tissue and fluid boundaries, and the detection of small changes are included. T1 maps can be created by linearly scaling dSIR images.

This review describes targeted magnetic resonance imaging (tMRI) of small changes in the T 1 and the spatial properties of normal or near normal appearing white or gray matter in disease of the brain. It employs divided subtracted inversion recovery (dSIR) and divided reverse subtracted inversion recovery (drSIR) sequences to increase the contrast produced by small changes in T 1 by up to 15 times compared to conventional T 1 -weighted inversion recovery (IR) sequences such as magnetization prepared-rapid acquisition gradient echo (MP-RAGE). This increase in contrast can be used to reveal disease with only small changes in T 1 in normal appearing white or gray matter that is not apparent on conventional MP-RAGE, T 2 -weighted spin echo (T 2 -wSE) and/or fluid attenuated inversion recovery (T 2 -FLAIR) images. The small changes in T 1 or T 2 in disease are insufficient to produce useful contrast with conventional sequences. To produce high contrast dSIR and drSIR sequences typically need to be targeted for the nulling TI of normal white or gray matter, as well as for the sign and size of the change in T 1 in these tissues in disease. The dSIR sequence also shows high signal boundaries between white and gray matter. dSIR and drSIR are essentially T 1 maps. There is a nearly linear relationship between signal and T 1 in the middle domain (mD) of the two sequences which includes T 1 s between the nulling T 1 s of the two acquired IR sequences. The drSIR sequence is also very sensitive to reductions in T 1 produced by Gadolinium based contrast agents (GBCAs), and when used with rigid body registration to align three-dimensional (3D) isotropic pre and post GBCA images may be of considerable value in showing subtle GBCA enhancement. In serial MRI studies performed at different times, the high signal boundaries generated by dSIR and drSIR sequences can be used with rigid body registration of 3D isotropic images to demonstrate contrast arising from small changes in T 1 (without or with GBCA enhancement) as well as small changes in the spatial properties of normal tissues and lesions, such as their site, shape, size and surface. Applications of the sequences in cases of multiple sclerosis (MS) and methamphetamine dependency are illustrated. Using targeted narrow mD dSIR sequences, widespread abnormalities were seen in areas of normal appearing white matter shown with conventional T 2 -wSE and T 2 -FLAIR sequences. Understanding of the features of dSIR and drSIR images is facilitated by the use of their T 1 -bipolar filters; to explain their targeting, signal, contrast, boundaries, T 1 mapping and GBCA enhancement. Targeted MRI (tMRI) using dSIR and drSIR sequences may substantially improve clinical MRI of the brain by providing unequivocal demonstration of abnormalities that are not seen with conventional sequences., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-23-232/coif). JD serves as an unpaid editorial board member of Quantitative Imaging in Medicine and Surgery. MNJP is a scientific and technical adviser to Magnetica, Brisbane, Australia. GMB is a clinical consultant to Magnetica, Brisbane, Australia. The other authors have no conflicts of interest to declare., (2023 Quantitative Imaging in Medicine and Surgery. All rights reserved.)