ROCKETSHIP: a flexible and modular software tool for the planning, processing and analysis of dynamic MRI studies

Barnes, Samuel R.; Ng, Thomas S. C.; Santa-Maria, Naomi; Montagne, Axel; Zlokovic, Berislav V.; Jacobs, Russell E.

doi:10.1186/s12880-015-0062-3

BMC Medical Imaging

Table 3 Concordance correlation coefficients (CCC) comparing fitted and simulated Ktrans using different models and dependent parameters

From: ROCKETSHIP: a flexible and modular software tool for the planning, processing and analysis of dynamic MRI studies

Generating model	Fitting model	Time resolution (s)	SNR	Dependent parameter	vp = 0.001	0.005	0.01	0.02	0.05	0.1
Patlak	Patlak	0.5	5	vp	1.00	1.00	1.00	1.00	1.00	1.00
		0.5	100	vp	1.00	1.00	1.00	1.00	1.00	1.00
		6	5	vp	0.98	0.98	0.98	0.98	0.98	0.98
		6	100	vp	1.00	1.00	1.00	1.00	1.00	1.00
					ve = 0.01	0.02	0.05	0.1	0.2	0.5
Tofts	Tofts	0.5	5	ve	0.38	0.85	0.98	0.99	1.00	1.00
		0.5	100	ve	1.00	1.00	1.00	1.00	1.00	1.00
		6	5	ve	0.08	0.32	0.76	0.92	0.96	0.97
		6	100	ve	0.67	0.92	1.00	1.00	1.00	1.00
					ve = 0.01	0.02	0.05	0.1	0.2	0.5
Ex-Tofts	Ex-Tofts	0.5	5	ve	0.01	0.33	0.95	0.99	1.00	1.00
		0.5	100	ve	0.92	1.00	1.00	1.00	1.00	1.00
		6	5	ve	−0.02	0.05	0.41	0.84	0.96	0.98
		6	100	ve	0.22	0.48	0.98	1.00	1.00	1.00
					vp = 0.001	0.005	0.01	0.02	0.05	0.1
		0.5	5	vp	0.74	0.73	0.71	0.68	0.61	0.51
		0.5	100	vp	0.99	0.98	0.98	0.99	0.99	0.98
		6	5	vp	0.57	0.58	0.57	0.56	0.45	0.41
		6	100	vp	0.89	0.90	0.88	0.81	0.54	0.35
					ve = 0.01	0.02	0.05	0.1	0.2	0.5
2CXM	2CXM	0.5	5	ve	−0.02	−0.02	0.11	0.22	0.65	0.90
		0.5	100	ve	0.07	0.42	0.65	0.76	0.98	0.99
		6	5	ve	−0.01	−0.01	−0.01	0.10	0.52	0.84
		6	100	ve	−0.03	−0.06	0.04	0.38	0.84	0.98
					vp = 0.001	0.005	0.01	0.02	0.05	0.1
		0.5	5	vp	0.18	0.20	0.23	0.31	0.43	0.47
		0.5	100	vp	0.32	0.63	0.72	0.76	0.76	0.74
		6	5	vp	0.20	0.19	0.21	0.21	0.28	0.29
		6	100	vp	0.18	0.26	0.34	0.41	0.45	0.45
					Fp = 0.5	1	5
		0.5	5	Fp	0.21	0.30	0.40
		0.5	100	Fp	0.46	0.69	0.81
		6	5	Fp	0.20	0.22	0.27
		6	100	Fp	0.26	0.35	0.43
					vp = 0.001	0.005	0.01	0.02	0.05	0.1
					vp = 0.001	0.005	0.01	0.02	0.05	0.1
		0.5	5	vp	0.98	1.00	0.98	1.00	1.00	1.00
		0.5	100	vp	1.00	1.00	1.00	1.00	1.00	1.00
		6	5	vp	0.88	0.88	0.88	0.91	0.98	0.99
		6	100	vp	1.00	1.00	1.00	1.00	1.00	1.00
Tissue uptake	Tissue uptake	0.5	5	vp	0.98	1.00	0.98	1.00	1.00	1.00
		0.5	100	vp	1.00	1.00	1.00	1.00	1.00	1.00
		6	5	vp	0.88	0.88	0.88	0.91	0.98	0.99
		6	100	vp	1.00	1.00	1.00	1.00	1.00	1.00
					Fp = 0.5	1	5
		0.5	5	Fp	1.00	0.98	1.00
		0.5	100	Fp	1.00	1.00	1.00
		6	5	Fp	0.82	0.97	0.98
		6	100	Fp	1.00	1.00
					ve = 0.01	0.02	0.05	0.1	0.2	0.5
					ve = 0.01	0.02	0.05	0.1	0.2	0.5
		0.5	5	ve	−0.01	0.02	0.08	0.14	0.39	0.95
		0.5	100	ve	0.07	0.31	0.97	1.00	1.00	1.00
		6	5	ve	0.01	−0.01	0.03	0.06	0.12	0.38
		6	100	ve	0.05	0.14	0.71	0.96	0.99	1.00
					τi = 0.1	0.5	2
		0.5	5	τi	0.11	0.14	0.14
		0.5	100	τi	0.56	0.59	0.56
		6	5	τi	0.06	0.07	0.07
		6	100	τi	0.54	0.61	0.52

100 curves for each model and fixed dependent parameter were generated as described in the text and Table 2. Ktrans values simulated are defined in Table 2. The CCC was calculated from the Ktrans (simulated) vs. Ktrans (fitted), such as depicted in Figure 5. Ktrans values from which CCCs were calculated were segregated according to the dependent parameter (vp, ve or Fp). A value of 1 shows near-perfect concordance, while 0 represents a low concordance relationship

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