Objective <p>Current liver T1 mapping methods present restricted liver coverage, take long acquisition times and mostly exclude the T1 bias induced by fat and iron effects. We evaluated the clinical feasibility of an accelerated water T1 (wT1) mapping method, including all liver segments and the potential of its T2*-compensation (wT1_comp) for fibrosis tissue assessment.</p> Materials and methods <p>Forty-three patients were classified into three groups: benign without/with risk of developing fibrosis and hepatocellular carcinoma (HCC). A 9-slice accelerated single-shot spiral continuous inversion-recovery Look-Locker (CIR-LL) wT1 mapping acquisition, performed in an 11-s breath-hold, and clinical images (proton density fat fraction (PDFF), T2*, T1- and T2-weighted) were acquired for all patients. ROIs were defined on the PDFF, T2* and wT1 maps in all liver segments. wT1_comp was estimated based on the wT1-T2* correlation of the benign-no-risk group and was compared to wT1 and clinical images inspecting for fibrosis.</p> Results <p>For each patient group, wT1 maps presented broad liver coverage, capturing all liver segments. T2* and wT1 measurements of the benign-no-risk group were significantly correlated <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(({{{\rm{wT}}}}1=12.78* {{{{\rm{T}}}}2}^{* }+481.45{{{\rm{;\; r}}}}=0.78,\,p \, &lt; \,0.001)\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo>(</mo> <mrow> <mi mathvariant="normal">wT</mi> <mn>1</mn> <mo>=</mo> <mn>12.78</mn> <mo>*</mo> <msup> <mrow> <mi mathvariant="normal">T</mi> <mn>2</mn> </mrow> <mrow> <mo>*</mo> </mrow> </msup> <mo>+</mo> <mn>481.45</mn> <mi mathvariant="normal">; r</mi> <mo>=</mo> <mn>0.78</mn> <mo>,</mo> <mspace width="0.25em" /> <mi>p</mi> <mspace width="0.25em" /> <mo>&lt;</mo> <mspace width="0.25em" /> <mn>0.001</mn> </mrow> <mo>)</mo> </mrow> </math></EquationSource> </InlineEquation> and the T2*-compensation model was defined by <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\({{{{\rm{wT}}}}1}_{{{{\rm{comp}}}}}={{{\rm{wT}}}}1{minus}\,12.78* ({{{{\rm{T}}}}2}^{* }\,{minus}\,22)\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mrow> <mi mathvariant="normal">wT</mi> <mn>1</mn> </mrow> <mrow> <mi mathvariant="normal">comp</mi> </mrow> </msub> <mo>=</mo> <mi mathvariant="normal">wT</mi> <mn>1</mn> <mi>m</mi> <mi>i</mi> <mi>n</mi> <mi>u</mi> <mi>s</mi> <mspace width="0.25em" /> <mn>12.78</mn> <mo>*</mo> <mrow> <mo>(</mo> <mrow> <msup> <mrow> <mi mathvariant="normal">T</mi> <mn>2</mn> </mrow> <mrow> <mo>*</mo> </mrow> </msup> <mspace width="0.25em" /> <mi>m</mi> <mi>i</mi> <mi>n</mi> <mi>u</mi> <mi>s</mi> <mspace width="0.25em" /> <mn>22</mn> </mrow> <mo>)</mo> </mrow> </math></EquationSource> </InlineEquation>. Liver segments of the same patient presented different wT1 values. Outperforming wT1, wT1_comp identified 21 liver segments from nine patients associated with qualitative fibrosis findings in clinical images, some only visible in post-contrast T1-weighted images.</p> Conclusion <p>The wT1 method is feasible for fast broad liver coverage in patients with HCC or benign lesions. The segments-based wT1_comp analysis shows potential for noninvasive contrast-free qualitative liver fibrosis assessment.</p> Relevance statement <p>The proposed water-specific T1 mapping method, its T2*-compensation and the inclusion of all liver segments could be clinically relevant for the tissue signal assessment of fibrotic liver segments without contrast agent administration.</p> Key Points <p><UnorderedList Mark="Bullet"> <ItemContent> <p>The developed water T1 (wT1) method enables broad liver coverage in a single 11-s breath-hold.</p> </ItemContent> <ItemContent> <p>Liver wT1 mapping and the proposed T2*-compensation (wT1_comp) remove the bias in T1 induced by fat and iron, respectively.</p> </ItemContent> <ItemContent> <p>The analysis in all liver segments allows the assessment of focal liver changes.</p> </ItemContent> <ItemContent> <p>The proposed liver segments-based wT1_comp method presents potential to identify tissue signal changes associated with fibrosis.</p> </ItemContent> </UnorderedList></p> Graphical Abstract <p></p>