This study determined if the magnetic resonance imaging (MRI) protocol used alters the estimation of change in abdominal fat with weight loss in obese type 2 diabetic women. This study also examined if there is a uniform fat loss across the abdomen.Thirty-three obese postmenopausal women with type 2 diabetes (age 50-70 years, body mass index>30 kg/m(2)) had a total abdominal MRI scan pre- and post weight loss intervention. Three different MRI analysis protocols were used and compared: a single slice at L(2)-L(3) vs five slices (centered at L(4)-L(5)) vs all abdominal slices. In addition, the total abdominal scan was divided into four regions (four slices each) with region 3 (critical region) including the traditionally studied L(2)-L(3), and regions 1 and 2 superior and region 4 inferior to critical region 3. Analysis of variance (ANOVA) with repeated measures was used to compare the influence of weight loss on abdominal fat measured both regionally and using the varying number of MR slices.At baseline, the ratio of visceral adipose tissue:subcutaneous adipose tissue (VAT:SAT) was significantly lower using the single-slice method compared to five slices and the total abdomen (P<0.01). Using the single-slice method, a lower %VAT was found than with the other methods (P<0.01). In regions 1, 2, 3, and 4, the absolute change in total fat was 122+/-50, 182+/-48, 182+/-55, and 155+/-40 cm(3), respectively. The regional difference in abdominal fat patterning revealed that the critical region (region 3) had a smaller VAT:SAT ratio than regions 1 and 2 (P<0.05), and the ratio at region 4 was smaller than region 3 (P<0.05). Weight loss resulted in a decrease in the VAT:SAT ratio (P<0.05) for regions 3 and 4 but not for regions 1 and 2.The number of MR slices analyzed yields differential result in relative VAT distribution. Regional differences in abdominal fat loss occur with a greater relative VAT loss in the critical region, thus if only the critical region is analyzed the overall VAT loss induced by weight loss intervention may be overestimated.