The spinopelvic alignment is often assessed via the Pelvic Incidence-Lumbar Lordosis (PI-LL) mismatch. Here we describe and validate a simplified method to evaluating the spinopelvic alignment through the L1-Pelvis angle (L1P). This method is set to reduce the operator error and make the on-film measurement more practicable.

126 standing lateral radiographs of patients presenting for Total Hip Arthroplasty were examined. Three operators were recruited to label 6 landmarks. One operator repeated the landmark selection for intra-operator analysis. We compare PI-LL mismatch obtained via the conventional method, and our simplified method where we estimate this mismatch using PI-LL = L1P - 90°. We also assess the method's reliability and repeatability.

We found no significant difference (p > 0.05) between the PI-LL mismatch from the conventional method (mean 0.22° ± 13.6) compared to L1P method (mean 0.0° ± 13.1). The overall average normalised root mean square error (NRMSE) for PI-LL mismatch across all operators is 7.53% (mean -3.3° ± 6.0) and 6.5% (mean -2.9° ± 4.9) for the conventional and L1P method, respectively. In relation to intra-operator repeatability, the correlation coefficients are 0.87 for PI, 0.94 for LL, and 0.96 for L1P. NRMSE between the two measurement sets are PI: 9.96%, LL: 5.97%, and L1P: 4.41%. A similar trend is observed in the absolute error between the two sets of measurements.

Results indicate an equivalence in PI-LL measurement between the methods. Reproducibility of the measurements and reliability between operators were improved. Using the L1P angle, the classification of the sagittal spinal deformity found in the literature translates to: normal L1P<100°, mild 100°<L1P<110°, and severe L1P>110°. Surgeons adopting our method should expect a small improvement in reliability and repeatability of their measurements, and a significant improvement of the assessment of the mismatch through the visualisation of the angle L1P.

Human error is usually evaluated using statistical descriptions during radiographic annotation. The technological advances popularized the “non-human” landmarking techniques, such as deep learning, in which the error is presented in a confidence format that is not comparable to that of the human method. The region-based landmark definition makes an arbitrary “ground truth” point impossible. The differences in patients’ anatomies, radiograph qualities, and scales make the horizontal comparison difficult. There is a demand to quantify the manual landmarking error in a probability format.

Taking the measurement of pelvic tilt (PT) as an example, this study recruited 115 sagittal pelvic radiographs for the measurement of two PTs. We proposed a method to unify the scale of images that allows horizontal comparisons of landmarks and calculated the maximum possible error using a density vector. Traditional descriptive statistics were also applied.

All measurements showed excellent reliabilities (intraclass correlation coefficients > 0.9). Eighty-four measurements (6.09%) were qualified as wrong landmarks that failed to label the correct locations. Directional bias (systematic error) was identified due to cognitive differences between observers. By removing wrong labels and rotated pelves, the analysis quantified the error density as a “good doctor” performance and found 6.77°-11.76° maximum PT disagreement with 95% data points.

The landmarks with excellent reliability still have a chance (at least 6.09% in our case) of making wrong landmark decisions. Identifying skeletal contours is at least 24.64% more accurate than estimating landmark locations. The landmark at a clear skeletal contour is more likely to generate systematic errors. Due to landmark ambiguity, a very careful surgeon measuring PT could make a maximum 11.76° random difference in 95% of cases, serving as a “good doctor benchmark” to qualify good landmarking techniques.

Pelvic tilt (PT) is always described as the pelvic orientation along the transverse axis, yet four PT definitions were established based on different radiographic landmarks: anterior pelvic plane (PT_a), the centres of femoral heads and sacral plate (PT_m), pelvic outlet (PT_h), and sacral slope (SS). These landmarks quantify a similar concept, yet understanding of their relationships is lacking. Some studies referred to the words “pelvic tilt” for horizontal comparisons, but their PT definitions might differ. There is a demand for understanding their correlations and differences for education and research purposes.

This study recruited 105 sagittal pelvic radiographs (68 males and 37 females) from a single clinic awaiting their hip surgeries. Hip hardware and spine pathologies were examined for sub-group analysis. Two observers annotated four PTs in a gender-dependent manner and repeated it after six months. The linear regression model and intraclass correlation coefficient (ICC) were applied with a 95% significance interval.

The SS showed significant gender differences and the lowest correlations to the other parameters in the male group (-0.3< r <0.2). The correlations of SS in scoliosis (n = 7) and hip implant (female, n = 18) groups were statistically different, yet the sample sizes were too small. PT_m demonstrated very strong correlation to PT_h (r > 0.9) under the linear model PT_m = 0.951 × PT_h - 68.284.

The PT_m and PT_h are interchangeable under a simple linear regression model, which enables study comparisons between them. In the male group, SS is more of a personalised spinal landmark independent of the pelvic anatomy. Female patients with hip implant may have more static spinopelvic relationships following a certain pattern, yet a deeper study using a larger dataset is required. The understanding of different PTs improves anatomical education.

Accurate measurement of pelvic tilt (PT) is critical in diagnosing hip and spine pathologies. Yet a sagittal pelvic radiograph with good quality is not always available. Studies explored the correlation between PT and sacro-femoral-pubic (SFP) angle from anteroposterior (AP) radiographs yet demonstrated conflicting conclusions about its feasibilities. This study aims to perform a cohort-controlled meta-analysis to examine the correlation between the SFP angle and PT and proposes an application range of the method.

This study searched PubMed, Embase, Cochrane, and Web of Science databases for studies that evaluated the correlation between SFP angle and PT. The Pearson's correlation coefficient r from studies were tabulated and compared. Pooled r for overall and gender/age (teenage or adult) controlled subgroup were reported using Fisher's Z transformation. Heterogeneity and publication bias were evaluated using Egger's regression test for the funnel plot asymmetry.

Eleven studies were recruited, with nine reported r (totalling 1,247 patients). The overall pooled r was 0.61 with high inter-study heterogeneity (I2 = 75.95%). Subgroup analysis showed that the adult group had a higher r than the teenage group (0.70 versus 0.56, p < 0.001). Although statistically insignificant (p = 0.062), the female group showed a higher r than the male group (0.72 versus 0.65).

The SFP method must be used with caution and should not be used in the male teenage group. The current studies did not demonstrate that the SFP method was superior to other AP landmarks correlating to PT. Identical heterogeneity was observed among studies, indicating that more ethnicity-segregated and gender-specific subgroup studies might be necessary. More data input analysing the errors will be useful.