Get out those rulers

Everyone with a suspected diagnosis of PSP should have a brain MRI.  It can find more-readily-treated things such as strokes, tumors or normal-pressure hydrocephalus.  But the MRI is not all that useful in differentiating PSP in its early, diagnostically-uncertain, stages from other neurodegenerative conditions such as Parkinson’s, MSA, Alzheimer’s, CBD, dementia with Lewy bodies, and the several forms of FTD.  Even the famous hummingbird sign of PSP doesn’t appear until the middle stages of the disease, by which time a neurologist can make the diagnosis by history and physical exam anyway.  Besides, any disorder that causes atrophy of the midbrain will produce a hummingbird sign.

But now, researchers at the University of California, San Francisco and the Universitat Autònoma de Barcelona have used an automated system to measure the degree of atrophy of several areas of brain as seen on MRI.  The system, called “FreeSurfer,” is in standard use in research requiring MRI measurements. The lead author was Ignacio Illán-Gaia and the senior author was Adam Boxer.  All of their 326 subjects had been evaluated at UCSF’s Memory and Aging Center between 1994 and 2019.  The diagnosis in each case was later established at autopsy – a major scientific strength of this study.  Autopsy showed PSP in 68, CBD in 44, various forms of FTD in 144, Alzheimer’s in 45, and PD, MSA or DLB in only 11.

The four brain areas chosen for analysis were all previously known to atrophy in PSP: cerebral cortex, midbrain, pons and superior cerebellar peduncle.  (The midbrain and pons are in the brainstem and the SCP is one of three tracts connecting the cerebellum to the rest of the brain.)  They used not only the size of each, but also a previously reported index called the “magnetic resonance parkinsonism index” (MRPI), a formula involving the size of the midbrain, pons, SCP and middle cerebellar peduncle. (See note below for details.) The MRPI does very well in distinguishing PSP from PD, but has not been adequately evaluated against all possible alternative diagnoses.  Actually, an updated version called “MRPI 2.0” can distinguish PSP from MSA because it takes into account atrophy of the thalamus, but it’s too new to have an automated version, so this project satisfied itself with the MRPI.

The result was that the MRPI showed an excellent ability to distinguish PSP from the other diseases as a group.  The area under the receiver operating curve (AUROC; see my previous post for an explanation) was excellent: 0.90 of a possible 1.00.  But the AUROC for distinguishing PSP from CBD was only moderate at 0.83.  A more sophisticated statistical analysis, a “multiple logistic regression model” (MLRM), worked even better, distinguishing PSP from the others with a superb AUROC of 0.98.  The CBD- vs-others comparison also benefited from the MLRM, rising to 0.86.

To put the AUROC into more-relatable terms: The AUROC of 0.98 in this case corresponds to an “accuracy” of 95%.  That means that the MLRM got the diagnosis correct (i.e., PSP or not PSP) in 95% of patients.  But that simple calculation can be misleading, which is why the AUROC is used by researchers. 

As mentioned above, the total number of patients with PD, DLB and MSA was only 11.  That’s because the study was performed at a memory center, not a movement center.  While the MRPI has proven its utility in distinguishing PSP from PD, the same can’t be said for the PSP vs DLB or the PSP vs MSA comparisons.  So we need more work with a statistically robust number of patients with DLB and MSA.

For an admittedly biased assessment of the importance of this study, here’s Dr. Illán-Gaia in emailed comments in response to my request for a couple of quotable blurbs:

Our study demonstrates in a large autopsy-proven cohort that combining a set of cortical and subcortical measures of cerebral atrophy could represent a powerful diagnostic tool. These measures can be obtained with a simple MRI and could be combined with other biomarkers to improve the diagnosis of patients with PSP or CBD.

More work needs to be done to ensure the translation of our method to clinical practice and we are now working to validate our results in other large multicenter studies.


The MRPI is calculated as follows: (area of pons on mid-sagittal section / area of midbrain on midsagittal section) X (diameter of middle cerebellar peduncle on parasagittal section / diameter of superior cerebellar peduncle on coronal section). 

The MRPI 2.0 multiplies the MRPI by the (maximum width of the third ventricle / maximum width of the frontal horns of the lateral ventricles).

Skin is now in the game

Researchers led by Dr. Elena Vacchi of Lugano, Switzerland report new data on the utility of skin biopsies in the diagnosis of PSP and CBS.  This diagnostic approach is further along for Parkinson’s, where the fibers of alpha-synuclein are not difficult to detect in the tiny nerves in skin. The same technique, but for tau, has not been particularly successful for PSP so far, but these researchers did more sophisticated molecular tests. 

They recruited 11 patients with PSP and 4 with CBS, along with 31 with PD, 14 with MSA and 24 healthy controls.  They obtained two cylindrical plugs of skin 3 mm in diameter from the back of the neck and another two from just above one ankle.  They measured the amount of normal and abnormal tau protein and the forms of RNA encoding the most common abnormal tau forms found in PSP and CBD (the 2N4R isoform). 

Comparing the group with PSP or CBS with the group with PD, there was a 90% sensitivity (i.e., the fraction of the patients with PSP or CBS whose biopsy showed an excess of abnormal tau) but only 69% specificity (the fraction of those without PSP or CBS with a normal result) and 0.812 AUC (see the note below).  For the comparison of PSP/CBS versus MSA, the results were better: 90% sensitivity, 86% specificity and 0.900 AUC.  I assume that that’s because of PD’s known tendency to have a little tau aggregation along with its alpha-synuclein, while that happens little in MSA.  For some reason the comparison of PSP/CBS with healthy controls was only moderate, with an AUC of 0.774.  The neck skin proved more informative than the ankle skin. 

The authors point out that their patients’ diagnoses were not autopsy-confirmed.  One solution might be to obtain the skin samples from deceased patients undergoing brain autopsy.  They also point out that the pattern of excessive phosphorylation of tau, which is known to be critical to disease causation, was not considered at all in their otherwise-thorough lab procedures.  So that might improve their results.

An interesting upshot is the authors’ observation that in PD and MSA, there was a reduction of nerve fibers in the skin, while this did not occur in PSP/CBS.  Together with evidence from many other sources, this suggests to them that in PD and MSA, the disease starts in the peripheral tissue (i.e., in non-brain organs such as the skin) and spreads to the brain, while in PSP and CBD, the problem starts in the brain and spreads outwards.

Note: Per Wikipedia, “A receiver operating characteristic curve, or ROC curve, is a graphical plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied.”  In other words, how well does a simple positive/negative diagnostic test do in distinguishing true positives from true negatives?  This allows you to optimize the definition of “positive” and “negative” test.  The curve’s vertical axis is the sensitivity or the true positive rate (0 to 1.0) and the horizontal axis is 1 minus specificity or the false positive rate.  The area under that curve (AUC) has a theoretical maximum of 1.0.  Excellent diagnostic tests have an AUC of 0.90 or more, and moderate tests, 0.80 to 0.89.  A coin flip’s AUC is 0.50.