Author Archives: Dr. L. Golbe

Good old MRI comes through

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We still don’t have a great diagnostic test for PSP.  The best we can do is about 80%-90% sensitivity, specificity and positive predictive value.  In English:

  • Sensitivity is the fraction of people with PSP who give a positive result on the test.
  • Specificity is the fraction of people without PSP who give a negative result on the test.
  • Positive predictive value is the fraction of people with a positive test who actually have PSP.
  • A single number combining these into something useful in evaluating a single individual — rather than in comparing groups — is the “area under the receiver operating curve” (AUC; see this post for an explanation).  The AUC ranges from 0.50, which is no better than a coin toss, to 1.00, which is perfect accuracy.  An acceptable diagnostic test typically has an AUC of at least 0.85.

Most of the studies of PSP diagnostic markers have important weaknesses such as:

  • The studies frequently set up artificial situations such as distinguishing PSP only from PD or normal aging rather than from the long list of other possibilities that must be considered in the real world.  
  • The patients’ “true diagnoses” are usually defined by history and examination alone rather than by autopsy.
  • The patients included in the study were already known to have PSP by history and exam (or sometimes by autopsy), while the purpose of the marker would be to identify PSP in its much earlier, equivocal stages or in borderline or atypical cases.
  • The patients with PSP in most such studies are only those with PSP-Richardson’s syndrome, who account for only about half of all PSP in the real world.

The best type of marker so far is ordinary MRI.  Recently, a group of neurologists in Athens, Greece led by first author Dr. Vasilios C. Constantinides and senior author Dr. Leonidas Stefanis evaluated the specificity of various MRI-based measurements of brain atrophy.  One strength of their study was that their 441 subjects included people not only with PSP and Parkinson’s disease, but also with a long list of other conditions with which PSP is sometimes confused as well as a group of healthy age-matched controls. 

The single best MRI marker per this study was the area of the midbrain, the fat, V-shaped structure indicated below:

They found that MRI markers provided:

  • High diagnostic value (AUC >0.950 and/or sensitivity and specificity ∼90 %) to distinguish PSP from multiple system atrophy, Parkinson’s disease, and control groups.
  • Intermediate diagnostic value (AUC 0.900 to 0.950 and/or sensitivity and specificity 80 % to 90 %) to distinguish PSP from Alzheimer’s disease, frontotemporal dementia, dementia with Lewy bodies, and mild cognitive impairment (an early stage usually of AD).  
  • Insufficient diagnostic value (AUC < 0.900 or sensitivity/specificity ∼80 %) to distinguish PSP from corticobasal degeneration, normal-pressure hydrocephalus, and primary progressive aphasia (a language abnormality that can be caused by multiple specific diseases).
  • Insufficient value to distinguish the non-Richardson PSP subtypes from corticobasal degeneration and primary progressive aphasia, but good performance in the other comparators.

The researchers also concluded that:

  • One MRI measurement isn’t best for all the possible PSP comparators. 
  • Sometimes a combination of two or three measurements performed better than any single measurement.

One weakness of their method was the use of subjects diagnosed by standard history/exam (i.e., “clinical”) criteria, rather than by autopsy. Another is that their patients with PSP had had symptoms for an average of three years, so these were not subtle or early-stage cases. A letter to the journal’s editor from Dr. Bing Chen of Qingdao City, China further pointed out that the study of Constantinides and colleagues failed to account for the subtle effects of neurological medications on brain atrophy.  As PSP and the comparator disorders may be treated with different sets of drugs, taking this factor into account might enhance or reduce the apparent diagnostic value of MRI atrophy measurements.  

So, bottom line?  Drs. Constantinides and colleagues have given us the first study of MRI markers in PSP to include meaningful numbers of subjects with non-Richardson subtypes.  It’s also one of the few studies of any kind of PSP marker to include comparison of PSP a wide range of diagnostic “competitors” beyond just Parkinson’s and healthy aged persons.  Another plus is that the test, routine MRI, is nearly universally available, relatively inexpensive, and non-invasive.

The hope is that Pharma companies or others with candidate drugs will now have fewer or lower hurdles in the way of initiating clinical trials.

A curable zebra

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In medical school, we were taught, “If you hear hoofbeats, consider horses, not zebras.”  While it’s true that more common diseases are more likely in a given situation, occasionally rare things do occur.  A great example is Wilson’s disease, because it’s a “zebra” that’s highly treatable, and failure to diagnose and treat it could be devastating.

Wilson’s is quite rare — a bit less than half as common as PSP.  It usually starts during late childhood, but occasionally does so as late as age 55.  It’s caused by a mutation in a gene related to the metabolism of copper, which accumulates in parts of the brain and in the liver to toxic effect.  It causes a long and variable list of neurological symptoms and can occasionally mimic PSP to a degree.  That’s why our 2024 review called “A General Neurologist’s Practical Diagnostic Algorithm for Atypical Parkinsonian Disorders” included Wilson’s among the 64 conditions (most of them zebras) to be considered in such situations.

Untreated Wilson’s disease typically leads to death from liver failure within a few years of diagnosis.  But drugs that remove copper from the body or that address the problem in other ways are extremely effective and if started soon enough, can confer a normal lifespan with little or no disability.  Furthermore, Wilson’s is easy to test for. 

I was reminded of this by a case report appearing today in the Annals of the Indian Academy of Neurology authored by Drs. J. Saibaba, S. Gomathy, R. Sugumaran and S Narayan.  Their patient’s symptoms started at age 51 with unprovoked backward falls followed by general slowing, slurred speech, tremor, weight loss, and depressed mood. (Any of that sound familiar?)  His exam showed, among other things, impairment of downgaze, limb rigidity, and loss of balance.  He also showed two strong clues for Wilson’s disease: a coppery-brownish ring at the edge of his corneas called a “Kaiser-Fleischer ring” and an unusual tremor of the arms called a “wing-beating tremor.”

Most neurologists test for Wilson’s in anyone with any movement disorder starting before age 55 without other obvious cause.  The testing consists of a check for K-F rings, which may require a “slit lamp” exam by an ophthalmologist; a blood test for a protein called “ceruloplasmin;” and a 24-hour urine collection to check its copper content.  If those are inconclusive, then a liver biopsy and/or a genetic test can be performed.

The important take-home is that if what looks like PSP starts before age 55, especially if accompanied by liver disease, Wilson’s disease should be tested for.  The result could be life-saving.

PSP and power

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As I occasionally do, I’ve selected a particularly pertinent and/or complicated reader comment to respond to as a self-contained post.  “Mayod” has commented on my post, “Orphans, this could be your chance,” which touched on the statistical issues relevant to including the nine non-Richardson PSP subtypes in clinical trials.   The comment essentially ask for clarification of terms as I and other medical writers use them, especially the term, “statistical power.”

Hi “Mayod”:

First, for the benefit of my other readers, I’ll point out that you are a very prominent academic expert on the philosophy and theory of statistics.  That’s pretty scary, so I’ll avoid trying to match that level of sophistication and simply reply to your question at a level comprehensible to most intelligent people who have never formally studied statistics.  (Full disclosure: I’ve never had a statistics course myself.  I’ve just picked stuff up along the way.)

In the context of a drug trial, the “power” is the ability to exclude the null hypothesis.  The null hypothesis, which we all hope will be disproved by the trial, posits that the drug works no better than placebo. At a more technical level, the study’s power is 1-β, where β is the false negative rate, or the likelihood of failing to identify a true benefit of the active drug relative to placebo.  It’s also called “Type II error.” Typically, β is set at 20%, sometimes 10%.  That would make the power 80% or 90%.     

Another component of a trial’s power is the α, which is the greatest tolerable likelihood of falsely rejecting the null hypothesis, which is concluding that the drug works better than placebo when it really doesn’t.  It’s also called the false positive rate, or Type I error and is typically set at 5%, sometimes 1%.  As a drug trial designer you have to balance the α and the β, meaning that you don’t want to make the false negatives so low that you risk elevating the false positives, and you don’t want to make the false positives so low that you risk elevating the false negatives.

The other number required to determine the trial’s power is the “effect size.”  In a PSP trial, that’s the detectable reduction detectable in the average rate of worsening over the duration of the trial for the active drug group relative that in the placebo group.  For PSP, the effect size is typically set somewhere between 20% and 40%, though we’d all like it to turn out to be much higher than that.  As an example, let’s say the placebo group and active group each start the trial with an average PSP Rating Scale score of 30.  At the end of the trial, the placebo groups has progressed to an average of 40, while the active drug group has progressed to an average of 37.  That’s a difference of 10 points vs 7 points, or a 30% slowing of progression (a 30% effect size).

As a brief aside: The previous paragraph’s use of the word “average,” usually means “mean” for drug trials, but there’s now a movement toward comparing not the two groups’ means, but the frequency among each group of having worsened by a pre-determined amount over the trial period.  Those two frequencies and their confidence intervals are then compared.   That “given amount” is the motivation behind using the “minimal clinically important difference” for that specific medical condition.  The confidence interval is the span of possible results in which 95% (typically; occasionally 90%) of each group’s frequency occurs.  (Nerd alert: The “95%CI” measures the variability of a frequency, just as the standard deviation measures the variability of a mean.)

Getting back to maximizing a study’s power: One way to do that is to choose an outcome measure with as little random “noise” as possible.  Such noise could arise from ambiguous wording in the scoring definitions, poor rater training, inclusion of medically irrelevant items in the scoring, poor fidelity between rating definitions and the true natural history of the disease, and many other factors. 

But another good way to reduce random noise in the results is simply to increase the number of patients in the study.  That’s why the medical literature often expresses the “power” of a clinical trial as the number of patients (the “N”) required to minimize the noise to the point where both the α and the β are acceptable.  Obviously, the lower the N, the greater the power. 

“Mayod,” I hope that answers your question, and as for the rest of you, thanks for powering through this far.

Orphans, this could be your chance

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Back in 2023, I posted an explanation of the ten PSP subtypes.  The archetypal subtype, PSP-Richardson syndrome accounts for about half of all PSP and, in contrast to most of the other subtypes, has a rapid progression rate, a validated rating scale, and highly accurate diagnostic criteria.  All of these features have led clinical trial sponsors to maximize their trials’ sensitivity and minimize their costs by restricting admission to people with PSP-Richardson.  But developing better outcome measures for non-Richardson forms of PSP could change that practice.

A big step toward realizing this goal was published last week in the journal Neurology by a group at the Mayo Clinic in Rochester, MN.  Led by first author Dr. Mahesh Kumar and senior authors Drs. Jennifer Whitwell and Keith Josephs, the study found that a good outcome measure for clinical neuroprotection trials in all PSP subtypes was to combine a measure of atrophy by MRI with a measure of clinical disability.  This is a major advance.

The researchers performed brain MRIs at the start and end of a one-year period in 88 people with PSP and 32 age-matched controls.  Of those with PSP, 50 had PSP-Richardson, 18 had “PSP-cortical” (three of the other nine subtypes) and 20 had “PSP-subcortical” (the other 6 of the subtypes).  They had to lump the non-Richardson subjects using their subtypes’ general anatomical predilections because most of the subtypes were too rare to analyze on their own.

Calculating how much each of ten important PSP-involved brain regions had atrophied over the one-year interval allowed the researchers to identify which region(s) might best serve as markers of progression for each of the three groups when coupled with standard clinical measures.  Those measures include such familiar instruments as the PSP Rating Scale and the Unified Parkinson’s Disability Rating Scale’s motor section as well as less familiar scales specific for cognition, gait, eye movement and speech.  All the scales were administered concurrently with each of the two MRIs. 

They expressed the sensitivity to one-year progression not by some abstract statistic, but by the number of patients needed in a double-blind trial to demonstrate with at least 80% certainty that patients on active drug enjoyed a 20% slowing of progression relative to the placebo group. (These specifications are typical for PSP clinical trials.)  The better the measure’s performance, the fewer patients are needed.

And the award for Best Performance by an Outcome Measure in a PSP Neuroprotection Trial goes to . . . a combination of the rate of atrophy of whatever brain region shrinks fastest in the patient’s specific subtype and the PSP Rating Scale score.

The real significance of this study’s result is that using an outcome measure customized to each participant’s PSP subtype could allow trials to enroll not just people with PSP-Richardson, but also those with any of the other subtypes.  That’s because the trial’s measure of success could be to compare each patient’s rate of progression during the trial to that of patients in the placebo group with the same PSP subtype. 

This could double the number of people eligible to enroll in PSP trials, which means cutting the enrollment period in half, with commensurate reduction in costs for the sponsor.  The hybrid measure is more sensitive to progression than the PSP Rating Scale alone, thereby reducing the number of patients required even more. 

Both factors could lower the financial barrier confronting a company hoping to mount a trial for a promising PSP drug.  That may be the most important bottleneck right now in the development of a treatment to prevent or slow the progression of PSP.s

That’s why this news is huge for PSP in general and for the “orphans” in particular.

My fingers in PSP pies

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If, like me, you like hearing about ideas in progress, here are the PSP-related projects at various points in my own pipeline right now:

  • I’ve written a long paper with statistician Ronald Thomas, PhD on clinical trial design issues in PSP that has been accepted for publication.  It’s a review of previously published work but includes our original calculation of a “minimal clinically important difference (MCID)” for PSP.
  • What’s an MCID?  It’s the smallest quantity of improvement that perceptibly changes a person’s quality of life.  This can be measured in multiple ways and how to do that in PSP is the topic of another project in which I’m collaborating.  Its leader is Anne-Marie Wills, MD of Massachusetts General Hospital and the Parkinson Study Group’s Atypical Parkinsonism Working Group.
  • I’m a sort of senior advisor – not really a collaborator – in a project led by Deepak Gupta, MD of the University of Vermont to create AI-assisted diagnostic software for the major Parkinsonian disorders, including PSP.  It’s based on the current, validated, published criteria, but is a lot easier to use.  It does require skill in the neurological exam, so it’s not for home use.  I hope it will soon be submitted for publication.
  • CurePSP has undertaken a project to determine the impact of PSP, CBS, and MSA on a family’s finances.  I’m working with a young staffer, Saira Mehra, on sending a detailed questionnaire to as many people with those disorders as we can.  We now have enough responses to start the statistical analysis.
  • I’m a moderately minor collaborator in a review of swallowing abnormalities in PSP, CBD and MSA.  It’s another project of the same working group and its primary author is Federico Rodriguez-Porcel, MD of the University of South Carolina.  It’s been submitted, so fingers are crossed.
  • I’m a more minor collaborator in another review, this one of imaging and fluid biomarkers in PSP, CBD and MSA.  Its primary author is Guillaume Lamotte, MD of the University of Utah.  All of the authors are affiliated with the Diagnosis and Treatment Working Group of CurePSP’s Centers of Care network.  It’s almost ready to submit for publication.
  • I’m an even more minor collaborator in an analysis of causal risk factors in PSP using medical records from 240 patients registered with the UK Biobank.  It’s been submitted and its primary author is Charlie Weige Zhao, MD of Mass General.  There were a couple of interesting findings, but I can’t discuss them until the paper is accepted (or maybe until it’s published, depending on the journal’s rules).
  • I’m advising several drug companies on how to design their PSP trials and to implement the PSP Rating Scale as the primary outcome measure. (I created the PSPRS in the mid-1990s and published it in 2007 along with statistician Pam Ohman-Strickland, PhD, of Rutgers.)

Five years ago, when I told my wife I was retiring, she actually believed me just because the paychecks stopped.

Artificial intelligence and artificial CSF drainage

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A common diagnostic problem is distinguishing PSP from normal-pressure hydrocephalus (NPH), but a new way to look at brain MRIs using artificial intelligence could have the solution.  I’ll now administer the usual large dose of background information:

NPH occurs in the same age group as PSP but is much more common.  Its three classic features sound a lot like PSP: frontal cognitive loss, urinary incontinence, and gait impairment.  But those often don’t appear until late in the course and other issues such as general slowness, reduced vertical eye movement and tremor can precede them.  Of course, those also are shared with PSP.

In NPH, the fluid-filled cavities of the brain enlarge and over-stretch the brain’s fibers to produce the symptoms.  The cause of the cerebrospinal fluid (CSF) accumulation in many cases is a partial blockage of its normal absorption into the blood.  In some cases, that appears to be the result of scarring from an old episode of brain infection or bleeding around the brain.  Other cases, called “idiopathic NPH,” have no history of such inflammatory events and their cause remains unknown.  There is also in NPH some evidence of a neurodegenerative component, as in PSP, Parkinson’s, and Alzheimer’s.

A diagnosis of NPH depends less on the clinical history and exam than on two other things: 1) a specific pattern on MRI of brain tissue loss and enlarged CSF spaces and 2) benefit after removal of some CSF.  I’ll discuss those in turn:

A. MRI diagnosis. Below are MRI images from idiopathic NPH (middle row) and PSP (bottom row).  The main differences between PSP and NPH are indicated by the labels on the right.  PSP features widening of the spaces between the brain’s folds caused by atrophy of the brain tissue.  But in NPH, the spaces toward the top of the brain are as tight as, or tighter than, normal.  There are other, less reliable, MRI differences, none of them adequately sensitive or specific for NPH.

B. CSF diagnosis. The other diagnostic feature is the response to CSF drainage.  It’s not just a diagnostic test; it also predicts the likely response to treatment by shunting.  If someone in whom NPH is suspected has an MRI consistent with NPH and no signs of other potential causes of their symptoms, the physician will usually perform a spinal tap to remove about 30-50 ml with before-and-after videos of the gait and other actions. (The average adult has about 100-150 ml at any one time, but the daily turnover is about 500 cc, so the 30-50 ml loss is replaced after only a few hours.)  Some neurologists prefer the greater diagnostic reliability provided by a more prolonged period of drainage via a soft plastic tube temporarily inserted into the lumbar CSF space (the same place where the needle of a spinal tap goes), but this can have complications.

Whichever temporary method of CSF removal is used, a good symptomatic response would prompt consideration of a tube, called a “shunt,” permanently implanted into the brain to direct flow of some CSF, usually into the abdominal cavity.  Of course, implanting such a shunt into the brain can produce complications such as infection or bleeding, so we’d first like to make sure the person doesn’t have PSP, which offers no potential shunt benefit to compensate for that risk.

I should point out that PSP is far from the only disease that can mimic NPH and not respond to shunting.  Among the others are the far more common PD and AD.  That means that only a small minority of “NPH candidates” actually has NPH, so placing brain shunts in all the candidates would be highly inadvisable, to put it mildly. So, it’s important to make the right diagnosis.

Over the decades since 1965, when NPH was first described in the literature, the number of proposed diagnostic methods has been prodigious and none has been sufficiently accurate.  But now, the cavalry may have arrived in the form of AI.  A group of researchers led by Drs. Fubuki Sawa and Syoji Kobashi of the University of Hyongo in Japan has used “convolutional neural networks,” a form of deep learning, to produce a predictive model. It used the most specific and informative MRI features from 59 people with NPH who subsequently benefitted from shunting and 65 people with PSP by current, validated criteria.  The resulting statistical formula produced a perfect score of 1.000 in the area under the curve (AUC) of the receiver operating characteristic (ROC). (Wikipedia has a nice little explanation of that statistic here.  Basically, it’s the ability of a diagnostic test to minimize both false positives and false negatives, with 1.0 being perfect and 0.5 being equivalent to a coin toss. Its virtue is that it’s applied to an individual, not merely to the averages of two groups.) 

Perhaps easier to intuit is the test’s accuracy, according to Sawa et al, of 0.983.  That statistic is formally defined as the fraction of all the participants who received a correct diagnosis from the formula. Such power for a diagnostic test is nearly unheard-of in medicine, but keep in mind that the definition of NPH in this study wasn’t autopsy, but an MRI showing the typical features plus a response to CSF shunting.  So that means that the input and outcome variables were partly redundant, inflating the accuracy to some extent.

The other caveat is that this technique only distinguished PSP from NPH, not from PD or anything else.  But the general AI-based statistical technique should be applicable to many kinds of diagnostic situations where the two candidate diseases cause atrophy in different parts of the brain.  We eagerly await those papers from Drs. Sawa and Kobashi, and we hope, others.

The take-home if you’re someone with PSP:

  1. Should people with a diagnosis of PSP get a new MRI each year in the hope that a pattern of NPH will emerge and a shunt procedure confer improvement?  Probably not, because an MRI showing the abnormalities of PSP won’t change into the abnormalities of NPH over time.   
  2. Should people with PSP get a shunting procedure just in case they actually have NPH?  Definitely not, as the risk of both short- and long-term shunt complications far exceeds the likelihood of benefit.
  3. Instead of either of these: Keep hydrated and well-nourished, avoid falls and aspiration, minimize unnecessary medications with your doctor’s advice and consent, get some exercise, maintain a social life, and join an FDA-approved clinical trial if one is available.
  4. Also, consider getting a second diagnostic opinion from a neurologist subspecializing in movement disorders, who can scrutinize the original MRI for evidence of NPH that might have eluded the original neurologist or radiologist.

    The take-home if you’re a neurologist:

    At each follow-up visit or phone call, keep in mind the possibility that the diagnosis may not actually be PSP, but something much more treatable — like NPH. Then, work up or refer accordingly.

    The cutting edge (part 1 of 2)

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    Here’s the first of two installments summarizing the original, PSP-related research presentations at the annual conference of the International Parkinson and Movement Disorder Society held in early October 2025 in Honolulu. 

    The listing is in no particular order and each is followed by my own editorial opinion.  I’ve culled the 29 PSP-related presentations down to the twelve I considered most interesting considering both their scientific importance and their potential interest to this blog’s readers. 

    —

    Clinical Deficits, Quality of Life and Caregiver Burden across PSP Phenotypes

    A. Cámara, I. Zaro, C. Painous, Y. Compta (Barcelona, Spain)

    Caregiver burden is greater for PSP-Richardson syndrome than for other PSP subtypes, and quality of life showed a statistically non-significant trend for PSP-RS as well.  This information may be useful in counseling patients and caregivers.

    LG comment: This result would be expected given the rapid progression of PSP-RS and its high prevalence of falls and dementia relative to most other PSP subtypes.  The study importantly points out that caregiver burden receives too little attention from clinicians, researchers, policy planners and insurors.

    Clinical Features Suggestive of Alpha-Synucleinopathy in Progressive Supranuclear Palsy

    C. Painous, A. Martínez-Reyes, J. Santamaria, M. Fernández, A. Cámara, Y. Compta (Barcelona, Spain)

    Rapid eye movement behavioral disorder and reduced ability to smell are known to be very common in Parkinson’s disease and other alpha-synuclein-aggregating disorders but also occur to some extent in those with PSP.  All of this study’s patients with PD and 10% if those with clinically typical PSP had a positive spinal fluid alpha-synuclein seeding amplification assay (SAA).

    LG comment: The new SAA test is not perfectly specific for synucleinopathies and could produce a false positives in people with PSP.  The same is true for RBD and reduced smell sensitivity.

    Identification of Genetic Variants in Progressive Supranuclear Palsy in China

    Y. Kang, W. Luo (Hangzhou, China)

    Pathogenic or likely pathogenic variants consistent with their respective inheritance patterns were detected in 20% (8/40) of patients: three carried PSP-related variants (CCNF, DCTN1, POLG), while five harbored variants in neurodegeneration genes linked to PSP-like phenotypes (AARS1, TDP1, FA2H, TBP, ATXN8).  The controls were only historical controls from the literature.

    LG comment: This list of genetic variants, each conferring a very slight increased PSP risk, differs from the lists reported in Western populations, which also have important differences from one another.  The differences could be related to geographically or culturally related environmental contributions (which need different genetic backgrounds to cause damage) or to differences in laboratory methods or choice of non-PSP control populations.

    Unraveling the Genetic Architecture of Progressive Supranuclear Palsy in East Asians

    P. Chen, R. Lin, N. Lee, J. Hsu, C. Tai, R. Wu, H. Chiang, Y. Wu, C. Lu, H. Chang, T. Lee, Y. Chang, C. Lin (Taipei, Taiwan)

    Using a Taiwanese population, this study identified three likely pathogenic variants, in the genes called APP and ABCA7, and the mitochondrial genome.  It also found 39 variants of unknown significance in 37 PSP patients (20.9%), involving  other genes, many of which were already known to confer slight risk for PSP.   

    LG comment: The difference in apparent genetic risk factors between Shanghai (previous abstract by Kang et al) and Taiwan underscores the possibility of differences in methodology, although ethnic differences between those two geographical areas could be contributing.  Genetic study of PSP in East Asians could benefit all ethnicities by identifying previously unsuspected cellular pathways involved in the disease.

    Multimodal imaging Integrating 18F-APN-1607 and 18F-FP-DTBZ PET in Progressive Supranuclear Palsy

    C. Dong, J. Ma, S. Liu (Beijing, China)

    Several kinds of positron emission tomography (PET) imaging are being tested for their ability to accurately diagnose PSP.  Two of them were applied concurrently to a group of 20 participants with PSP and a control group.  One, called 18F-APN-1607, shows abnormal accumulation of the tau protein and the other, called 18F-FP-DTBZ, images the neurons that use dopamine.  The result was that 16 of the 20 were correctly identified by the 18F-APN-1607 and three of the other four were identified by the 18F-FP-DTBZ as being probable Parkinson’s disease.  The conclusion is that performing both types of PET could provide more accuracy than the tau PET alone in distinguishing PSP from PD.

    LG comment: This result is consistent with the age-old medical principle that there’s no such thing as a perfectly accurate diagnostic test.  Two or more tests measuring different aspects of the same disease can work in a complementary manner to improve diagnostic accuracy.  Fortunately, PET is a nearly harmless, nearly painless test.  Its main drawbacks are time, expense and insufficient availability of many kinds of PET outside of referral centers.

    Levodopa response in pathology-confirmed Parkinson’s Disease, Multiple System Atrophy and Progressive Supranuclear Palsy

    V. Arca, J. Jurkeviciene, S. Wrigley, P. Cullinane, J. Parmera, Z. Jaunmuktane, T. Warner, E. de Pablo-Fernandez (London, United Kingdom)

    About one in three people with PSP experiences some degree of benefit on levodopa, a statistic that prompts most neurologists to give that drug a try.  However, the benefit is often short-lived.  To measure this in a formal way, these researchers reviewed the medical records of autopsy-confirmed patients with PSP, PD or MSA.  Those responding well for over two years were 2% of those with PSP, 86% of those with PD and 8% of those with MSA.

    LG comment: The short duration of useful benefit from levodopa in PSP means that each patient enjoying a benefit after the drug initiation should be re-evaluated at each subsequent visit for a continued benefit.  As levodopa can have long-term side effects such as low blood pressure, hallucinations and involuntary movements, a dosage taper carefully monitored by the physician should be considered after the first year or so of treatment.

    “A little duloxetine to loosen my tongue”

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    The drug duloxetine, marketed under the brand name Cymbalta, was originally developed for depression or anxiety but is now prescribed mostly for pain management.  An article from neurologists in Russia and Malaysia now reports that three people with PSP who were receiving duloxetine for their mood issues experienced important, unexpected improvement in their speech. 

    The article’s first author is Dr. Oybek Turgunkhujaev of the Semeynaya Clinic in Moscow and its senior author is Dr. Shen-Yang Lin of Universiti Malaya in Kuala Lumpur.  Unfortunately, the journal, Movement Disorders Clinical Practice, is not open-access and because it’s only a brief article, there is no abstract in PubMed for me to link to.

    The mechanism of action duloxetine is to enhance the action of the neurotransmitters serotonin and norepinephrine by blocking the brain cell’s ability to re-absorb those molecules from the synapse.  That’s a standard way for brain neurons to regulate and sharpen its signals to other neurons.  That process is called “reuptake” and you’ve probably heard of the SSRIs or selective serotonin reuptake inhibitors. Duloxetine works on norepinephrine as well as serotonin, so it’s an SNRI.   Other SNRIs in common use include venlafaxine (Effexor) and desvenlafaxine (Pristiq). The figure below shows the mechanism of action of duloxetine and venlafaxine. 

    Nerd alert: This mostly takes place in the pons, specifically the locus ceruleus (for norepinephrine), raphe nuclei (for serotonin), but to a lesser extent in prefrontal cortex of the cerebrum (both norepinephrine and serotonin).

    The journal article is accompanied by before-and-after videos of two of the three patients.  They all had difficulties not only with slurring, but also with difficulties initiating speech and stuttering.  The delay to onset of the drug’s benefit is described only as “within weeks.”  All three patients also experienced an improvement in their mood, which could have been a direct effect of the drug on the natural reaction to their improved ability to speak.

    The authors do a good job of describing how the drug’s known mechanism of action might address the parts of the brain that when impaired, are known to cause those symptoms.  But they also recognize that the general alerting and energizing effect of duloxetine could explain the result as well.  Placebo effect seems unlikely, as the durations of benefit were too long: “> 3 months,” “15 months until death” and “>5 months.” 

    Bottom line: This is encouraging and I hope further reports of duloxetine in PSP from other centers are forthcoming. BUT . . . and MEANWHILE . . .

    Physicians considering prescribing duloxetine off-label for speech problems in PSP should be aware that it can have important side effects and drug/dietary interactions.  I can’t get into those here, but they are described in detail in the 31-page FDA-approved package insert and its one-page summary. Needless to say, there has been no formal trial of duloxetine in PSP, so that population could have different/additional/worse side effects relative to the mostly younger people in the depression and pain trials on which the package insert was based. 

    Posts from an outpost

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    A colleague and co-author of mine, Michiko Kimura Bruno, MD, has started a blog that might interest you. Its platform is the Psychology Today site and its very cool overall topic is neurological disorders from the psychological standpoint. Dr. Bruno alerted me to this because the third post is about PSP.

    Dr. Bruno is an academic movement disorders specialist, like me, but in Hawaii, not New Jersey. (No jokes, please.) She works at The Queen’s Medical Center, which is affiliated with the John A. Burns School of Medicine at The University of Hawai’i at Mānoa, where she is Professor of Neurology. She directs CurePSP’s Center of Care at her institution. To date, Dr. Bruno is author or co-author of eight peer-reviewed papers on PSP, five of which are about its social or psychological aspects. Take a look.

    Michiko K. Bruno, MD

    PSP meets metaphenomic annotation

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    Back in the 19th Century, diagnosing brain disorders relied mostly on listening carefully to the patient’s history, performing a detailed neurological examination, and knowing what previous, similar patients turned out to have at autopsy.  That approach remains important, but since the early 20th Century, chemical, electrical and imaging tests have replaced it to a great extent.  But now, neurologists at one of the world’s most prestigious medical centers, the Queen Square Institute of Neurology at University College London, have turned back the clock.

    The researchers were motivated by the failure to date of modern techniques short of autopsy to provide a sufficient level of diagnostic certainty for the atypical Parkinsonian disorders.  So, they squeezed some more value out of the traditional approach.  First, they reviewed 125 publications since 1992 describing a total of 5,748 people with Parkinsonian disorders of various types and a diagnostic answer at autopsy.  Those proven diagnoses were Parkinson’s disease (30%), PSP (23.5%) multiple system atrophy (16.8%), dementia with Lewy bodies (6.0%), corticobasal degeneration (4.6%).  There was also a large group called “others” (19.6%), who mostly had Alzheimer’s disease, which in its advanced stages can acquire stiffness and slowness and look “Parkinsonian.”  Keep in mind that the sources of these numbers were specialized academic referral centers, where the atypical Parkinsonian disorders would be over-represented.

    Led by first author Dr. Quin Massey and senior author Dr. Christian Lambert, the researchers invented a new statistical technique called “metaphenomic annotation,” which involved feeding the 125 journal articles into commercially available text-mining software to tabulate the patient’s lists of symptoms against the autopsy results.

    Etymology lesson of the day: “Meta” means “beyond,” in this case beyond the confines of a single published study.  “Pheno” means “outward appearance,” in this case the features of the disease during life.  “Phenomics” means a large collection of such features, analogous to “genomics” as a large collection of genes. “Annotation” in this case means somehow managing to shoehorn all that data from disparate sources into a usable database.

    They found that among the 1,195 people with PSP diagnosed during life, the autopsy diagnosis was PSP in 89.5%, PD in 3.0%, CBD in 2.5%, MSA in 1.3%, and “other” in 3.7%. Among the 1,349 people whose autopsy showed PSP, the diagnosis during life was PSP in 79.3%, PD in 8.5%, MSA in 5.6%, CBS in 3.6%, DLB in 0.2% and “other” in 2.7%.  The graph below shows the corresponding numbers for all five conditions and the “others” group. The curving bands show how the diagnoses made during life (the “clinical cohort” on the left) were corrected by autopsy to the diagnoses (the “histological cohort” on the right).  (“Histology” is the study of body tissues through the microscope.)

    Figure and table from: Quin Massey, Leonidas Nihoyannopoulos, Peter Zeidman, Thomas Warne, Kailash Bhatia, Sonia Gandhi, Christian Lambert. Refining the diagnostic accuracy of Parkinsonian disorders using metaphenomic annotation of the clinicopathological literature. NPJ Parkinsons Disease 2025 Nov 10;11:314.

    If you think the figure above is information-rich but a bit confusing, the table below may be more of both.  Each of the five rows is labeled with a disease defined by autopsy, and each column represents how that disease compares with each of the other four with regard to diagnostic signs during life.  For example, for assistance in distinguishing PSP from MSA, look at the third row, second column, where square waves (an abnormal eye movement) are listed as being more common in PSP.  The number in parentheses is the ”positive likelihood ratio” for distinguishing PSP from MSA.  The PLR is calculated as (sensitivity / (1-specificity)) and can be informally described for this example as how much more likely is PSP than MSA to be the correct diagnosis, based on just this one diagnostic feature.

    This analysis can be very useful for the vast majority of neurologists and mid-level neurological professionals unfamiliar with the details of the differences among the atypical Parkinsonian disorders.  Even experienced movement disorders neurologists will find it useful to have all this information in one place and neatly quantified.

    A great part of this project is that the researchers have made the annotated data and their computer code publicly available for the use of other researchers.