L Barthelmes

A Goyal

R G Newcombe

F Mcneill

Robert E Mansel
email: manselre@cf.ac.uk

Adverse reactions to patent blue V dye -The NEW START and ALMANAC experience

Keywords: anaphylaxis, allergy, breast cancer, sentinel lymph node biopsy, patent blue V, isosulfan blue

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Abstract

Background

Blue dye with or without isotope has been widely used to identify the sentinel lymph node(s) in breast cancer. Patent blue V is used in the UK while its isomer isosulfan blue is used in the US. The allergic potential of isosulfan blue is well documented (1.4% adverse reactions) but that of patent blue V is less clearly defined.

Methods

In this paper we review the adverse reactions of patent blue V in 7,917 patients participating in the NEW START training programme and the ALMANAC trial. All patients underwent sentinel lymph node biopsy for breast carcinoma using patent blue V in combination with 99m Tc-albumin colloid.

Results

In total, 72 of 7,917 (0.9 %) patients experienced adverse reactions : non-allergic reactions were observed in 4 (0.05%) patients, 23 (0.3%) patients had minor grade I allergic skin reactions (urticaria, blue hives, pruritis, or generalised rash) and 16 (0.2%) had grade II reactions (transient hypotension/ bronchospasm /laryngospasm).

Severe Grade III reactions (severe hypotension requiring vasopressor support and/or and/or change / abandoning of planned procedure and/or HDU/ITU admission) were noted in 5 (0.06%). The type of adverse reaction was not specified in 24 (0.3%) patients. No mortality was recorded.

Conclusion

The allergic potential of patent blue V dye compares favourably with isosulfan blue however both surgeon and anaesthetist need to be alert to the risk of allergic reactions.

Introduction

Patent blue V dye has been used since the 1960's in lymphangiography. It is a 2,5 disulfonated calcium-chelated dimer of the triphenylmethane family (CAS number 3536-49-0). [START_REF] Scherer | Blue Dyes in Medicine--a Confusing Terminology[END_REF] Outside medicine it is used in textiles and as a food colourant (E 131) and potentially exposes the general population to the risk of allergic sensitisation. [START_REF] Kalimo | Sensitivity to Patent Blue Dye During Skin-Prick Testing and Lymphography. A Retrospective and Prospective Study[END_REF] With its use in sentinel lymph node biopsy there is a renewed interest in its medical role. We reviewed our experience of its allergic potential in the large number of patients in the NEW START training programme and the ALMANAC trial. In addition, we searched the ADROITE database of the Committee of Safety of Medicines and the pharmacovigilance files of the manufacturer (Laboratoire Guerbet, Aulnay-Sous-Bois, France) and compared the rate of adverse effects of patent blue V with other dyes, namely isosulfan and methylene blue.

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Patients and Methods

Before implementing sentinel lymph node biopsy (SLNB) for axillary nodal staging we investigated the procedure in a multicentre, randomised study (ALMANAC randomised controlled trial) [START_REF] Mansel | Randomized Multicenter Trial of Sentinel Node Biopsy Versus Standard Axillary Treatment in Operable Breast Cancer: the ALMANAC Trial[END_REF] preceded by a validation phase. We have now rolled out a UK -wide sentinel lymph node biopsy training programme (NEW START) in the UK to train breast teams and at the same time ensure patient safety.

Blue dye injection technique

In the ALMANAC validation phase and the ALMANAC randomised trial 2 ml of 2.5% aqueous solution of patent blue V diluted to 5 ml with normal saline was injected around the tumour. In the NEW START sentinel lymph node training programme undiluted 2 ml of 2.5 % patent blue V dye or 2 ml of 2.5 % aqueous solution of patent blue V diluted to 5 ml with normal saline was injected subdermally at the areola-skin margin of the index quadrant.

Adverse reactions

Side-effects after injection of patent blue V dye injection were recorded prospectively.

The participating surgeons described the specific reaction in a free-text box. Drug treatment of the reaction (histamine antagonist, steroids or vasopressor use), admission to intensive care unit or changes of procedure were recorded. The classification of blue dye allergic reactions described by Montgomery et al. [START_REF] Montgomery | Isosulfan Blue Dye Reactions During Sentinel Lymph Node Mapping for Breast Cancer[END_REF]

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Results

Adverse reactions

9 of 839 patients in the ALMANAC validation phase, 5 of 492 patients in the ALMANAC randomised trial, and 58 of 6586 patients in the NEW START training programme were noted to have an adverse reaction to patent blue V dye. In total, 72 of 7917 (0.9 %) patients experienced adverse reactions (Table 1).

23 patients experienced minor (grade I) allergic skin reactions. Grade II allergic reactions occurred in 16 patients. 5 patients experienced severe grade III allergic reactions (Table 2).

Non-allergic reactions were observed in 4 patients. The type of adverse reaction was not specified in 24 patients. Drug treatment for grade 1 and grade 2 reactions included administration of a histamine antagonist and/or hydrocortisone. 2 of 5 patients with grade 3 reaction were admitted to HDU/ITU for observation but recovered without any sequelae. In one patient who developed severe hypotension immediately after administration of patent blue V the procedure was abandoned. The planned operative procedure had to be changed in two patients with grade 3 reactions. All patients recovered from their reactions without any long-term morbidity. There was no mortality.

Committee of the Safety of Medicines -Yellow Card Scheme

We searched the database of the Committee of the Safety of Medicines (Yellow Card Scheme in UK) for adverse reactions following the use of patent blue V. Between

Isosulfan blue

Several American studies have addressed the issue of allergic reactions following injection of isosulfan, an isomer of patent blue V, for sentinel lymph node biopsy in breast and melanoma patients (Table 3). Adding all studies, 1.42 % (119 / 8372) of patients were noted to have allergic reactions after injection of isosulfan blue compared with 0.86 % (68 / 7917) of patients recruited in the NEW START and ALMANAC studies (Table 3) (difference 0.56%, 95% CI 0.24 to 0.89). Severe allergic reactions with hypotension requiring treatment with vasoactive drugs (grade III allergic reaction) were noted in 0.44 % (37 / 8372) of patients after injection of isosulfan compared with 0.06 % (5 / 7917) of patients who received patent blue V (Table 3) (difference 0.38 %, 95 % CI 0.23 to 0.55).

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Discussion

The combination of isotope and blue dye is the current recommended technique for sentinel node localisation in breast cancer in the UK with localisation rates of over 99%. However, blue dye is associated with a range of allergic reactions. There have been a number of case reports and single case series of anaphylactic reactions following administration of patent blue V. Its allergic potential is also reflected in reports to the Committee of Safety of Medicines and to the manufacturer. No mortality has been reported but two cardio-respiratory arrests have been attributed to patent blue V 5,6 . This is the first prospective analysis of anaphylactic reactions of patent blue V dye in a large cohort. The allergic risk of patent blue V compares favourably with the published US data on isosulfan blue.

Predicted incidence of blue dye reactions in UK

Severe potentially life threatening allergic reactions are rare but the total number of adverse reactions will rise with increasing use of sentinel lymph node biopsy in the UK. NICE (National Institute of Clinical Excellence, UK) 2009 guidelines recommend that axillary staging should be performed by sentinel lymph node biopsy using a combination of isotope and blue dye. 7 Breast cancer is the most common cancer affecting women in England and Wales, with about 44,000 new cases diagnosed each year. [START_REF]Cancer Incidence in Wales 1992-2002[END_REF][START_REF]Cancer Statistics Registrations: Registrations of Cancer Diagnosed in 2005[END_REF] Approximately 25,000 -30,000 of these patients with early stage breast cancer will undergo axillary staging by sentinel node biopsy. Based on the risk of reaction from the NEW START and ALMANAC dataset, 15 to 18 patients (0.06 %) may suffer severe grade 3 allergic reactions per annum.

It is not possible to accurately foresee anaphylaxis in a particular patient as severe allergic reactions to patent blue V have occurred in patients without any allergic

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predisposition. [START_REF] Wohrl | Near-Fatal Anaphylaxis to Patent Blue V[END_REF] Pre-operative antiallergic medication does not prevent anaphylactic reactions but can reduce severity. [START_REF] Raut | Incidence of Anaphylactoid Reactions to Isosulfan Blue Dye During Breast Carcinoma Lymphatic Mapping in Patients Treated With Preoperative Prophylaxis: Results of a Surgical Prospective Clinical Practice Protocol[END_REF]

Omitting patent blue V increases the false-negative rate

In an effort to minimise blue dye morbidity some centres are now performing isotope only localisation. We have some concerns with regards to this: in the ALMANAC validation phase in 10% of patients the sentinel lymph node stained with blue dye, but did not take up 99m Tc-albumin colloid. More importantly, in approximately 4% patients, the sentinel node that was involved with metastatic disease was identified by blue dye alone. [START_REF] Goyal | Factors Affecting Failed Localisation and False-Negative Rates of Sentinel Node Biopsy in Breast Cancer--Results of the ALMANAC Validation Phase[END_REF] An attractive option is to use blue dye selectively in the subgroup of patients in whom a hot node is not demonstrated on the lymphoscintiscan or cannot be detected with a gamma-probe. However, there is no published data on how this approach will influence the false-negative rate. NEW START dataset analyses will be able to answer this question, however till this is done all teams should use a combined technique (isotope and blue dye) for sentinel node localisation.

Methylene blue

Methylene blue dye due to its lower cost, lower allergic potential and lesser interference with pulse oximetry [START_REF] Aydogan | A Comparison of the Adverse Reactions Associated With Isosulfan Blue Versus Methylene Blue Dye in Sentinel Lymph Node Biopsy for Breast Cancer[END_REF][START_REF] Pinero | Effect on Oximetry of Dyes Used for Sentinel Lymph Node Biopsy[END_REF] has been used as an alternative. Sentinel lymph node detection rates with methylene blue are similar to isosulfan blue [START_REF] Golshan | Can Methylene Blue Only Be Used in Sentinel Lymph Node Biopsy for Breast Cancer?[END_REF][START_REF] Varghese | Methylene Blue Dye--a Safe and Effective Alternative for Sentinel Lymph Node Localization[END_REF][START_REF] Nour | Efficacy of Methylene Blue Dye in Localization of Sentinel Lymph Node in Breast Cancer Patients[END_REF][START_REF] Simmons | Methylene Blue Dye As an Alternative to Isosulfan Blue Dye for Sentinel Lymph Node Localization[END_REF][START_REF] Blessing | A Comparison of Methylene Blue and Lymphazurin in Breast Cancer Sentinel Node Mapping[END_REF] despite theoretical concerns about its poor lymphatic uptake due to its lack of sulfonic acid groups essential for binding to plasma proteins and absorption into lymphatics [START_REF] Tsopelas | Why Certain Dyes Are Useful for Localizing the Sentinel Lymph Node[END_REF] .

However, it is associated with fat necrosis [START_REF] Salhab | Skin and Fat Necrosis of the Breast Following Methylene Blue Dye Injection for Sentinel Node Biopsy in a Patient With Breast Cancer[END_REF][START_REF] Ruhlen | Tissue Necrosis. Cutaneous and Subcutaneous Damage Following Extravasation of Methylene Blue[END_REF][START_REF] Perry | Nectotic Subcutaneous Abscesses Following Injections of Methylene Blue[END_REF] and capsular contraction after implant surgery. [START_REF] Singh-Ranger | Capsular Contraction Following Immediate Reconstructive Surgery for Breast Cancer -An Association With Methylene Blue Dye[END_REF] While its allergic potential is less as reflected in fewer reports in the published literature and to the Committee of Safety of Medicines it is by no means non-existent. However, the presence of blue hives is diagnostic of reaction to the blue dye.

Practice guidelines

We recommend that allergic risk should be documented and discussed with patients undergoing sentinel lymph node biopsy when taking consent. Patent blue V should be avoided in patients with an allergy history to foods containing food colorant E 131 or hyperallergic patients carrying an adrenaline-containing syringe for selfadministration (epipen®). However, omitting blue dye may adversely affect the failed localisation and false-negative rates.

The surgeon should verbally alert the anaesthetist when patent blue V dye is administered. Since the use of patent blue V dye is on a named basis only and a licence is unlikely to be issued in future, we encourage reporting of adverse effects of patent blue V dye to the Committee of Safety of Medicines with the Yellow Card System in the UK.

Conclusion

The allergic potential of patent blue V dye compares favourably with isosulfan blue.

Severe anaphylaxis is rare. However, surgical and anaesthetic teams need to be alert to the risk of allergic reactions.

7. 1 .

 1 1974 to15.4.2008 there were 46 reports of 97 reactions, nearly half of them (44 / 97) due to anaphylactic immune system and skin disorders. There was one cardiorespiratory arrest, but no mortality.Pharmacovigilance files of the manufacturer revealed 86 cases (collated worldwide, including cases reported in literature) corresponding to 158 adverse events between 1/5/2002 to 30/4/2007. As 780,705 doses were sold during the period, the reporting frequency is estimated at 11 cases per 100,000 patients and 2 adverse events for 10,000 patients (personal communication Dr. Sophie Gaillard -Guerbet).

  was modified and used in this study. Allergic reactions were defined as grade I (urticaria,

	blue	hives,	pruritis	or	generalised	rash),	grade	II	(transient
	hypotension/bronchospasm/laryngospasm), grade III (severe hypotension requiring

vasopressor support and/or change/abandoning of planned procedure and/or HDU/ITU admission) and grade IV (cardiorespiratory arrest and/or death).

Table 1 . Adverse reactions to patent blue V dye

 1

	Study	Adverse reactions to	95% confidence
		patent blue V dye	interval
	NEW START	0.9 % (58/6586)	0.7% -1.1%
	(n=6586)
	ALMANAC	1.0 % (5/492)	0.4% -2.4%
	randomised phase
	(n=492)
	ALMANAC validation	1.1 % (9/839)	0.6% -2.0%
	phase
	(n=839)
	Total (n=7917)	0.9 % (72/7917)	0.7% -1.1%

Table 2 . Side-effects of patent blue V dye

 2

	Allergic reactions
	Grade I	urticaria, blue hives, pruritis, or generalised rash	23 patients
	Grade II	transient hypotension/ bronchospasm /laryngospasm	16 patients
	Grade III	severe hypotension (requiring vasopressor support)	5 patients
		and/or change / abandoning of planned procedure
		and/or HDU/ITU admission
	Grade IV	cardio-respiratory arrest and/or death	-
	Unspecified		24 patients
	Total allergic reactions	68
	Non-allergic reactions
	Skin tattooing	1 patient
	Bluish hue persisting for few hours	3 patients
	Total allergic +

non-allergic reactions

Acknowledgements

We thank all patients who participated in the NEW START training programme and ALMANAC trial; other study investigators; research fellows and all the surgery, nuclear medicine, radiological, radiographic, and nursing staff at each centre.

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Table 3. Allergic reactions to isosulfan blue compared to patent blue V dye

Conflict of interest

None.

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Rémi Gribonval
email: remi.gribonval@inria.fr

Morten Nielsen
email: mnielsen@math.auc.dk

Keywords: Nonlinear approximation, sparse decomposition, dictionary, Matching Pursuit, Basis Pursuit, linear programming, quadratic programming, coherence, spread, spark

Ten years ago, Mallat and Zhang proposed the Matching Pursuit algorithm : since then, the dictionary approach to signal processing has been a very active field. In this paper, we try to give an overview of a series of recent results in the field of sparse decompositions and nonlinear approximation with redundant dictionaries. We discuss sufficient conditions on a decomposition to be the unique and simultaneous sparsest expansion for all ,

. In particular, we prove that any decomposition has this nice property if the number of its nonzero coefficients does not exceed a quantity which we call the spread of the dictionary. After a brief discussion of the interplay between sparse decompositions and nonlinear approximation with various families of algorithms, we review several recent results that provide sufficient conditions for the Matching Pursuit, Orthonormal Matching Pursuit, and Basis Pursuit algorithms to have good recovery properties. The most general conditions are not straightforward to check, but weaker estimates based on the notions of coherence of the dictionary are recalled, and we discuss how these results can be applied to approximation and sparse decompositions with highly redundant incoherent dictionaries built by taking the union of several orthonormal bases. Eventually, based on Bernstein inequalities, we discuss how much approximation power can be gained by replacing a single basis with such redundant dictionaries.

INTRODUCTION

In many signal and image processing applications, it is desirable to find a representation where the data is "sparse" [START_REF] Rao | Signal processing with the sparseness constraint[END_REF] : replacing the original data with a sparse approximation can decrease substantially the processing cost. Early data representations were based on orthogonal linear transforms, but natural images and sounds contain superimposed features of very different nature (edges vs texture, transients vs stationary parts, ) that do not necessary have a sparse representation in a single basis. Ten years ago, Mallat and Zhang [START_REF] Mallat | Matching pursuit with time-frequency dictionaries[END_REF] proposed to look for sparse representations using redundant dictionaries and introduced the Matching Pursuit algorithm : since then, the dictionary approach to sparse decompositions and nonlinear approximation has become more and more popular.

In a Hilbert space of finite or infinite dimension, a dictionary is any family of unit vectors (called atoms) that spans (a dense subspace of) the entire space. Nonlinear approximation consists in approximating a vector with -term approximants of the form where card [START_REF] Rao | Signal processing with the sparseness constraint[END_REF] and the error of best -term approximation is defined as [START_REF] Mallat | Matching pursuit with time-frequency dictionaries[END_REF] where the infimum is taken over all possible choices of coefficients and index sets with card .

When is an orthonormal basis for , it is well known how to get the best -term approximant to any : the solution is to keep the atoms of the basis which have the largest inner products with . Moreover, in infinite dimension, the class of vectors that can be approximated at a given rate is known to coincide (up to some technicalities [START_REF] Stechkin | On absolute convergence of orthogonal series[END_REF][START_REF] Devore | Some remarks on greedy algorithms[END_REF]) with the class of elements that have sparse expansions in the sense When is a redundant dictionary, any has infinitely many possible representations . It is possible to choose a representation according to various sparseness measures. Among the most popular ones are the criteria : for , when is a frame , one can define the "norms"

where denotes the number of nonzero entries in and . For each sparseness measure, within the class the elements have exact sparse representations [START_REF] Gribonval | Nonlinear approximation with dictionaries. I. Direct estimates[END_REF] (which are not necessarily unique when )

When is redundant and , the sparsest expansion exists for all for . It changes drastically depending whether

or not [START_REF] Kreutz-Delgado | Convex/schur-convex (csc) log-priors and sparse coding[END_REF], but it is not clear in general whether depends on for . In Section 2 we introduce the notion of spread of a dictionary and prove some conditions on and that guarantee that Eq. ( 4) defines a unique which does not depend on . From the main results of Section 2 we derive the following Theorem, which generalizes to any what was obtained for in [START_REF] Donoho | Optimally sparse representation in general (non-orthogonal) dictionaries via minimization[END_REF][START_REF] Gribonval | Sparse decompositions in unions of bases[END_REF]. It is based on the coherence of a dictionary (5) THEOREM 1.1. Let an arbitrary dictionary in a finite of infinite dimensional Hilbert space. If with [START_REF] Kreutz-Delgado | Convex/schur-convex (csc) log-priors and sparse coding[END_REF] then is the unique and simultaneous solution to all minimization problems, i.e.

An immediate and very nice consequence is that for with a "sparse enough" representation, linear programming provides simultaneously the solution to all the highly nonlinear optimization problems .

For arbitrary redundant dictionaries, the interplay between the rate of best -term approximation and the sparseness of the expansions is not as clear as in the case of a single orthonormal basis, and getting the best -term approximation from an arbitrary redundant dictionary is a NP-hard problem [START_REF] Davis | Adaptive greedy approximations[END_REF]. In Section 3 we discuss some relations between the sparseness of the expansions of in and the rate of approximation of with various families of algorithms.

For more general dictionaries in infinite dimension, a similar norm can be defined but requires a topological definition [START_REF] Devore | Some remarks on greedy algorithms[END_REF][START_REF] Gribonval | Nonlinear approximation with dictionaries. I. Direct estimates[END_REF].

Several sub-optimal algorithms have been introduced such as Basis Pursuit [START_REF] Chen | Atomic decomposition by basis pursuit[END_REF], Matching Pursuit [START_REF] Mallat | Matching pursuit with time-frequency dictionaries[END_REF], and variants thereof [START_REF] Pati | Orthonormal matching pursuit : recursive function approximation with applications to wavelet decomposition[END_REF] to compute sparse decompositions or nonlinear approximations of signals with redundant dictionaries. In the last few years, many efforts have been put into understanding what structure should be imposed on (for a given dictionary), or on the dictionary itself, so that "good" approximants can be obtained with such algorithms [START_REF] Donoho | Optimally sparse representation in general (non-orthogonal) dictionaries via minimization[END_REF][START_REF] Gribonval | Sparse decompositions in unions of bases[END_REF][START_REF] Donoho | Uncertainty principles and ideal atomic decompositions[END_REF][START_REF] Elad | A generalized uncertainty principle and sparse representations in pairs of bases[END_REF][START_REF] Feuer | On sparse representations in pairs of bases[END_REF][START_REF] Fuchs | Une approche à l'estimation et l'identification simultanées[END_REF][START_REF] Fuchs | Detection and estimation of superimposed signals[END_REF][START_REF] Fuchs | On sparse representations in arbitrary redundant bases[END_REF][START_REF] Gilbert | Approximation of functions over redundant dictionaries using coherence[END_REF][START_REF] Tropp | Greed is good : Algorithmic results for sparse approximation[END_REF][START_REF] Gribonval | Exponential convergence of Matching Pursuit in quasi-incoherent dictionaries[END_REF][START_REF] Gilbert | Improved sparse approximation over quasi-incoherent dictionaries[END_REF]. In Section 5 we give a survey of a series of recent results that guarantee that some of these algorithms recover the "good" decompositions.

The most general exact recovery conditions expressed in Sections 2 and 4 are not straightforward to check. In Section 5 we recall weaker conditions that are based on estimates of the spread and the spark of (see Section 2) from its coherence (see Eq. ( 5)). We conclude by showing examples of highly redundant incoherent dictionaries where the results presented in this paper can be applied to perform nonlinear approximation and get sparse decompositions, and we discuss how much approximation power can be gained by replacing a single basis with such redundant dictionaries.

UNIQUENESS OF SPARSE EXPANSIONS,

In this section we review some conditions on and such that the minimization problem minimize subject to [START_REF] Donoho | Optimally sparse representation in general (non-orthogonal) dictionaries via minimization[END_REF] admits a unique solution, i.e. the sparse expansion given by Eq. ( 4) is unique. We also discuss some conditions so that this unique does not depend on .

Definitions

We will us extensively the following definitions. The support of a sequence is the set . We will call kernel of the dictionary the set Ker . For we define

Ker ( 8
)
where we use the convention and . For notational convenience, we will simply denote . Finally, we introduce the quantities Ker [START_REF] Davis | Adaptive greedy approximations[END_REF] Because decreases with , the maximal value (which is called the spark of in [START_REF] Donoho | Optimally sparse representation in general (non-orthogonal) dictionaries via minimization[END_REF]) and the minimal one (which we call the spread of , because it measures how much the sequences from the kernel of can spread -or how "flat" they can be-in the sense) will play a special role.

General results

In [START_REF] Gribonval | Sparse decompositions in unions of bases[END_REF] we proved the following Lemma by refining ideas from [START_REF] Donoho | Uncertainty principles and ideal atomic decompositions[END_REF][START_REF] Elad | A generalized uncertainty principle and sparse representations in pairs of bases[END_REF]. It shows that, given a representation , the value of can tell us if is necessarily the unique solution to Eq. ( 7).

LEMMA 2.1 (GRIBONVAL, NIELSEN). Let a (possibly redundant) dictionary, an index set and .

If there exists and with such that and .

If then, for all such that , is the unique solution to [START_REF] Donoho | Optimally sparse representation in general (non-orthogonal) dictionaries via minimization[END_REF] with .

COROLLARY 1. If and [START_REF] Chen | Atomic decomposition by basis pursuit[END_REF] then the unique solution to Eq. ( 7) is COROLLARY 2. If and

(11)
then the unique and simultaneous solution to all problems Eq. ( 7) is

Simplified results

Because the computation of is not straightforward, it may not be easy to check conditions [START_REF] Chen | Atomic decomposition by basis pursuit[END_REF] or [START_REF] Pati | Orthonormal matching pursuit : recursive function approximation with applications to wavelet decomposition[END_REF]. In particular, it is not known if varies monotonically with or not : if it were the case, the condition (11) would be simplified to . In [START_REF] Gribonval | Sparse decompositions in unions of bases[END_REF] we provided an upper estimate of in terms of , which is easily generalized here to any :

LEMMA 2.2. For any ,

Ker card card ( 12
)
It follows that we have :

COROLLARY 3. If and card ( 13
)
then the unique solution to Eq. ( 7) is

COROLLARY 4. If and card ( 14
)
then the unique and simultaneous solution to all problems Eq. ( 7) is

Corollary 4 shows that if has a "sparse enough" representation, then it does not matter which criterion is used to define sparseness. As a consequence, we can use the criterion, which shows that this very sparse representation can be recovered using linear programming. In practice, given , one does not know in advance whether has a sparse enough representation. Nevertheless, linear programming provides a minimizer , and it is possible to check whether is sparse enough. When the answer is positive, we know that it is the minimizer as well as the minimizer for . In such a case, it is particularly interesting to notice that linear programming has retrieved in polynomial time the optimum of the criterion, which usually requires a combinatorial search. How sparse should be the "sparse enough" representation so that the nice consequences of Corollary 4 hold, this depends on the value of the spread . The following result [START_REF] Donoho | Optimally sparse representation in general (non-orthogonal) dictionaries via minimization[END_REF][START_REF] Gribonval | Sparse decompositions in unions of bases[END_REF], which is somehow a converse to Corollary 3 for , illustrates the role of the spark :

LEMMA 2.3. If the integer is even, there exists with card and If is odd, the same is true for some with card .

We refer the reader to [START_REF] Gribonval | Sparse decompositions in unions of bases[END_REF] for a proof. Notice that when is odd, is the smallest integer value that exceeds . Hence, if some algorithm provides a representation of with card , we cannot draw conclusions about from the sole knowledge of card . In Section 5 we will see that, for dictionaries that are the union of orthonormal bases, there are sufficient conditions that ensure (resp.

) and are less restrictive than card (resp. card ).

Below is the coarsest but perhaps most general lower estimate on the spread , which is based on the coherence of (see Eq. ( 5)). The estimate coincides with the lower estimate on the spark obtained simultaneously in [START_REF] Donoho | Optimally sparse representation in general (non-orthogonal) dictionaries via minimization[END_REF] and [START_REF] Gribonval | Sparse decompositions in unions of bases[END_REF]. Its combination with Corollary 4 proves Theorem 1.1 which extends the results from [START_REF] Donoho | Optimally sparse representation in general (non-orthogonal) dictionaries via minimization[END_REF][START_REF] Gribonval | Sparse decompositions in unions of bases[END_REF] to any instead of just .

LEMMA 2.4. Let an arbitrary dictionary in finite or infinite dimension. Then In this section we have focused on general conditions on such that it solves simultaneously and uniquely Eq. ( 7) for all . In Section 4 we will discuss other general conditions that ensure exact recovery of a sparse expansion through linear programming, and we will see that a similar recovery can be obtained with several variants of Matching Pursuit instead of linear programming. The general conditions obtained in this section and in Section 4 are not straightforward to check on a given expansion, and in Section 5 we will see how to compute effectively verifiable sufficient conditions, based on the notion of coherence (see Eq. ( 5)).

SPARSE DECOMPOSITIONS AND NONLINEAR APPROXIMATION

For each , the sparse representations exist (but are not always unique) for every in the sparseness class . When is an orthonormal basis in infinite dimension, we have already mentioned that these sparseness classes actually coincide with approximation classes. Precisely, if we define the norm with [START_REF] Fuchs | Detection and estimation of superimposed signals[END_REF] we have with equivalent norms and [START_REF] Stechkin | On absolute convergence of orthogonal series[END_REF][START_REF] Devore | Some remarks on greedy algorithms[END_REF], and best -term approximants can be obtained through the thresholding strategy (also called greedy strategy) which consists in two steps :

1. compute the representation such that ;

2. threshold to keep the index set of the largest coefficients, and build the approximant

When is a Riesz basis, but not necessarily orthonormal, we still have with equivalent norms [START_REF] Gribonval | Some remarks on nonlinear approximation with Schauder bases[END_REF]. The thresholding strategy no longer provides the best -term approximants, but is not far from it [START_REF] Konyagin | A remark on greedy approximation in Banach spaces[END_REF]. In fact, it reaches the optimum rate of approximation : we have with equivalent norms, where is a new thresholding approximation class defined similarly to [START_REF] Gribonval | Some remarks on nonlinear approximation with Schauder bases[END_REF] by replacing, in Eq. ( 16), with , being obtained through the thresholding strategy.

When is redundant, it is possible to generalize the notion of thresholding approximation class [START_REF] Gribonval | Nonlinear approximation with dictionaries. I. Direct estimates[END_REF]. Without going into the details, in the first step of the thresholding strategy, several representations of are possible: the thresholding approximation class is based on the one which provides the highest rate of approximation (not necessarily the sparsest expansion). It is not known in general whether with equivalent norms, but as soon as is a frame we have [START_REF] Devore | Some remarks on greedy algorithms[END_REF][START_REF] Gribonval | Nonlinear approximation with dictionaries. I. Direct estimates[END_REF] the continuous embeddings with norm inequalities . The converse embedding , which corresponds (up to some nontrivial technicalities that involve interpolation of function spaces [START_REF] Devore | Nonlinear approximation[END_REF]) to a so-called Bernstein inequality for all -term expansions [START_REF] Gilbert | Approximation of functions over redundant dictionaries using coherence[END_REF] is known for some special redundant dictionaries [START_REF] Gribonval | On approximation with spline generated framelets[END_REF][START_REF] Gribonval | On the quasi-greedy property and uniformly bounded orthonormal systems[END_REF]. Bernstein inequalities are generally hard to prove, and it is still an open problem to characterize the class of dictionaries for which .

For a given , assuming we know that , a practical version of the thresholding strategy consists in thresholding a sparsest representation computed by some optimization algorithm. In general, as the value of is not known in advance, it is difficult to choose which criterion should be optimized. However we have seen in Section 2 that for elements that have "sparse enough" representations, does not depend on and can be computed using linear programming.

weaker conditions than being a frame are sufficient [START_REF] Gribonval | Nonlinear approximation with dictionaries. I. Direct estimates[END_REF], but their expression requires mathematical details that neither fit in this margin nor in this paper.

EXACT RECOVERY WITH SOME ALGORITHMS

Computing best -term approximant from an arbitrary redundant dictionary is a NP-hard problem [START_REF] Davis | Adaptive greedy approximations[END_REF], and several algorithms have been proposed to get sub-optimal approximants. In this section we recall the definition of the main algorithms and discuss some of their essential properties. In particular we review a series of recent results on exact recovery conditions that indicate some cases where these algorithms are (close to being) optimal. In the next section we will discuss how these exact recovery conditions can be checked on specially structured dictionaries that may be highly redundant.

Basis Pursuit

Basis Pursuit (BP) [START_REF] Chen | Atomic decomposition by basis pursuit[END_REF] is a principle rather than an algorithm. It consists in computing the sparsest representation of from based on the sparseness criterion. The implementations proposed in [START_REF] Chen | Atomic decomposition by basis pursuit[END_REF] combine recent methods of linear programming with ad hoc fast transforms based on the structure of the dictionary to speed up the computations as much as possible, but the computational complexity remains quite large and the implementation with poorly structured dictionaries is tricky. Recent approaches based on Minimum Fuel Neural Networks seem a promising direction [START_REF] Wang | Minimum fuel neural networks and their application to overcomplete signal representations[END_REF]. A variant is Basis Pursuit Denoising (BPD) which uses quadratic programming to compute [START_REF] Tropp | Greed is good : Algorithmic results for sparse approximation[END_REF] When the dictionary is a union of orthonormal bases (which may have common elements), the Block Coordinate Relaxation method [START_REF] Sardy | Block coordinate relaxation methods for nonparametric wavelet denoising[END_REF] seems a good strategy to perform the optimization.

Many numerical experiments on synthetic data [START_REF] Chen | Atomic decomposition by basis pursuit[END_REF] have lead to the observation that if happens to have a very sparse expansion in and if is well structured, then the sparse expansion is perfectly recovered through BP. The observation was turned into a series of proved theorems, first when is the union of two mutually incoherent bases [START_REF] Donoho | Uncertainty principles and ideal atomic decompositions[END_REF][START_REF] Elad | A generalized uncertainty principle and sparse representations in pairs of bases[END_REF][START_REF] Feuer | On sparse representations in pairs of bases[END_REF], then for the union of several mutually incoherent bases and for more general (quasi)incoherent dictionaries [START_REF] Donoho | Optimally sparse representation in general (non-orthogonal) dictionaries via minimization[END_REF][START_REF] Gribonval | Sparse decompositions in unions of bases[END_REF][START_REF] Fuchs | Une approche à l'estimation et l'identification simultanées[END_REF][START_REF] Fuchs | Detection and estimation of superimposed signals[END_REF][START_REF] Fuchs | On sparse representations in arbitrary redundant bases[END_REF][START_REF] Tropp | Greed is good : Algorithmic results for sparse approximation[END_REF].

One of the most general and most subtle results in this series is perhaps the following Theorem obtained by Fuchs [START_REF] Fuchs | Une approche à l'estimation et l'identification simultanées[END_REF][START_REF] Fuchs | Detection and estimation of superimposed signals[END_REF][START_REF] Fuchs | On sparse representations in arbitrary redundant bases[END_REF]. then BP exactly recovers the expansion, i.e. .

Fuchs obtained a similar result for BPD under a slightly stronger condition.

THEOREM 4.2 (FUCHS). Assume has an expansion in an arbitrary dictionary. For , denote the linear operator

. If is small enough and sign [START_REF] Gribonval | Some remarks on nonlinear approximation with Schauder bases[END_REF] where is the adjoint and the pseudo-inverse, then BPD "recovers" the expansion : each nonzero component of corresponds to an index .

How small should be is a function of the index set and, most of all, of the magnitude of the smallest components in . Note that when Eq.( 22) is satisfied, Eqs. ( 20) and ( 21) are also satisfied with sign , hence Eq. ( 22) implies that plain BP allows a perfect recovery.

The results of Fuchs are subtle in the sense that they take into account not only the support of the representation, but also its sign sign . If we are not willing to go into such details, noticing that sign sign we recover the Exact Recovery Condition of Tropp [START_REF] Tropp | Greed is good : Algorithmic results for sparse approximation[END_REF] [Theorem 3.3] as a corollary of Fuchs' results.

THEOREM 4.3 (TROPP).

Assume in an arbitrary dictionary, and let . If [START_REF] Konyagin | A remark on greedy approximation in Banach spaces[END_REF] then BP exactly recovers the expansion, i.e. is the unique -sparsest expansion of .

Because of Lemma 2.1, we have [START_REF] Devore | Nonlinear approximation[END_REF] but it is not clear whether the converse is true. Another question is whether ( 23) implies for some .

Matching Pursuit and its variants

Matching Pursuit (MP) [START_REF] Mallat | Matching pursuit with time-frequency dictionaries[END_REF] is an iterative greedy algorithm that builds -term approximants and residuals by adding one term at a time in the approximant. At the beginning we set and ; assuming and are defined, we set [START_REF] Gribonval | On approximation with spline generated framelets[END_REF] (26) [START_REF] Wang | Minimum fuel neural networks and their application to overcomplete signal representations[END_REF] MP is also known as Projection Pursuit in the statistics community [START_REF] Friedman | Projection pursuit regression[END_REF][START_REF] Huber | Projection pursuit[END_REF] and as a Pure Greedy Algorithm [START_REF] Temlyakov | Weak greedy algorithms[END_REF] in the approximation community. In infinite dimension, it might not be possible to attain the maximum in Eq. ( 25) so "weak" variants are possible where we only require with

Both plain MP and its weak variants are known to converge [START_REF] Jones | On a conjecture of Huber concerning the convergence of PP-regression[END_REF], i.e. , as soon as the dictionary spans (a dense subspace of) the entire space . In finite dimension, the convergence is even exponential [START_REF] Mallat | Matching pursuit with time-frequency dictionaries[END_REF] but there is in general no control on the convergence rate compared to best -term approximation.

Orthonormal Matching Pursuit (OMP) [START_REF] Pati | Orthonormal matching pursuit : recursive function approximation with applications to wavelet decomposition[END_REF] is a variant of MP where the update step given by Eq. ( 26) is replaced with [START_REF] Friedman | Projection pursuit regression[END_REF] where is the orthonormal projector onto the linear span of . Just as plain MP, Orthonormal Matching Pursuit is convergent [START_REF] Temlyakov | Weak greedy algorithms[END_REF].

Several counter-example have been built that show that, in infinite dimension, it is possible to find "bad" dictionaries and "good" functions for which MP provides "bad" approximants. In [START_REF] Devore | Some remarks on greedy algorithms[END_REF] a dictionary is built where for some special , we have . In [START_REF] Livschitz | Two lower estimates in greedy approximation[END_REF], another construction provides , with a convergence as slow as . Orthonormal Matching Pursuit has a better behaviour in terms of convergence rate, in particular [START_REF] Devore | Some remarks on greedy algorithms[END_REF]. Such counter-examples illustrate the need for conditions on and/or to ensure a good behaviour of MP. The first positive result in this direction was obtained when Villemoes [START_REF] Villemoes | Nonlinear approximation with walsh atoms[END_REF] proved that for Walsh wavelet packets, MP on "good functions" ( any sum of any two wavelet packets) picked up one of the two "correct" wavelet packets at each step and was exponentially convergent with .

Nothing much happened in this direction until Gilbert et al. [START_REF] Gilbert | Approximation of functions over redundant dictionaries using coherence[END_REF][START_REF] Gilbert | Improved sparse approximation over quasi-incoherent dictionaries[END_REF] proved that (a variant of) Orthonormal Matching Pursuit recovers sufficiently sparse expansions over incoherent dictionaries. As shown by Tropp [START_REF] Tropp | Greed is good : Algorithmic results for sparse approximation[END_REF], the "sufficiently sparse expansion" condition turned out to be actually given by the Exact Recovery Condition, Eq. ( 23). Thus, the Exact Recovery Condition is not only sufficient for BP to exactly recover an expansion, it also works for OMP, and it is a sharp condition. Later on the result was extended [START_REF] Gribonval | Exponential convergence of Matching Pursuit in quasi-incoherent dictionaries[END_REF] to plain MP as follows. Note that, when Theorem 4.4 is applied to the Walsh wavelet packet dictionary and , we recover the result of Villemoes [START_REF] Villemoes | Nonlinear approximation with walsh atoms[END_REF].

THEOREM 4.4 (TROPP, GRIBONVAL-VANDERGHEYNST). Assume in an arbitrary dictionary and let (which need not be a finite set).

1. If [START_REF] Huber | Projection pursuit[END_REF] then plain (resp. Orthogonal) Matching Pursuit recovers the expansion, in the sense that at each step, a "correct" atom is chosen : .

2. If [START_REF] Huber | Projection pursuit[END_REF] is not satisfied, there exists for which .

3. If card the convergence to with OMP occurs in a finite number of steps. With MP, the convergence is exponential, and if card we have the estimate card [START_REF] Temlyakov | Weak greedy algorithms[END_REF] Let us give the flavour of the proof. Denoting the linear span of , Eq. ( 30) ensures for all that As and , we get inductively that , (see Eqs. ( 26)-( 29) and , hence the first part of the result :

. The second part is almost trivial: for OMP, each index can be chosen only once because the residuals are orthogonal to the atoms selected at previous steps; for MP, we simply notice that the pursuit is performed in the finite dimensional space , hence the exponential convergence [START_REF] Mallat | Matching pursuit with time-frequency dictionaries[END_REF].

As noted by Tropp, a similar exact recovery condition ensures (sharply) the good behaviour of weak versions of MP and OMP, where the selection of the atom at each step if performed according to Eq. ( 28).

When does not satisfy the assumptions of Theorem 4.4, it may happen that its best -term approximation is better conditioned in the sense that satisfies Eq. [START_REF] Huber | Projection pursuit[END_REF]. In this case, Tropp [START_REF] Tropp | Greed is good : Algorithmic results for sparse approximation[END_REF] proved that OMP will pick up "correct" atoms until it reaches a good enough approximant. MP [START_REF] Gribonval | Exponential convergence of Matching Pursuit in quasi-incoherent dictionaries[END_REF] as well as other combinations of variants of MP [START_REF] Gilbert | Approximation of functions over redundant dictionaries using coherence[END_REF][START_REF] Gilbert | Improved sparse approximation over quasi-incoherent dictionaries[END_REF] share the same "provably good behaviour".

HIGHLY REDUNDANT INCOHERENT DICTIONARIES

So far we have mentioned a series of conditions that ensure the good behaviour of a variety of approximation or sparse decomposition algorithms. These conditions (Eqs. ( 10)-( 14) and ( 23)) are generally not straightforward to check on a given representation . Using the coherence of or its so-called Babel function, several estimates that can actually be checked have been proposed [START_REF] Donoho | Optimally sparse representation in general (non-orthogonal) dictionaries via minimization[END_REF][START_REF] Gilbert | Approximation of functions over redundant dictionaries using coherence[END_REF][START_REF] Tropp | Greed is good : Algorithmic results for sparse approximation[END_REF][START_REF] Gilbert | Improved sparse approximation over quasi-incoherent dictionaries[END_REF], one of which is given by Lemma 2.4. In this section we focuss on sufficient conditions for exact recovery based on the coherence, and we show that there exists highly redundant incoherent dictionaries where the exact recovery conditions are easily met.

Exact recovery conditions for unions of bases

The first condition given in Lemma 2.4 was a lower bound on the spread based on the coherence . In [START_REF] Gribonval | Sparse decompositions in unions of bases[END_REF] we proved other sufficient conditions for dictionaries that are the union of orthonormal bases, i.e.

where is an orthonormal basis, . The results, which generalize those obtained previously for pairs of bases [START_REF] Donoho | Uncertainty principles and ideal atomic decompositions[END_REF][START_REF] Elad | A generalized uncertainty principle and sparse representations in pairs of bases[END_REF][START_REF] Feuer | On sparse representations in pairs of bases[END_REF] The second condition Eq. ( 34) is obtained from Theorem 5.1 by noticing that Eq. ( 34) implies Eq. ( 32). Moreover, Tropp proved that Eq. ( 32) implies the exact recovery condition (Eq. ( 23)), so in summary we have card

The quantity is a natural candidate as a lower estimate on the spread , but this is still a conjecture. For it is not clear whether a condition similar to Eq. ( 32) can be derived which ensures .

Existence of highly redundant incoherent dictionaries

In finite dimension , as soon as the dictionary contains an orthonormal basis, it is not difficult to check that the value of the coherence is at least . Thus, a dictionary which contains an orthonormal basis is said to be (perfectly) incoherent if its coherence is minimum . For , a well known pair of bases is incoherent : EXAMPLE 1 (DIRAC-FOURIER). Let the Dirac basis in and the complex Fourier basis. Then is incoherent.

The Dirac-Fourier dictionary was indeed the first for which exact recovery conditions were proved [START_REF] Donoho | Uncertainty principles and ideal atomic decompositions[END_REF]. Other examples of pairs of incoherent bases can be built, e.g., based on the Haar and the Walsh systems on (see [START_REF] Gribonval | Nonlinear approximation with dictionaries. II. Inverse estimates[END_REF][START_REF] Golubov | Walsh series and transforms, Theory and applications[END_REF]). Let us see that it is actually possible to have unions of several orthonormal bases that are incoherent. The proof of Theorem 5.3 can be found in [START_REF] Calderbank | -Kerdock codes, orthogonal spreads, and extremal Euclidean line-sets[END_REF][START_REF] Strohmer | Grassmannian frames with applications to coding and communications[END_REF]. THEOREM 5.3. Let , and consider . There exists a dictionary in consisting of the union of orthonormal bases for , such that for any pair : .

For , and , one can find a dictionary in consisting of the union of orthonormal bases for , again with the perfect incoherence property:

. The dictionaries given by Theorem 5.3 are called Grassmannian frames due to the connection between their construction and the Grassmannian packing problem [START_REF] Strohmer | Grassmannian frames with applications to coding and communications[END_REF]. They can be highly redundant: in the complex case, can contain as many as atoms.

Given an arbitrary orthonormal basis , it is not difficult to check from the above theorem that it is possible to complete with other bases which are incoherent. However, it does not seem clear whether such a completion is still possible when the first two mutually incoherent bases are fixed. In the case the Dirac and Fourier bases, the Chirp basis can be added to get three incoherent basis, but additional work is needed to know if the construction can go further. The reader interested in the construction of quasi-incoherent dictionaries (with ) is referred to [START_REF] Strohmer | Grassmannian frames with applications to coding and communications[END_REF] and [START_REF] Gilbert | Approximation of functions over redundant dictionaries using coherence[END_REF] where some other constructions are proposed.

  can write for any index hence we get . Taking the supremum of all we obtain . from which we reach the desired result.

THEOREM 4 . 1 (

 41 FUCHS). Assume has an expansion in an arbitrary dictionary. If there exists such

ACKNOWLEDGMENTS

The authors thanks R. DeVore for initiating their interest in this research and D. Donoho for suggesting -at a meeting of the Wavelet IDR Center in Florham Park in fall 1999-to look for optimality results for Basis Pursuit with more than two orthonormal bases. We also want to thank Joel Tropp and Jean-Jacques Fuchs for pointing out some chronological inaccuracies in the first version of this paper.

CONCLUSION

We have discussed several issues related with nonlinear approximation and sparse decompositions with redundant dictionaries. We have proved that, under some general conditions, the "sparsest" representation of an element is unique and does not depend on the choice of the sparseness measure , . These results complete a series of recent advances which show that Basis Pursuit is a provably good strategy for sparse decomposition of signals over redundant dictionaries.

We have reviewed and made connections between different "exact recovery conditions" that turn out to ensure simultaneously the good behaviour of Basis Pursuit and Matching Pursuit (and variants thereof). Because these general conditions are not always straightforward to check, we have provided easily verifiable conditions based on the coherence of a dictionary. Besides general dictionaries, we have given specific results for unions of several orthonormal bases.

Besides the now classical pairs of mutually incoherent bases such as the Dirac-Fourier bases, we have shown that there exists highly redundant incoherent dictionaries built by taking the union of several mutually incoherent bases. A key question, back to applied signal/image processing, is whether and how one can build "useful" and "meaningful" families of incoherent bases, and in particular whether it is possible to do it incrementally. We are currently investigating such matters. Besides algebraic construction methods [START_REF] Calderbank | -Kerdock codes, orthogonal spreads, and extremal Euclidean line-sets[END_REF][START_REF] Strohmer | Grassmannian frames with applications to coding and communications[END_REF], we believe a promising direction consists in "learning" the bases from training datasets [START_REF] Field | Emergence of simple-cell receptive field properties by learning a sparse code for natural images[END_REF][START_REF] Bell | The 'independent components' of natural scenes are edge filters[END_REF][START_REF] Bell | Learning the higher-order structure of a natural sound[END_REF][START_REF] Lewicki | Efficient coding of natural sounds[END_REF][START_REF] Abdallah | If edges are the independent components of natural images, what are the independent components of natural sounds?[END_REF].

Let us conclude this paper by mentioning that for incoherent dictionaries, a Bernstein inequality can be proved [START_REF] Gribonval | Nonlinear approximation with dictionaries. II. Inverse estimates[END_REF]. Instead of Eq. ( 18) with we have for incoherent dictionaries for all -term expansions with , hence the approximation class introduced in Section 3 is, up to technicalities that involve interpolation spaces, continuously embedded into the sparseness class . We conjecture that this result is sharp for unions of incoherent bases. This conjecture is optimistic : as , it implies which means that we gain in approximation power when combine several incoherent bases. To see it, notice [START_REF] Gribonval | Nonlinear approximation with dictionaries. I. Direct estimates[END_REF] that so the sharpness of the Bernstein inequality would show that there exists elements that can be approximated at a good rate from (they are in the approximation class ) even if they have no decomposition as a sum of elements , which can individually be approximated at the same good rate. In a sense, taking unions of incoherent bases would double the approximation power for some elements. The negative aspect of the conjecture is that thresholding approximation algorithms as well as Matching Pursuits will probably have a limited ability to approximate such elements, and other strategies will have to be investigated to get effectively computable good approximants. It may very well be that these elements for which the approximation gain is potentially substantial are those where the NP-hardness [START_REF] Davis | Adaptive greedy approximations[END_REF] of -term approximation eventually shows up.


Li Xiong

John H Xuereb

Maria Grazia Spillantini

Karalyn Patterson

John R Hodges

Peter J Nestor

Clinical comparison of progressive aphasia associated with Alzheimer versus FTD-spectrum pathology

Keywords: Progressive aphasia, Frontotemporal dementia, Alzheimer disease

niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Progressive non-fluent aphasia (PA) is a clinical syndrome defined by consensus criteria, [START_REF] Neary | Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria[END_REF] of slow, effortful speech production characterized by anomia plus phonological and grammatical errors. Single word comprehension and non-linguistic cognitive functions are relatively preserved in the early stages. PA is one of the clinical subgroups of frontotemporal lobar degeneration (FTLD), the others being semantic dementia (SD) and behavioural variant frontotemporal dementia (bvFTD). Histopathologically, clinical FTLD can be associated with tau-positive inclusions (including classic Pick's disease as well as pathology consistent with progressive supranuclear palsy or corticobasal degeneration); ubiquitin-positive inclusions (including overlap cases with motor neuron disease); and cases with neither tau nor ubiquitin inclusions (dementia lacking distinctive histology, DLDH). [START_REF] Kertesz | The evolution and pathology of frontotemporal dementia[END_REF] A growing number of studies, however, indicate that approximately one third of cases with the clinical syndrome of PA have AD pathology at necropsy. [START_REF] Li | An autopsy case of Alzheimer's disease presenting with primary progressive aphasia: a clinicopathological and immunohistochemical study[END_REF][START_REF] Alladi | Focal cortical presentations of Alzheimer's disease[END_REF][START_REF] Knibb | Clinical and pathological characterization of progressive aphasia[END_REF] This does not appear to be the case with the other FTLD syndromes-in one study, the rate of AD pathology was 44.1% in PA compared to only 7.1% of clinical bvFTD and 10% of SD. [START_REF] Alladi | Focal cortical presentations of Alzheimer's disease[END_REF] Comparable findings were reported in a separate study in which PA was subsumed under the label of 'primary progressive aphasia'. [START_REF] Kertesz | The evolution and pathology of frontotemporal dementia[END_REF] The pathological heterogeneity of clinical PA poses a challenge to accurate prediction of pathology in vivo. More recently, a subordinate PA syndrome called 'logopenic aphasia' (LPA) has been described, the salient features of which are slow speech with anomia and word-finding pauses, while production of grammar, articulation and single-word comprehension are relatively spared. [START_REF] Gorno-Tempini | Cognition and anatomy in three variants of primary progressive aphasia[END_REF] Amyloid ligand imaging suggests that Alzheimer pathology is the most probable diagnosis in this group. [START_REF] Rabinovici | Abeta amyloid and glucose metabolism in three variants of primary progressive aphasia[END_REF][START_REF] Mesulam | Alzheimer and frontotemporal pathology in subsets of primary progressive aphasia[END_REF] Although LPA is a fluent aphasia in the grammatical sense, word finding pauses can lead to a slowing of speech output; a separation of PA into PNFA (agrammatic) and LPA (anomic) has been proposed. [START_REF] Gorno-Tempini | The logopenic/phonological variant of primary progressive aphasia[END_REF] In pragmatic terms, improving clinical prediction of underlying pathology need not focus exclusively on linguistic features in PA. For instance, a nuclear imaging study reported that hypofunctioning of bilateral temporo-parietal association cortex (TPA)-as is found in clinical AD-was highly specific in predicting AD pathology in clinically diagnosed PNFA, while normal TPA perfusion or metabolism was highly specific for FTD-spectrum pathology. [START_REF] Nestor | Nuclear imaging can predict pathologic diagnosis in progressive nonfluent aphasia[END_REF] Although this finding provided the possibility to predict AD-pathology with standard diagnostic tests in PA in vivo, the sensitivity of nuclear imaging was low. The aim of the present study, therefore, was to search retrospectively for other clinical features that might discriminate AD from FTD-spectrum pathology. Using post-mortem pathological diagnosis as the gold standard to divide patients into AD versus FTD-spectrum pathology groups, we compared demographic, general neuropsychological, neuropsychiatric and structural imaging features. Although new techniques such as amyloid-ligand imaging offer the potential to classify patients accurately into AD and FTD-spectrum pathology, [START_REF] Rabinovici | 11C-PIB PET imaging in Alzheimer disease and frontotemporal lobar degeneration[END_REF] such techniques are presently restricted to research settings. Should these procedures find clinical application in the future, cost and availability will keep them out of reach of many cognitive disorders clinics. Similarly, although the LPA syndrome suggests that certain linguistic features neuropsychological evaluation and an MMSE score of ≤23/30. As different neuropsychological test batteries were used during the 19 year recruitment period, we were unable to contrast test performance directly and were, instead, limited to a simple binary classification of "impaired" vs. "preserved" global function. Specifically assessed neuropsychiatric behaviours included exacerbated preference for sweet food, disinhibition, apathy and depression. These four features were chosen because previous research has suggested that sweet food preference and disinhibition have specificity for FTD; apathy is extremely prevalent in FTD; and lack of insight in FTD is suggested to be associated with less depression. [START_REF] Bozeat | Which neuropsychiatric and behavioural features distinguish frontal and temporal variants of frontotemporal dementia from Alzheimer's disease?[END_REF][START_REF] Ikeda | Changes in appetite, food preference, and eating habits in frontotemporal dementia and Alzheimer's disease[END_REF] 2/ Visuospatial ability and non-verbal memory Rey figure copy and delayed recall after 30 minutes, as measures of visuospatial ability and non-verbal memory, [START_REF] Osterrieth | Le test de copie d'une figure complexe[END_REF] were available from the first examination in 25 patients (AD n=11; FTD-spectrum n=14).

3/ Structural imaging

Structural imaging from the original clinical work-up was available in 21 patients (magnetic resonance imaging in 20; computerized tomography in one): six with AD, and 15 with FTD-spectrum, pathology. Previous reports have suggested that disproportionate and, particularly, asymmetric frontotemporal atrophy has predictive value in discriminating FTD from AD. [START_REF] Likeman | Visual assessment of atrophy on magnetic resonance imaging in the diagnosis of pathologically confirmed young-onset dementias[END_REF][START_REF] Kitagaki | Frontotemporal dementia and Alzheimer disease: evaluation of cortical atrophy with automated hemispheric surface display generated with MR images[END_REF][START_REF] Varma | Diagnostic patterns of regional atrophy on MRI and regional cerebral blood flow change on SPECT in young onset patients with Alzheimer's disease, frontotemporal dementia and vascular dementia[END_REF] Visual ratings of scans, blinded to pathological group and clinical details, were conducted. Scans were rated for the presence or absence of unequivocal disproportionate, and/or asymmetrical, frontal and/or temporal lobe atrophy (so-called 'knife-edge' atrophy). Inter-rater and intra-rater reliability were both 95.2%; in each case disagreement involved the same single subject (an FTD-spectrum patient); there was complete agreement in the ratings for the cases identified as having AD pathology.

4/ Confrontation naming

Although the aim of this study was to identify general clinical features that predict pathological diagnosis rather than to compare language profiles, scores on confrontation naming were available in N=25 patients (n=10 AD; n=15 FTD-spectrum) and so are included here. The Cambridge-devised naming test used in our research programme was altered during the period from which the current cohort of cases was sampled: the initial version contained 48 items and the subsequent version has 64 items (line drawings of familiar objects in both cases). Of the 25 cases with naming scores, N=13 and N=12 had done the 64-item and 48-item versions respectively (N=5 AD for each version). As reported in a previous publication, [START_REF] Woollams | Anomia: a doubly typical signature of semantic dementia[END_REF] during the period of transition from use of the 48-to the 64-item version of this naming test, 13 patients with semantic dementia were given both versions in the same testing round to enable evaluation of the comparability of the two tests. The correlation between those patients' scores on the two versions was nearly perfect (r=0.99); it was therefore deemed safe to convert all scores to proportion correct and treat the two versions as equivalent. For present purposes, we wanted to compare naming error types as well as proportions correct. The errors were classified by a single observer (KP), blinded to pathological group, into the following categories: no response; circumlocutory semantic description (e.g. target: sledge; response: "slides down a hill"); single word semantic substitution (e.g. target: guitar; response: "violin"); phonological error (e.g. target: motorcycle; response: "myskikle"; incomplete word fragment (e.g. target: seahorse; response "horse"); and unclassifiable (e.g. target: pliers; response: "gerse").

Pathological diagnosis (Fig. 1a): Brains were examined by the same senior neuropathologist (JHX) blind to the clinical information using histological and immunohistochemical methods detailed previously. [START_REF] Alladi | Focal cortical presentations of Alzheimer's disease[END_REF][START_REF] Knibb | Clinical and pathological characterization of progressive aphasia[END_REF] AD pathology was diagnosed in cases reaching Braak stage 4 or greater, with presence of both neuritic plaques and neurofibrillary tangles, and with involvement of the isocortex (n=13). FTD-spectrum pathologies were diagnosed and divided into three subgroups according to immunohistochemical criteria. The first was a tau-positive group (FTD-T) that included classic Pick's disease (n=3); corticobasal degeneration (CBD) (n=4); progressive supranuclear palsy (PSP) (n=4); and one with tangle only pathology and marked cell loss in BA 44/45 and 39. Second was FTD with ubiquitin-positive inclusions (FTD-U) (n=6); all were TAR DNA binding protein (TDP43) positive. One patient in the FTD-U group developed clinical motor neuron disease six years after symptom onset. The third group was tau-negative and ubiquitin-negative (dementia lacking distinctive histology, DLDH, n=2). Two of the 33 patients had mixed pathology: one FTD patient confirmed by tau-positive Pick bodies also showed minor, incidental AD changes; and one patient reaching the criterion for AD pathology also had early Parkinson's pathology.

Results

Demographic characteristics (Table 1)

Although age at onset was 2.0 years older in the AD group, the degree of overlap between groups was high (Fig. 1b). Onset before 65 years occurred in 62% of patients with AD pathology (n=8) versus 45% of cases with FTD-spectrum pathology (n=9). Onset age before 60 years, however, occurred in seven (35%) of the FTD-spectrum group compared to only one (8%) with AD pathology. Onset before 60 years yielded specificity of 92% and a positive predictive value (PPV) of 88% for FTD-spectrum pathology although sensitivity for this was low (35%). The mean age at death in the AD pathology group was 73.4 (SD 7.4, range 63.8-85.5), 2.7 years older than that of the FTD-spectrum pathology group (mean 70.7, SD 8.8, range 52.0-84.9). Kaplan-Meier survival curves are shown in Fig. 1c. Median survival in the AD pathology group was 8.1 years from symptom onset, and 6.3 years in the FTD-spectrum pathology group (P=0.81, log rank test). Dividing the FTD-spectrum group into tau-positive (n=12) and tau-negative (n=8), there was trend towards a difference favouring the tau-positive cases (median survival 7.8 years versus 4.0 years, P=0.10).

Cognitive function (Table 2)

62% of AD pathology patients and 80% of FTD-spectrum pathology patients had preserved global function within the first two years after onset, and this characteristic was only 38.5% specific and 80.0% sensitive for predicting FTD-spectrum pathology. The time duration from onset to ADL impairment was similar in the two groups as was performance of copy and recall of the Rey figure. With regard to the Rey figure, it was notable that each pathological group contained patients with both normal and severely impaired performance (Rey figure copy score range 2.5-35 in AD and 2-35 in FTD-spectrum; Rey figure delayed recall score range 0-18 in AD and 0-22.5 in FTD-spectrum). Importantly there was no difference in time from symptom onset to Rey figure testing that might have biased the results (AD group mean 3.00, FTD-spectrum group mean 3.49, P=0.63).

Neuropsychiatric characteristics (Table 3)

Emergence of a sweet food preference had the highest specificity (92.3%) for FTD-spectrum pathology, but sensitivity was very low (25.0%). The other most specific features for FTD-spectrum pathology were disinhibition (76.9% specific, 45.0% sensitive) and apathy (69.2% specific, 40.0% sensitive). Absence of depression was not useful in predicting FTD-spectrum pathology (sensitivity 55.0%, specificity 38.5%). Imaging features (Fig. 2) None of the six available scans from patients with AD pathology had disproportionate or asymmetrical frontotemporal atrophy (knife-edge atrophy), while this feature was evident in six of 15 in the FTD-spectrum pathology group. Therefore, knife-edge atrophy was 100% specific and 40.0% sensitive for FTD-spectrum pathology. The PPV and NPV of knife-edge atrophy for FTD-spectrum pathology were 100% and 40.0% respectively.

Co-occurrence of features

As the results indicated that (i) early age of onset, (ii) sweet food preference, (iii) disinhibition and (iv) knife-edge atrophy on structural imaging had the highest specificity (>70%) for FTD-spectrum pathology, a survey of prevalence of these symptoms was undertaken in the 15 FTD-spectrum patients who had had imaging. This revealed that 6/15 patients had one of these features; 6/15 had two features; 2/15 had three features; none had all four features. Only one FTD-spectrum patient had none of these features.

As less than half of the AD-pathology group had structural imaging available, the same survey could not be undertaken. Comparing the prevalence of features (i) -(iii) alone, the results were as follows: in FTD-spectrum pathology, 4/20 had no features; 11/20 had one feature; 5/20 had two features; none had all three features. In the AD pathology group, 10/13 (77%) had no features; 1/13 had one feature; 2/13 had two features; none had all three features.

Naming (Table 4)

The AD group made a significantly greater proportion of "don't know" responses (P<0.001). The FTD-spectrum group made a significantly greater proportion of single word semantic substitutions (P=0.01). All other error rates were comparable between groups. Interestingly, none of the FTD-U patients made phonological errors in confrontation naming; excluding these, the proportions of patients with FTD-T and AD that made phonological errors were similar: 6/9 versus 6/10 patients respectively.

Discussion

Grouping patients by pathology, four clinical features demonstrated specificity in predicting FTD-spectrum rather than AD pathology in patients presenting with PA: onset before 60 years, sweet food preference, disinhibition, and knife-edge fronto-temporal atrophy on structural neuroimaging. An examination of the combined prevalence of these features indicated that the majority of the FTD-spectrum group exhibited at least one feature whereas the majority of AD group had none. Neither early global cognitive impairment, poor non-verbal memory nor early impairment of self care was helpful in distinguishing AD pathology from FTD-spectrum pathology.

The AD pathology group was older than the FTD-spectrum group, consistent with the recognized consensus that FTD, on average, has an earlier onset than AD. [START_REF] Blair | A longitudinal study of language decline in Alzheimer's disease and frontotemporal dementia[END_REF][START_REF] Grossman | Frontotemporal dementia: a review[END_REF] Although 'early-onset' dementia is typically defined as before 65 years and FTD is considered a major cause of early-onset dementia, [START_REF] Grossman | Frontotemporal dementia: a review[END_REF][START_REF] Ratnavalli | The prevalence of frontotemporal dementia[END_REF] the present study indicated that this age was not a discriminating cut-off. About half of the patients in both groups had onset before 65 years. Onset before 60 years, however, had 92% specificity in predicting FTD-spectrum pathology in this series. At the other end of the age spectrum, onset beyond 65 years was not predictive of AD pathology; the oldest FTD-spectrum patient (FTD-U pathology) had symptom onset at 76.8 years.

The AD pathology group had a 1.8 year longer median survival, even though their mean age of onset was higher than the FTD-spectrum pathology group. Considering that advancing age is also a risk factor for death, this observation implies that PA patients with FTD-spectrum pathology progress faster, consistent with previous reports indicating that FTD is a more aggressive disease than AD. [START_REF] Rascovsky | Rate of progression differs in frontotemporal dementia and Alzheimer disease[END_REF][START_REF] Roberson | Frontotemporal dementia progresses to death faster than Alzheimer disease[END_REF] In passing, it was noted that the FTD-spectrum PA patients with tau-positive inclusions had a significantly better prognosis than those with tau-negative pathology, a finding consistent with a previous report. [START_REF] Roberson | Frontotemporal dementia progresses to death faster than Alzheimer disease[END_REF] One might expect that AD pathology would be associated with a greater prevalence of early global cognitive decline as well as more deficits in non-linguistic cognitive domains such as memory and visuospatial ability. In fact, severe amnesia and visuospatial impairment have been regarded as exclusion criteria for FTLD according to the current consensus statement. [START_REF] Neary | Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria[END_REF] The present study, however, found no evidence to support a significant role of these deficits in discriminating between pathological groups. A substantial 62% of patients with AD pathology had preserved global function within the first two years following symptom onset. Measures of visuo-constructional ability and non-verbal memory from the Rey complex figure test yielded no significant differences between the two groups. Furthermore, although one cannot exclude the possibility that significant differences might have emerged with greater statistical power, it is unlikely that such a scenario would have any genuine clinical diagnostic utility because both groups in this series contained individuals with either normal or severely impaired performance on either measure. In recent studies, marked amnesia also presented as the dominant syndrome in 11% of pathologically confirmed FTD patients. [START_REF] Graham | Pathologically proven frontotemporal dementia presenting with severe amnesia[END_REF][START_REF] Knopman | Antemortem diagnosis of frontotemporal lobar degeneration[END_REF] This study confirms that, in the PA subgroup of FTD, the presence of anterograde amnesia cannot be regarded as a strict criterion to distinguish AD pathology from FTD-spectrum pathology; this resonates with a recent finding of comparable anterograde memory impairment in bvFTD and early AD suggesting that memory impairment might be a less desirable exclusion criterion for FTLD than previously thought. [START_REF] Hornberger | How preserved is episodic memory in behavioral variant frontotemporal dementia?[END_REF] In contrast to those with early global decline, it was not possible to estimate whether there was a group difference in time to global cognitive impairment in those who had been intact at two years because many still had a relatively pure aphasia at their last clinic assessment. Anecdotally the most extreme examples were an AD pathology case and an FTD-spectrum case (PSP pathology) both with isolated language syndromes nine years and eight years, respectively, from symptom onset. In summary, although it has been proposed that the syndrome of "primary progressive aphasia" be reserved for patients with a relatively pure aphasia in, at least, the first two years of symptoms, [START_REF] Mesulam | Primary progressive aphasia: sharpening the focus on a clinical syndrome[END_REF] no evidence could be found in the current series to suggest that this rule conveys any meaningful distinction in pathological terms.

Time from onset to impairment of ADLs was also approximately equal between the two groups. Previous studies have reported that FTLD patients were more impaired than AD patients on basic ADLs. [START_REF] Rascovsky | Rate of progression differs in frontotemporal dementia and Alzheimer disease[END_REF][START_REF] Binetti | Differences between Pick disease and Alzheimer disease in clinical appearance and rate of cognitive decline[END_REF] These studies, however, did not distinguish between the three subtypes of FTLD. A recent study of ADLs that divided FTLD into its three clinical subtypes and also included a clinical AD group matched for disease duration, reported that the bvFTD group was most affected whereas clinical PA and clinical AD were less severely impaired. [START_REF] Mioshi | Activities of daily living in frontotemporal dementia and Alzheimer disease[END_REF] Taken together these studies suggest that bvFTD may be the subgroup that drives the apparent observation of FTLD as a condition that genuinely disrupts everyday functioning. The current findings additionally suggest that time to impairment of ADLs in PA is not dependent on pathological type.

Regarding neuropsychiatric features, sweet food preference and disinhibition were highly specific for FTD-spectrum pathology but with low sensitivity. These two features have been consistently reported to have value in distinguishing FTD from AD, [START_REF] Bozeat | Which neuropsychiatric and behavioural features distinguish frontal and temporal variants of frontotemporal dementia from Alzheimer's disease?[END_REF][START_REF] De Vugt | Impact of behavioural problems on spousal caregivers: a comparison between Alzheimer's disease and frontotemporal dementia[END_REF][START_REF] Bathgate | Behaviour in frontotemporal dementia, Alzheimer's disease and vascular dementia[END_REF] and the present results indicate that these features have specificity with respect to this discrimination specifically within PA patients. Given that SD and bvFTD seem rarely to be associated with AD pathology, [START_REF] Kertesz | The evolution and pathology of frontotemporal dementia[END_REF][START_REF] Davies | The pathological basis of semantic dementia[END_REF] the present results imply that sweet food preference and disinhibition are reasonably specific for all three variants of FTD once PA associated with AD pathology is excluded.

Knife-edge atrophy on structural imaging was 100% specific for FTD-spectrum pathology but was only present in a minority of patients (sensitivity 40%). Previous studies have reported that asymmetric frontotemporal atrophy was highly specific for FTD compared with AD or vascular dementia. [START_REF] Kitagaki | Frontotemporal dementia and Alzheimer disease: evaluation of cortical atrophy with automated hemispheric surface display generated with MR images[END_REF][START_REF] Varma | Diagnostic patterns of regional atrophy on MRI and regional cerebral blood flow change on SPECT in young onset patients with Alzheimer's disease, frontotemporal dementia and vascular dementia[END_REF] The present study confirms this finding for PA, but indicates thatwhereas the presence of disproportionate frontotemporal atrophy strongly predicts FTDits absence by no means rules out pathology in the FTD spectrum.

Although this retrospective study was motivated by a search for pathological predictors identifiable in the setting of a neurological assessment, confrontational naming data were available for about three-quarters of the patient sample. Perhaps unsurprisingly, the AD group was more anomic in terms of "don't know" errors, possibly implying greater semantic involvement. That said, circumlocutions were comparable between groups, while single word substitutions (co-ordinate or super-ordinate) were more frequent in the FTD-spectrum group. Another interesting observation was that within the FTD-spectrum group, only those with FTD-T made phonological errors during confrontation naming. Although this could be interpreted as consistent with a previous study that reported apraxia of speech in FTD-T but not FTD-U, [START_REF] Josephs | Clinicopathological and imaging correlates of progressive aphasia and apraxia of speech[END_REF] it was notable that the Alzheimer group had a comparable prevalence of phonological errors to that seen in FTD-T.

It is important to emphasize that the naming data can only be treated as a preliminary observation and that detailed analysis of linguistic function was not possible. Further prospective studies are necessary to test whether language profiles can reliably predict pathology. In particular, within the spectrum of PA, recent evidence suggests that a fluent anomic syndrome (logopenic aphasia) is predictive of Alzheimer pathology, [START_REF] Rabinovici | Abeta amyloid and glucose metabolism in three variants of primary progressive aphasia[END_REF] while prominent motor speech disturbance (apraxia of speech) is predictive of the tauopathies: progressive supranuclear palsy and corticobasal degeneration. [START_REF] Josephs | Apraxia of speech and nonfluent aphasia: a new clinical marker for corticobasal degeneration and progressive supranuclear palsy[END_REF] Data thus far, however, have been derived from relatively small case series. Prospective studies would be helpful to examine the predictive value of language features and, particularly, to evaluate PA cases that defy neat syndromic classification.

A final caveat with respect to the demographic information must be highlighted. This was not a population-based epidemiological study; patients were recruited from referrals to a neurology-led cognitive disorders clinic. The clinic has some bias towards atypical dementia syndromes (such as PA) but there is quite possibly some additional bias towards younger-onset patients.

In conclusion, the present study highlights an emerging picture of clinical features that may help to discriminate PA patients with AD pathology from those with FTD-spectrum pathology (Table 4). Onset before 60 years, neuropsychiatric symptoms such as sweet food preference and disinhibition, and imaging features of knife-edge frontotemporal atrophy all show relative specificity for FTD-spectrum pathology. These can be added to the earlier finding that absence of posterior temporo-parietal lesions (using either FDG-PET or HMPAO-SPECT) was also highly specific for PA with FTD-spectrum pathology. [START_REF] Nestor | Nuclear imaging can predict pathologic diagnosis in progressive nonfluent aphasia[END_REF] While it is important to note that each of these features lacks sensitivity in isolation, it is rare for a PA patient with FTD-spectrum pathology to exhibit none of these features. In contrast it is common for all of these features to be absent in PA with AD pathology. Finally, the study highlights that impairment of global function within the first two years, poor memory and onset before 65 years are not useful in discriminating AD pathology from FTD-spectrum pathology. Table 5. Clinical and imaging features with utility in distinguishing AD from FTD-spectrum pathology in PA (*predictive of AD pathology, all others predictive of FTD-spectrum pathology).

•

  Figure 1a. Proportion of different pathology in clinically diagnosed PA patients. AD=Alzheimer's disease; FTD-U=ubiquitin-positive FTD; DLDH=Dementia lacking distinctive histology; Tauopathies=tau-positive pathology; CBD=corticobasal degeneration; PSP=progressive supranuclear palsy; Pick=Pick's disease. Figure 1b. Age of onset according to pathology classification. Figure 1c. Survival curves of the two pathology groups.

Figure 2 .

 2 Figure 2. Structural imaging of three PA patients A, B: Frontal and temporal imaging of one FTD-spectrum pathology PA patient, with asymmetrical frontal and/or temporal lobe atrophy. C, D: Frontal and temporal imaging of one FTD-spectrum pathology PA patient, without asymmetrical frontal and/or temporal lobe atrophy. E, F: Frontal and temporal imaging of one AD pathology PA patient, without asymmetrical frontal and/or temporal lobe atrophy.

Table 1 .

 1 Demographic characteristics according to pathology classification

		FTD-spectrum
	AD pathology	pathology	P-value

Table 2 .

 2 Global function, ADLs and Rey figure scores according to the pathological classification. Time of intact ADLs is the duration from disease onset to the first impairment of activities of daily living.

			FTD-spectrum
	Features	AD pathology	pathology	P-value
	Preserved global function	8,n=13	16,n=20	0.43
	Time of intact ADLs (yrs)	4.64 (2.81),n=13	4.35 (2.72),n=20	0.77
	Rey figure Copy (/36)	25.59 (11.05),n=11	28.89 (8.71),n=14	0.43
	Rey figure Recall (/36)	8.36 (7.19),n=11	11.64 (6.92),n=14	0.26
	ADLs =activities of daily living.

Table 3 .

 3 Neuropsychiatric characteristics according to the pathological classification NPV=negative prediction value. Specificity, sensitivity, PPV and NPV are parameters for predicting FTD-spectrum pathology; scores in brackets indicate the time range (years) from symptom onset that these features emerged.

		AD	FTD-spectrum	Specificity	Sensitivity	PPV	NPV
	Feature	pathology	pathology	(%)	(%)	(%)	(%)	P-value
	Sweet food
	preference	1/13 (3)	5/20 (2.5-6)	92.3	25.0	83.3	44.4	0.36
	Disinhibition	3/13 (1.5-3.5)	9/20 (1-7.5)	76.9	45.0	75.0	47.6	0.28
	Apathy	4/13 (2.5-8)	8/20 (1.5-10.5) 69.2	40.0	66.7	42.9	0.72
	Absence of
	depression	8/13	11/20	38.5	55.0	57.8	35.7	1.00
	PPV=positive prediction value,

Table 4 .

 4 Confrontation naming as percentage of total with range in parentheses.

	Naming	FTD-spectrum	AD
	Overall proportion correct	78% (14-95)	60% (23-88)
	Error types:
	Don't know responses	8% (0-44)	36% (14-71)
	Semantic descriptions (circumlocutions) 8% (0-33)	14% (0-73)
	Single word semantic substitutions	50% (2-100)	22% (5-45)
	Phonological errors	15% (0-84)*	17% (0-46)
	Word Fragments	3% (0-20)	7% (0-33)
	Unclassifiable	15% (0-50)	4% (0-13)
	*Phonological errors were generated exclusively by the FTD-T subgroup.

Acknowledgements and funding:

This work was supported by Medical Research Council, UK, grants to PJN (G108/653) and JRH (RG35882) and the NIHR Cambridge Biomedical Research Centre. We are grateful to our patients and their families for participating in the research.

Competing interests: none declared.

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